release: bump 0.6.0 -> 0.6.1 (#192 )

Version bump for the v0.6.1 release shipping the B6 Bands & Channels family (#191): 429 -> 434 indicators.
feat(indicators): add B6 Bands & Channels family (429 -> 434) (#191 )
2026-06-07 00:13:58 +02:00 · 2026-06-07 00:03:02 +02:00 · 2026-06-06 22:48:56 +02:00 · 2026-06-06 22:38:34 +02:00 · 2026-06-06 21:32:35 +02:00 · 2026-06-06 21:09:05 +02:00
331 changed files with 81126 additions and 627 deletions
@@ -0,0 +1,3 @@
+# Shell scripts must keep LF line endings so they run on Linux/macOS CI and
+# local shells regardless of the committer's platform autocrlf setting.
+*.sh text eol=lf
@@ -60,7 +60,7 @@ Closes #
 - [ ] Public API changes are reflected in `CHANGELOG.md`
 - [ ] Public API changes are reflected in rustdoc / README / examples
 - [ ] No `todo*.md` or other local-only notes are staged
- [ ] License header / `LICENSE` reference unchanged (PolyForm-NC-1.0.0)
+- [ ] License header / `LICENSE` reference unchanged (MIT OR Apache-2.0)

 ## Notes for reviewers

@@ -6,6 +6,8 @@ updates:
    schedule:
      interval: weekly
    open-pull-requests-limit: 10
+    cooldown:
+      default-days: 7
    commit-message:
      prefix: "deps(cargo)"

@@ -15,6 +17,8 @@ updates:
    schedule:
      interval: weekly
    open-pull-requests-limit: 10
+    cooldown:
+      default-days: 7
    commit-message:
      prefix: "deps(npm)"

@@ -24,9 +28,26 @@ updates:
    schedule:
      interval: weekly
    open-pull-requests-limit: 10
+    cooldown:
+      default-days: 7
    commit-message:
      prefix: "deps(pip)"

+  # Hash-pinned CI/bench Python tooling under .github/requirements/. Each
+  # <name>.in is the loose source; the matching hash-locked <name>.txt is the
+  # output regenerated by scripts/update-lockfiles.sh (uv). Dependabot keeps the
+  # pins fresh; ci-dev-py39.in caps numpy <2.1 so 3.9 stays installable. Any
+  # bump that breaks a matrix row surfaces in the PR's CI run.
+  - package-ecosystem: pip
+    directory: "/.github/requirements"
+    schedule:
+      interval: weekly
+    open-pull-requests-limit: 10
+    cooldown:
+      default-days: 7
+    commit-message:
+      prefix: "deps(ci-pip)"
+
  # GitHub Actions — keeps the SHA-pinned actions current (Dependabot reads
  # the version comment after each pinned SHA and bumps both together).
  - package-ecosystem: github-actions
@@ -34,5 +55,7 @@ updates:
    schedule:
      interval: weekly
    open-pull-requests-limit: 10
+    cooldown:
+      default-days: 7
    commit-message:
      prefix: "deps(actions)"
@@ -0,0 +1,11 @@
+# Python deps + peer TA libraries for the bench.yml cross-library benchmark.
+# Loose source spec — the pinned, hash-locked output is generated from this:
+#   bench.txt  (Python 3.11)  via scripts/update-lockfiles.sh
+# bench.yml runs on a single Python version (3.11), so one output suffices.
+maturin
+numpy
+pandas
+TA-Lib
+tulipy
+talipp
+finta
@@ -0,0 +1,247 @@
+# This file was autogenerated by uv via the following command:
+#    ./scripts/update-lockfiles.sh
+build==1.5.0 \
+    --hash=sha256:13f3eecb844759ab66efec90ca17639bbf14dc06cb2fdf37a9010322d9c50a6f \
+    --hash=sha256:302c22c3ba2a0fd5f3911918651341ebb3896176cbdec15bd421f80b1afc7647
+    # via ta-lib
+colorama==0.4.6 \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via build
+finta==1.3 \
+    --hash=sha256:b94b94df311c18bf5402eb2fe8fd2db5e1bdaff08baf58a7367d05c7abdd10d3 \
+    --hash=sha256:f2fa0673748f4be8f57e57cf6d5c00a4d44bc6071ea69dbb9a1d329d045cbba2
+    # via -r .github/requirements/bench.in
+maturin==1.13.3 \
+    --hash=sha256:0ef257e692cc756c87af5bea95ddfe7d3ac49d3376a7a87f728d63f06e7b6f8b \
+    --hash=sha256:1cc0a110b224ca90406b668a3e3c1f5a515062e59e26292f6dbaf5fd4909c6f3 \
+    --hash=sha256:2389fe92d017cea9d94e521fa0175314a4c52f79a1057b901fbc9f8686ef7d0b \
+    --hash=sha256:3cc13929ca82aefa4adbf0f2c35419369796213c6fb0eb24e914945f50ef5d8c \
+    --hash=sha256:3db93337ed97e60ffc878aa8b493cd7ae44d3a5e1a37256db3a4491f57565018 \
+    --hash=sha256:4667ef609ab446c1b5e0bfe4f9fb99699ab6d8548433f8d1a684256e0b67217f \
+    --hash=sha256:49fd6ab08da28098ccf37afca24cdba72376ba9c1eedf9dd25ff82ed771961ff \
+    --hash=sha256:4cd478e6e4c56251e48ed079b8efd55b30bc5c09cf695a1bdafaeb582ee735a0 \
+    --hash=sha256:53b08bd075649ce96513ad9abf241a43cb685ed6e9e7790f8dbc2d66e95d8323 \
+    --hash=sha256:771e1e9e71a278e56db01552e0d1acfd1464259f9575b6e72842f893cd299079 \
+    --hash=sha256:a2675e25f313034ae6f57388cf14818f87d8961c4a96795287f3e155f59beb11 \
+    --hash=sha256:b6741d7bf4af97da937528fd1e523c6ab54f53d9a21870fa735d6e67fd88e273 \
+    --hash=sha256:c00ea6428dea17bf616fe93770837634454b28c2de1a876e42ef8036c616079a \
+    --hash=sha256:def4a435ea9d2ee93b18ba579dc8c9cf898889a66f312cd379b5e374ec3e3ad6
+    # via -r .github/requirements/bench.in
+numpy==2.4.6 \
+    --hash=sha256:001fbb8e08d942dd57599e781f2472269ee7f2755fae407b4f67b2f0b17da3f1 \
+    --hash=sha256:0280e0356c0829a18d9de1cb7eee50ec22ca639878d7240307ca0943d73cd2c4 \
+    --hash=sha256:043191bfa8eab18c776647b62723ac9dddece59743b13f49b2016094129c2b3f \
+    --hash=sha256:06ca2f61ec4385a07a6977c55ba998a4466c123642b4a32694d3128fce18c079 \
+    --hash=sha256:0a041d3d761dc3c35cc56ce0351506a02bcbc25f7b169f652435141a17db9096 \
+    --hash=sha256:0ab0a9c4ffb1a6d95ef519fe4247dba8eb6b18ad93999f76b7f657039acabd47 \
+    --hash=sha256:0c9136e14ed34a9e343a31c533d78a9813a69a3148332bce5e9821cb2f996e66 \
+    --hash=sha256:110f8b71aacb688ec69062bb7f6938a0f8acb01b7c1c4beb453c65b6d234584d \
+    --hash=sha256:112b06a867b235ef466ed3508ddf0238050df9c727cafb5301ac385b899189a1 \
+    --hash=sha256:17f9ade344e7d9b464a084d69bcf18fc691cb1db67c62ed80820bf4926d78f0e \
+    --hash=sha256:1e254a00cdf42b1e4d5b3d68d33af63268d41340d8885df2ab6470f2e1500147 \
+    --hash=sha256:1e978ec1e8bd0e0e4de6bb75de9d30cbb74db6b6a2bb727618613703ca0167dd \
+    --hash=sha256:25c692919ac5a01f170a3bfcd62d745b24fd095c353d50812637d6fcab442e75 \
+    --hash=sha256:260a5d70215b61ab4fadf5c7baacd64821842975eea312125ed3c39a6391b063 \
+    --hash=sha256:2803abfebfc990042cd494d8ce2d5f82e9d847af6d35ec486923aa19dbad5e73 \
+    --hash=sha256:29a287e0cf63ff528da061de6b9f64a4618da591ca1046aafc54062e40ca7eab \
+    --hash=sha256:29cb7f67d10b479ff07c17d33e39f78c07f71c40ef30d63c153d340e96cd3fb4 \
+    --hash=sha256:3213d622a0283a39a93d188f3cf72b26862df52fbb4ca3697f51705016523d41 \
+    --hash=sha256:33111801a01c12a8a1e3721f0a9232f8cfc8ae2c6b7098167e6f623c6073f402 \
+    --hash=sha256:357cc07a6d7b0b182ff02249616a03742827ebb1277546b5c7cd7f7620a45698 \
+    --hash=sha256:38efbc8de75c7a0fc1ac190162d892787f3f47b57cc291231aafee36b80982b7 \
+    --hash=sha256:4081eb135ac24158bd51cdfbef16f1c64df7063b1143f24731387137c092bec8 \
+    --hash=sha256:40fdc1ae7125e518ea98e53e69a4ebc27e1fd50510c47b7ea130cf21e5e1d42b \
+    --hash=sha256:4cfe66903cc32a9921a6733d96b19bb6abf310397581bbad89c228f5abaf0ee8 \
+    --hash=sha256:511dbaf848decaaaf4b4ca48032619fb3138710c4bf7da7617765edad1ef96b0 \
+    --hash=sha256:55cced7c52e981362f708ad635198e97a752dfba412cc03c23bbf3bd8d5cd662 \
+    --hash=sha256:56b39e5e0622a09a25bf5baf62f4bcf0cb8a41ae6e2819cf49bbc5a74c083f91 \
+    --hash=sha256:5dbbdb29840ca3d91ee0fece42fc29278886d908280bfec0a5846c6f901a3eb0 \
+    --hash=sha256:5f9fb9157b4ce2971008323afe46053787b526ef624fea915b261468a8421a0f \
+    --hash=sha256:6180d8b35af935aed8ece3a85e0a43f87393ae0ac87c8d2c8bd2c993f7270ef3 \
+    --hash=sha256:68a5124b13fa6cc2086764a20005d30bc0548146f7f5322f02fce212ca14317f \
+    --hash=sha256:68bb27509ac1b9a3443094260f6326150663b06abe40b73a2f81160623da5b67 \
+    --hash=sha256:6f41ae150c4e32db4f3310cdaf64b1593a03dbabe29eec77fc9b50fe64061df6 \
+    --hash=sha256:7265a2f3d436e54ef9f2b52b5c937e6be778781bd97a590319d7348f1c1ca997 \
+    --hash=sha256:72fbe16c6fac95aedf5937fa873445cec2110be35d8a4e9433d7501fd98dae6b \
+    --hash=sha256:7d92c3819208a60205a12a245c91ad70cb0a85336659b19b834205573ac8456e \
+    --hash=sha256:8155154c7c691289fe18f510b5d4657c68c67989f293f0535a91360392ff6538 \
+    --hash=sha256:81a1cca95ed5bb92aa8b10dd2cdc9a0d3853a50fad926c28b5d7e8ea54389627 \
+    --hash=sha256:89cd468399cfd2504718f0ba50e410dca55a170b61a02ad92bb18c8a65186e93 \
+    --hash=sha256:8ad03c0965fb3c692200e74d458ca28c1dbb4ce96f9a479a8aa041ad5fabca02 \
+    --hash=sha256:90f9849678c75fe7afa2d348ac842c168b0a4d3d61919687216dfc547976d853 \
+    --hash=sha256:948424b06129ce883307e8cff868c31396d8dc7630a59c61d70d98dbe70f222c \
+    --hash=sha256:9cd5ffd25db4e7ba6a375693b3fc0fc1791ec636c17db3720da19bde7180ec43 \
+    --hash=sha256:a0df0043bdb289bde1f62da130d20df23d58b45429f752bc7a8fc5325a225ecd \
+    --hash=sha256:a2c306dea656c12c68f51f4cea133cbe78ca7435eb28c735eac1d3ebe73be6e8 \
+    --hash=sha256:a7830bab239b79cda9c08c2da014761cafb48da6150e1da17ac06283f43b6089 \
+    --hash=sha256:a7c711e21628b52034bb5ab8d1bce291f752fcc5e92accc615778acee1ff4778 \
+    --hash=sha256:aaf159caa35993cb1f56fb9b8e4610d35758e7ca005412eb1daa856a78c9c4b1 \
+    --hash=sha256:ae506e6902902557576a26ff33eda8695e7ecb3cb36c3b573a0765dee114ebdb \
+    --hash=sha256:b507f5c4c1d508876d1819b6bf9a49d365b96320b5d4993426b33a23ca4b8261 \
+    --hash=sha256:bf162abab1c1a736333192707cef898e735a5ca00f38f27eeedf44b39d9e85eb \
+    --hash=sha256:c1a2af6c6ef86344a6b0db6b97834208bf598db514f2b155042439b62605601a \
+    --hash=sha256:c2d37ab77531417474168eb79d6d80b14f821a966818505d03013d0833edb7a8 \
+    --hash=sha256:c4fc99836233ea196540b17ab0983aff60ed07941751930f5f4d05bc3b3b7359 \
+    --hash=sha256:d581b735e177fdcdce6fed8e7e8880a3fb6ee4e3653a3ac6af01c6f4c03effc5 \
+    --hash=sha256:d6da64deb6b8ed903e7560180a92f2d804ee1ba5eeb849ac2748b8c1aba1f6d7 \
+    --hash=sha256:d8e8286dd7cea7895157318d1b91cdacac64c479f3cbc8dce548331728484751 \
+    --hash=sha256:ddea102b48f9e339f3948bf22040944184627a30fdf7f858667673b9c5f033c8 \
+    --hash=sha256:dfa20cc6ca228e6b155b11da03825975ce66aea520985dbbddf0f2a5a495c605 \
+    --hash=sha256:e3e5193ef5a3dc73bceee50f7fdc2c90dbb76c42df8d8fae3d1067a583df579e \
+    --hash=sha256:e3eeb0aabd6bd5ce64faae67e9935203a6991b4bc2a485a767fbafb2c5125f45 \
+    --hash=sha256:e5805d5a22fd19c8ccff10a9561f9df94436b0545619ea579db2d3c35294bce2 \
+    --hash=sha256:e85b752a1e912b70eaad4fafbd4d1238007ab221de2009b9a2f5ae7461239895 \
+    --hash=sha256:eaf7fa2de5c0be8ae6ff8e9bea2ccd725e980541244521d8d4b5f3354a27babe \
+    --hash=sha256:ebfb099f8dcf083deef3ac1ca4c1503f387cf76296fcb3816b66f5ecb5f54fdb \
+    --hash=sha256:ece3d2cfe132e7d51f44a832b303895e6f2d499c5e74dfbdb06ee246147a304a \
+    --hash=sha256:ed9749eef4cbd126da3dc1d6bcb3a57f5eb7ac6a6484146bdbf743f552dfc577 \
+    --hash=sha256:ede83e07a75dd06bc501566c1eca2afc0d61677c1472ac9ad93fdee6e638a48d \
+    --hash=sha256:ef4aea96ce4d3b074422cb4f2f64e216bf9e213004bb58ecfdf50ea02ea8eb9a \
+    --hash=sha256:f3a3570c4a2a16746ac2c31a7c7c7b0c186b95ce902e33db6f28094ed7387dda \
+    --hash=sha256:f407cb6b8e9d6d8c626bc73c945db1706035af8fd632295547bf1c9e46d092d6 \
+    --hash=sha256:f74a575920ab21fe304421a3fc28793d82e299cae9eccb37084e9fc7f3617c20
+    # via
+    #   -r .github/requirements/bench.in
+    #   finta
+    #   pandas
+    #   ta-lib
+    #   tulipy
+packaging==26.2 \
+    --hash=sha256:5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e \
+    --hash=sha256:ff452ff5a3e828ce110190feff1178bb1f2ea2281fa2075aadb987c2fb221661
+    # via build
+pandas==3.0.3 \
+    --hash=sha256:0383c72c75cdcca61a9e116e611143902dbfd08bff356829c2f6d1cf40a9ca8c \
+    --hash=sha256:05f1f1752b8533ea03f7f39a9c15b1a058d067bb48f4748948e7a8691e0510f2 \
+    --hash=sha256:08d789b41f87e0905880e293cedf6197ce71fe67cc081358b1e148a491b9bd13 \
+    --hash=sha256:0d589105b3c14645af1738ff279b2995102d8f7a03b0a66dc8d95550eb513e04 \
+    --hash=sha256:13fc1e853d9e04743d11ba75a985ccbc2a317fe07d8af61e445a6fd24dacd6a6 \
+    --hash=sha256:14da8316da4d0c5a77618425996bfb1248ca87fc2c1486e6fde4652bd18b5824 \
+    --hash=sha256:1928e07221f82db493cd4af1e23c1bfca524a19a4699887975bff68f49a72bfb \
+    --hash=sha256:261e308dfb22448384b7580cf719d2f998fe2966c92893c3e77d14008af1f066 \
+    --hash=sha256:275c14e0fce14a2ec20eee474aecd305478ea3c1e6f6a9d8fe219a165542717e \
+    --hash=sha256:335f62418ed562cfc3c49e9e196375c28b729dcef8543abf4f9438e381bf3c76 \
+    --hash=sha256:3650109c0f22879df8bd6179ab9ee3d7f1d1d4e7e0094a3f0032d9f51e2e64ac \
+    --hash=sha256:39436b377d56d2a2e52d0395bdbee171f01068e99af5250509aceeb929f765c7 \
+    --hash=sha256:3c20a521bbb85902f79f7270c80a59e1b5452d96d170c034f207181870f97ac5 \
+    --hash=sha256:3e91cec1879ada0624fc3dc9953c5cbd60208e59c0db28f540c5d6d47502422f \
+    --hash=sha256:455f6f8139d4282188f526868dbc3c828470e88a3d9d59a891bd46a455f21b98 \
+    --hash=sha256:46997386d528eb40376ecd6b033cf4a8a1e5282580f68f43de875b78cba2199d \
+    --hash=sha256:4db8c527972a821cf5286b40ccc57642a39bc62e62022b42f99f8a67fca8c3a1 \
+    --hash=sha256:4e15135e2ee5df1063313e2425ceef8ac0f4ae775893815b0923651b806a5639 \
+    --hash=sha256:51b1fe551acb77dac643c6fda86084d8d446c10fe64b06a9cc29c4cc8540e7f2 \
+    --hash=sha256:557409bc4178e70ee8d9ddb494798e51ebf6ea59330f6be22c51bab2a7db6c49 \
+    --hash=sha256:5cc09a68b3120e0f54870dede8287a7bb1fa463907e4fcec1ea77cab6179bf7a \
+    --hash=sha256:60ae316d3fd75d1858d450d0db0103ea2be3e7d4a95ec2f064f7e2ae63f7b028 \
+    --hash=sha256:6674ab18ad8c57802867264b00e15e7bb904700cdd9046e3b2fa1fce237439ea \
+    --hash=sha256:67b3b64c11910cfa29f4e94a14d3bff9ee693b6fc76055e7cad549cee0aec5fa \
+    --hash=sha256:696a4a00a2a2a35d4e5deb3fc946641b96c944f02230e4f76137fe35d806c4fc \
+    --hash=sha256:6dc0b3fd2169c9157deed50b4d519553a3655c8c6a96027136d654592be973a9 \
+    --hash=sha256:7e65d5407dc0b394f509699650e4a2ec01c0514f21850f453fa60f3be79a5dbf \
+    --hash=sha256:819959dab7bbd0049c15623fbac4e29a191b9528160a61fb1032242d8ced2d9c \
+    --hash=sha256:8a1e45c80cceb3b4a21bc5939d52e8cbd8d9b7305309219d59e9754d9ce09e27 \
+    --hash=sha256:9c39be2d709d01fa972a0cabc522389fceca4f3969332ba25a7d6c5802cf976a \
+    --hash=sha256:9d71c63ae4ebdbf70209742096f1fc46a83a0613c99d4b23766cced9ff8cd62a \
+    --hash=sha256:a2d2dff8a04f3917b55ab3910c32990f8ddf7eceba114947838cefa976a68977 \
+    --hash=sha256:a4eeb6830daf35a71cc09649bd823e2b542dac246cdee9614c6e4bd65028cd6a \
+    --hash=sha256:a55066a0505dae0ba2b50a46637db34b46f9094c65c5d4800794ef6335010938 \
+    --hash=sha256:a82d532a3351d435432cd913edbccaf8b8e01d4dd0e5ced5a8d2e8ecd94c7e44 \
+    --hash=sha256:b168fc218fd80a6cbdbdbc1a97ddc7889ed057d7eb45f50d866ceab5f39904c4 \
+    --hash=sha256:b2c95f8bfc1ee412bf482605d7bfd30c12d1d26bd59fdd91efeef1d4718decb1 \
+    --hash=sha256:ba7e08b9ac1d54569cd1e256e3668975ed624d6826f7b68df0342b012007bddb \
+    --hash=sha256:bab900348131a7db1f69a7309ef141fd5680f1487094193bcbbb61791573bf8f \
+    --hash=sha256:bd3a518890b400d32f9023722dc9a9a5c969f00b415419a3c06c043f09bb5d7d \
+    --hash=sha256:c7be265b62cef88e253a941e4698604973736dcfe242fdb5198f0f7bc473cdcc \
+    --hash=sha256:d26cbe1fcfc12e8fd900e2454163e466b2d3af84f7c75481df7683ffc073d870 \
+    --hash=sha256:d4be06d68f9ddcfc645b87534911da79a8fbffc7573c80e0edcf42a5020624d8 \
+    --hash=sha256:d72828c20c6d6e83e1e22a6a3b47b326b71664112fa9705dcbccfd7a39b62085 \
+    --hash=sha256:dd1a5d1def6a46002e964510bdc67c368aa0951df5d1d9f8365336f5a1f490cd \
+    --hash=sha256:e3a2ec42c98ffa2565a67e08e218d06d72576d758d90facb7c00805194d8f360 \
+    --hash=sha256:f8894dc474d648fe7b6ff0ca9b0bd73950d19952bc1a6534540762c5d79d305c \
+    --hash=sha256:fed2ff7fd9779120e388e285fc029bd5cf9490cdd2e4166a9ee22c0e49a9ab09
+    # via
+    #   -r .github/requirements/bench.in
+    #   finta
+pyproject-hooks==1.2.0 \
+    --hash=sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8 \
+    --hash=sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913
+    # via build
+python-dateutil==2.9.0.post0 \
+    --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
+    --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
+    # via pandas
+six==1.17.0 \
+    --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
+    --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
+    # via python-dateutil
+ta-lib==0.6.8 \
+    --hash=sha256:02388054c059945e5f02625f5075bac20a1803573cb43e7d096091027511961f \
+    --hash=sha256:094677b279a59c3f01c3aca8a889fda3523fd641a3805f69a2d642121b72e55e \
+    --hash=sha256:0a08a29690a922ba92a6cf42902a8a93c6fbda4cfed62c3c5b0471560ef60135 \
+    --hash=sha256:0ccd478ff5735831bf2a61d653466bfda8afadc26ad58ca6b1edb9e7521cc674 \
+    --hash=sha256:0e371d14b49e70caa973a234c8823341dd446f5c5d7acc826868bb42b272bdc0 \
+    --hash=sha256:11a373c9308eae3bac2d56d37017f9ab63968cc074a8b95be879aae3d13133aa \
+    --hash=sha256:128ec92e6a0e9ff7a38edef80e3b74f15bb2ed1c531d5d3252c8dca22677651b \
+    --hash=sha256:1fb4028437201e19014e4e374272b739867c8a3eb655da46675ef4c2ff14b616 \
+    --hash=sha256:282e49c766b5952dd8796f77d7ed3ae412cdd88e31f845b1fbbb86ac6cb7bebf \
+    --hash=sha256:2b369cabb48485fbf444beb3f5a878075367b99c2c86db2f796afeabebc749e0 \
+    --hash=sha256:2bf714333788bf5175f2512b86d2ed129e89ae6f6c2923e8a297a1e3395e13b5 \
+    --hash=sha256:30de46b55873b51be945a09edf486afcc190dc47eff9fb5d2b12c9f7e3d743da \
+    --hash=sha256:34e3b12407ddf99f6627435aa8a165f094339bb7dc33de92e1d7472e9f237304 \
+    --hash=sha256:36b2a516fce57309840f5ef3fa2fd0c4449293fc72536a0400d2e1e26b414da8 \
+    --hash=sha256:3a9195299df9d7d2a6e9d16bebd6b706b0ea99e4b871864c4b034c2577e21a77 \
+    --hash=sha256:3c32fc0f546ceecc47dd45f33d72ab4a1e341b80d9081c2d77b100add5d49104 \
+    --hash=sha256:3d7333e907bff3e3997e54f89733ffa8d619842a3e1cd962bca34bdc11944c28 \
+    --hash=sha256:4795e93d130c9b7fb661f0cead49752ae6a980437df74b99d5918026c212443e \
+    --hash=sha256:490e19a45cd3cdd6dfe6b46019f7ffe1103500750b41b51996a870e7c1c5f066 \
+    --hash=sha256:4aa0fe08383f3e5fc7d2f8cf9b42ac778f4d53fd75bcd2799a858225954eab89 \
+    --hash=sha256:559326d8f3d904cd4aa61f6a392d5626f35eec6a9f6cc83bcddb0abf88c40516 \
+    --hash=sha256:5929c83bd8cb7572d1c17ffdbf0eac235bf3c4d53cde1950cf89d944eaf97525 \
+    --hash=sha256:5bfd21b6acb32e20d4e279c34405a34e63da345be4b2b6eabd683e1a88857406 \
+    --hash=sha256:613cf06313331f49dd7b85a5a24fbddb1156c9723b6921a231906241726e5aee \
+    --hash=sha256:66a8e1c1e899d15a2f7510e43527fba22d895e7f6058d027db3e3837d88a69de \
+    --hash=sha256:691a62926ba09f2653ec0908554b3635497efb7751c5d46b916cd1ebbb1d3c25 \
+    --hash=sha256:6c1fd18e45c39d5a4be4b0d6a20c141e43fe46daeb1b2e2f304ebae7015ab6e6 \
+    --hash=sha256:6c6a1e8f98de92e817491b50aa4d01d69a1b41a4ed3173747e8f16f0d4cf81cc \
+    --hash=sha256:6cf029b886cfb28a2701503b7c602b811f2daa45276bd6459b0c71e051deb497 \
+    --hash=sha256:71506116eac0d3e3598d6325b4b818c3a0f6acb3222b24d30ad726e8c4bf7ea8 \
+    --hash=sha256:7993164e8e9f78ec31d38c47850ca6ba5451788b5b49a8a2dbb3322b36b5693b \
+    --hash=sha256:7a5cc6bf60791d8274edfdfe2dd7cec3f00f656dcc92e2b0a9af06c8b18ce6a6 \
+    --hash=sha256:87c1cc1057d903b78a8257a7c5f497db6fd5284f5080392bd57b66031d7389a3 \
+    --hash=sha256:98376c75bd6c103c74396953084a5e0798ffe476aecbfcc51ec6d100a685ac38 \
+    --hash=sha256:a395524b0fafa10446d11e11acb4742e919523de58aac03b791f26d7a783bcf0 \
+    --hash=sha256:a5100a4be91b7d4b7c8fe16a3600bd0951e10205eb1066b6873afd3996b51ee4 \
+    --hash=sha256:a63a52221f8c73f82f4e00493351d987f594931198589287aee96f8da673cfd5 \
+    --hash=sha256:a89734a7bcb2ea3b6fd600a74d6fbcdb8d3fa3f7917dbd978e039710b5509c9c \
+    --hash=sha256:b165f5e6de1ccc964e863bd2035807a4d3bad3e0481f9db2dc52034d6ad4f9de \
+    --hash=sha256:b3845e4c2fa32963fb7f384ebbaa2761b0e6b96145239bf80e956d4aff4b071c \
+    --hash=sha256:b3b017d9103e7a7372a146773be32b184ff7330bd708d40b1f56f06a686756ed \
+    --hash=sha256:b6c6e4858d8c3f88e19b7aa94b6a7619108f0bee51da9fa67b0785a8b59955f9 \
+    --hash=sha256:bfad1202fb1f9140e3810cc607058395f59032d9128cc0d716900c78bea5f337 \
+    --hash=sha256:c01809fb602e2fefc8cbfb3b603bb59d2a2eaee8708410896d48a835ba00e7c5 \
+    --hash=sha256:cce8de9d48289927ed18aaa420740efd52b2cd9289da32e3799afbb3a02822e8 \
+    --hash=sha256:ce2bc1ea01200b6d8130ab917296d05d77a1a571ec6c1ee25cfca6d55cd5db4a \
+    --hash=sha256:d4601e2a8b46ffbf540601a4926fd6cc5aae8a13b36fdd467f1040f01f9edaed \
+    --hash=sha256:d556d1c256b3700b60b6b061664a667b2e49d599c2772d46a9f2348f2dc4ab5c \
+    --hash=sha256:ddf7453acd03b966624ebefdb38169b5bbbeea1a1a58c90b095667247f9de327 \
+    --hash=sha256:e781eeb65b2007af553389c8a7fb7bc53cb856118b0fcffb2c26b0f49561c686 \
+    --hash=sha256:e920c272cd9e70a6b10eae9203cc96845da142e1dd4482de9343dda3738a9862 \
+    --hash=sha256:f5b6174bf4bf9152e368561dff410203c6921e4dd2afbcda3283a95957158112 \
+    --hash=sha256:f69bd42fd2515060af69b120668213121264bb7976b113954b6f9db327727c65 \
+    --hash=sha256:f823d0f6b04a6797fbe253bcf91666e71a6b63c290683819650c68b2468ebe64 \
+    --hash=sha256:fa7e9f2e80a9535f9692e113d02b4268b5f88675a730d1b0ef0abeb74c9a4e80
+    # via -r .github/requirements/bench.in
+talipp==2.7.0 \
+    --hash=sha256:567f59ad74366cb59a14a00d350f35fd9d22e6924d6228bad581e6dcf1de2205 \
+    --hash=sha256:f749f22b9ad615605e71faf26457bb7f5e3fe16f04d3287f4ca54fd16bc3d4eb
+    # via -r .github/requirements/bench.in
+tulipy==0.4.0 \
+    --hash=sha256:540704956b5b940a5f6306aa393a37536a6d7c3cbc07efe47512f3496e5203ab \
+    --hash=sha256:95542e40537afdd345d875baf37485eac993c6a819d00c51432e9de8df21eba8 \
+    --hash=sha256:fbc31727ef7657c93ad910bfdce65fecc6aaa7a5e961fe00240718e7a3fc79d8
+    # via -r .github/requirements/bench.in
+tzdata==2026.2 \
+    --hash=sha256:9173fde7d80d9018e02a662e168e5a2d04f87c41ea174b139fbef642eda62d10 \
+    --hash=sha256:bbe9af844f658da81a5f95019480da3a89415801f6cc966806612cc7169bffe7
+    # via pandas
@@ -0,0 +1,7 @@
+# Python 3.10+ dev/test tooling for the ci.yml binding test job
+# (covers the 3.11 / 3.12 / 3.13 matrix rows). Locked output: ci-dev-py3.txt
+# Refresh via scripts/update-lockfiles.sh.
+maturin
+pytest
+numpy
+hypothesis
@@ -0,0 +1,124 @@
+# This file was autogenerated by uv via the following command:
+#    ./scripts/update-lockfiles.sh
+colorama==0.4.6 \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via pytest
+hypothesis==6.155.1 \
+    --hash=sha256:07c102031612b98d7c1be15ca3608c43e1234d9d07e3a190a53fa01536700196 \
+    --hash=sha256:2753f469df3ba3c483b08e0c37dbcbc41d8316ebb921abcc07493ee9c8a7d187
+    # via -r .github/requirements/ci-dev-py3.in
+iniconfig==2.3.0 \
+    --hash=sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730 \
+    --hash=sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12
+    # via pytest
+maturin==1.13.3 \
+    --hash=sha256:0ef257e692cc756c87af5bea95ddfe7d3ac49d3376a7a87f728d63f06e7b6f8b \
+    --hash=sha256:1cc0a110b224ca90406b668a3e3c1f5a515062e59e26292f6dbaf5fd4909c6f3 \
+    --hash=sha256:2389fe92d017cea9d94e521fa0175314a4c52f79a1057b901fbc9f8686ef7d0b \
+    --hash=sha256:3cc13929ca82aefa4adbf0f2c35419369796213c6fb0eb24e914945f50ef5d8c \
+    --hash=sha256:3db93337ed97e60ffc878aa8b493cd7ae44d3a5e1a37256db3a4491f57565018 \
+    --hash=sha256:4667ef609ab446c1b5e0bfe4f9fb99699ab6d8548433f8d1a684256e0b67217f \
+    --hash=sha256:49fd6ab08da28098ccf37afca24cdba72376ba9c1eedf9dd25ff82ed771961ff \
+    --hash=sha256:4cd478e6e4c56251e48ed079b8efd55b30bc5c09cf695a1bdafaeb582ee735a0 \
+    --hash=sha256:53b08bd075649ce96513ad9abf241a43cb685ed6e9e7790f8dbc2d66e95d8323 \
+    --hash=sha256:771e1e9e71a278e56db01552e0d1acfd1464259f9575b6e72842f893cd299079 \
+    --hash=sha256:a2675e25f313034ae6f57388cf14818f87d8961c4a96795287f3e155f59beb11 \
+    --hash=sha256:b6741d7bf4af97da937528fd1e523c6ab54f53d9a21870fa735d6e67fd88e273 \
+    --hash=sha256:c00ea6428dea17bf616fe93770837634454b28c2de1a876e42ef8036c616079a \
+    --hash=sha256:def4a435ea9d2ee93b18ba579dc8c9cf898889a66f312cd379b5e374ec3e3ad6
+    # via -r .github/requirements/ci-dev-py3.in
+numpy==2.4.6 \
+    --hash=sha256:001fbb8e08d942dd57599e781f2472269ee7f2755fae407b4f67b2f0b17da3f1 \
+    --hash=sha256:0280e0356c0829a18d9de1cb7eee50ec22ca639878d7240307ca0943d73cd2c4 \
+    --hash=sha256:043191bfa8eab18c776647b62723ac9dddece59743b13f49b2016094129c2b3f \
+    --hash=sha256:06ca2f61ec4385a07a6977c55ba998a4466c123642b4a32694d3128fce18c079 \
+    --hash=sha256:0a041d3d761dc3c35cc56ce0351506a02bcbc25f7b169f652435141a17db9096 \
+    --hash=sha256:0ab0a9c4ffb1a6d95ef519fe4247dba8eb6b18ad93999f76b7f657039acabd47 \
+    --hash=sha256:0c9136e14ed34a9e343a31c533d78a9813a69a3148332bce5e9821cb2f996e66 \
+    --hash=sha256:110f8b71aacb688ec69062bb7f6938a0f8acb01b7c1c4beb453c65b6d234584d \
+    --hash=sha256:112b06a867b235ef466ed3508ddf0238050df9c727cafb5301ac385b899189a1 \
+    --hash=sha256:17f9ade344e7d9b464a084d69bcf18fc691cb1db67c62ed80820bf4926d78f0e \
+    --hash=sha256:1e254a00cdf42b1e4d5b3d68d33af63268d41340d8885df2ab6470f2e1500147 \
+    --hash=sha256:1e978ec1e8bd0e0e4de6bb75de9d30cbb74db6b6a2bb727618613703ca0167dd \
+    --hash=sha256:25c692919ac5a01f170a3bfcd62d745b24fd095c353d50812637d6fcab442e75 \
+    --hash=sha256:260a5d70215b61ab4fadf5c7baacd64821842975eea312125ed3c39a6391b063 \
+    --hash=sha256:2803abfebfc990042cd494d8ce2d5f82e9d847af6d35ec486923aa19dbad5e73 \
+    --hash=sha256:29a287e0cf63ff528da061de6b9f64a4618da591ca1046aafc54062e40ca7eab \
+    --hash=sha256:29cb7f67d10b479ff07c17d33e39f78c07f71c40ef30d63c153d340e96cd3fb4 \
+    --hash=sha256:3213d622a0283a39a93d188f3cf72b26862df52fbb4ca3697f51705016523d41 \
+    --hash=sha256:33111801a01c12a8a1e3721f0a9232f8cfc8ae2c6b7098167e6f623c6073f402 \
+    --hash=sha256:357cc07a6d7b0b182ff02249616a03742827ebb1277546b5c7cd7f7620a45698 \
+    --hash=sha256:38efbc8de75c7a0fc1ac190162d892787f3f47b57cc291231aafee36b80982b7 \
+    --hash=sha256:4081eb135ac24158bd51cdfbef16f1c64df7063b1143f24731387137c092bec8 \
+    --hash=sha256:40fdc1ae7125e518ea98e53e69a4ebc27e1fd50510c47b7ea130cf21e5e1d42b \
+    --hash=sha256:4cfe66903cc32a9921a6733d96b19bb6abf310397581bbad89c228f5abaf0ee8 \
+    --hash=sha256:511dbaf848decaaaf4b4ca48032619fb3138710c4bf7da7617765edad1ef96b0 \
+    --hash=sha256:55cced7c52e981362f708ad635198e97a752dfba412cc03c23bbf3bd8d5cd662 \
+    --hash=sha256:56b39e5e0622a09a25bf5baf62f4bcf0cb8a41ae6e2819cf49bbc5a74c083f91 \
+    --hash=sha256:5dbbdb29840ca3d91ee0fece42fc29278886d908280bfec0a5846c6f901a3eb0 \
+    --hash=sha256:5f9fb9157b4ce2971008323afe46053787b526ef624fea915b261468a8421a0f \
+    --hash=sha256:6180d8b35af935aed8ece3a85e0a43f87393ae0ac87c8d2c8bd2c993f7270ef3 \
+    --hash=sha256:68a5124b13fa6cc2086764a20005d30bc0548146f7f5322f02fce212ca14317f \
+    --hash=sha256:68bb27509ac1b9a3443094260f6326150663b06abe40b73a2f81160623da5b67 \
+    --hash=sha256:6f41ae150c4e32db4f3310cdaf64b1593a03dbabe29eec77fc9b50fe64061df6 \
+    --hash=sha256:7265a2f3d436e54ef9f2b52b5c937e6be778781bd97a590319d7348f1c1ca997 \
+    --hash=sha256:72fbe16c6fac95aedf5937fa873445cec2110be35d8a4e9433d7501fd98dae6b \
+    --hash=sha256:7d92c3819208a60205a12a245c91ad70cb0a85336659b19b834205573ac8456e \
+    --hash=sha256:8155154c7c691289fe18f510b5d4657c68c67989f293f0535a91360392ff6538 \
+    --hash=sha256:81a1cca95ed5bb92aa8b10dd2cdc9a0d3853a50fad926c28b5d7e8ea54389627 \
+    --hash=sha256:89cd468399cfd2504718f0ba50e410dca55a170b61a02ad92bb18c8a65186e93 \
+    --hash=sha256:8ad03c0965fb3c692200e74d458ca28c1dbb4ce96f9a479a8aa041ad5fabca02 \
+    --hash=sha256:90f9849678c75fe7afa2d348ac842c168b0a4d3d61919687216dfc547976d853 \
+    --hash=sha256:948424b06129ce883307e8cff868c31396d8dc7630a59c61d70d98dbe70f222c \
+    --hash=sha256:9cd5ffd25db4e7ba6a375693b3fc0fc1791ec636c17db3720da19bde7180ec43 \
+    --hash=sha256:a0df0043bdb289bde1f62da130d20df23d58b45429f752bc7a8fc5325a225ecd \
+    --hash=sha256:a2c306dea656c12c68f51f4cea133cbe78ca7435eb28c735eac1d3ebe73be6e8 \
+    --hash=sha256:a7830bab239b79cda9c08c2da014761cafb48da6150e1da17ac06283f43b6089 \
+    --hash=sha256:a7c711e21628b52034bb5ab8d1bce291f752fcc5e92accc615778acee1ff4778 \
+    --hash=sha256:aaf159caa35993cb1f56fb9b8e4610d35758e7ca005412eb1daa856a78c9c4b1 \
+    --hash=sha256:ae506e6902902557576a26ff33eda8695e7ecb3cb36c3b573a0765dee114ebdb \
+    --hash=sha256:b507f5c4c1d508876d1819b6bf9a49d365b96320b5d4993426b33a23ca4b8261 \
+    --hash=sha256:bf162abab1c1a736333192707cef898e735a5ca00f38f27eeedf44b39d9e85eb \
+    --hash=sha256:c1a2af6c6ef86344a6b0db6b97834208bf598db514f2b155042439b62605601a \
+    --hash=sha256:c2d37ab77531417474168eb79d6d80b14f821a966818505d03013d0833edb7a8 \
+    --hash=sha256:c4fc99836233ea196540b17ab0983aff60ed07941751930f5f4d05bc3b3b7359 \
+    --hash=sha256:d581b735e177fdcdce6fed8e7e8880a3fb6ee4e3653a3ac6af01c6f4c03effc5 \
+    --hash=sha256:d6da64deb6b8ed903e7560180a92f2d804ee1ba5eeb849ac2748b8c1aba1f6d7 \
+    --hash=sha256:d8e8286dd7cea7895157318d1b91cdacac64c479f3cbc8dce548331728484751 \
+    --hash=sha256:ddea102b48f9e339f3948bf22040944184627a30fdf7f858667673b9c5f033c8 \
+    --hash=sha256:dfa20cc6ca228e6b155b11da03825975ce66aea520985dbbddf0f2a5a495c605 \
+    --hash=sha256:e3e5193ef5a3dc73bceee50f7fdc2c90dbb76c42df8d8fae3d1067a583df579e \
+    --hash=sha256:e3eeb0aabd6bd5ce64faae67e9935203a6991b4bc2a485a767fbafb2c5125f45 \
+    --hash=sha256:e5805d5a22fd19c8ccff10a9561f9df94436b0545619ea579db2d3c35294bce2 \
+    --hash=sha256:e85b752a1e912b70eaad4fafbd4d1238007ab221de2009b9a2f5ae7461239895 \
+    --hash=sha256:eaf7fa2de5c0be8ae6ff8e9bea2ccd725e980541244521d8d4b5f3354a27babe \
+    --hash=sha256:ebfb099f8dcf083deef3ac1ca4c1503f387cf76296fcb3816b66f5ecb5f54fdb \
+    --hash=sha256:ece3d2cfe132e7d51f44a832b303895e6f2d499c5e74dfbdb06ee246147a304a \
+    --hash=sha256:ed9749eef4cbd126da3dc1d6bcb3a57f5eb7ac6a6484146bdbf743f552dfc577 \
+    --hash=sha256:ede83e07a75dd06bc501566c1eca2afc0d61677c1472ac9ad93fdee6e638a48d \
+    --hash=sha256:ef4aea96ce4d3b074422cb4f2f64e216bf9e213004bb58ecfdf50ea02ea8eb9a \
+    --hash=sha256:f3a3570c4a2a16746ac2c31a7c7c7b0c186b95ce902e33db6f28094ed7387dda \
+    --hash=sha256:f407cb6b8e9d6d8c626bc73c945db1706035af8fd632295547bf1c9e46d092d6 \
+    --hash=sha256:f74a575920ab21fe304421a3fc28793d82e299cae9eccb37084e9fc7f3617c20
+    # via -r .github/requirements/ci-dev-py3.in
+packaging==26.2 \
+    --hash=sha256:5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e \
+    --hash=sha256:ff452ff5a3e828ce110190feff1178bb1f2ea2281fa2075aadb987c2fb221661
+    # via pytest
+pluggy==1.6.0 \
+    --hash=sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3 \
+    --hash=sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746
+    # via pytest
+pygments==2.20.0 \
+    --hash=sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f \
+    --hash=sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176
+    # via pytest
+pytest==9.0.3 \
+    --hash=sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9 \
+    --hash=sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c
+    # via -r .github/requirements/ci-dev-py3.in
+sortedcontainers==2.4.0 \
+    --hash=sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88 \
+    --hash=sha256:a163dcaede0f1c021485e957a39245190e74249897e2ae4b2aa38595db237ee0
+    # via hypothesis
@@ -0,0 +1,8 @@
+# Python 3.9 dev/test tooling for the ci.yml binding test job.
+# numpy is capped <2.1 because that is the last series shipping cp39 wheels
+# (>=2.1 dropped Python 3.9). Locked output: ci-dev-py39.txt
+# Refresh via scripts/update-lockfiles.sh.
+maturin
+pytest
+numpy<2.1
+hypothesis
@@ -0,0 +1,162 @@
+# This file was autogenerated by uv via the following command:
+#    ./scripts/update-lockfiles.sh
+attrs==26.1.0 \
+    --hash=sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309 \
+    --hash=sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32
+    # via hypothesis
+colorama==0.4.6 \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via pytest
+exceptiongroup==1.3.1 \
+    --hash=sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219 \
+    --hash=sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598
+    # via
+    #   hypothesis
+    #   pytest
+hypothesis==6.141.1 \
+    --hash=sha256:8ef356e1e18fbeaa8015aab3c805303b7fe4b868e5b506e87ad83c0bf951f46f \
+    --hash=sha256:a5b3c39c16d98b7b4c3c5c8d4262e511e3b2255e6814ced8023af49087ad60b3
+    # via -r .github/requirements/ci-dev-py39.in
+iniconfig==2.1.0 \
+    --hash=sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7 \
+    --hash=sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760
+    # via pytest
+maturin==1.13.3 \
+    --hash=sha256:0ef257e692cc756c87af5bea95ddfe7d3ac49d3376a7a87f728d63f06e7b6f8b \
+    --hash=sha256:1cc0a110b224ca90406b668a3e3c1f5a515062e59e26292f6dbaf5fd4909c6f3 \
+    --hash=sha256:2389fe92d017cea9d94e521fa0175314a4c52f79a1057b901fbc9f8686ef7d0b \
+    --hash=sha256:3cc13929ca82aefa4adbf0f2c35419369796213c6fb0eb24e914945f50ef5d8c \
+    --hash=sha256:3db93337ed97e60ffc878aa8b493cd7ae44d3a5e1a37256db3a4491f57565018 \
+    --hash=sha256:4667ef609ab446c1b5e0bfe4f9fb99699ab6d8548433f8d1a684256e0b67217f \
+    --hash=sha256:49fd6ab08da28098ccf37afca24cdba72376ba9c1eedf9dd25ff82ed771961ff \
+    --hash=sha256:4cd478e6e4c56251e48ed079b8efd55b30bc5c09cf695a1bdafaeb582ee735a0 \
+    --hash=sha256:53b08bd075649ce96513ad9abf241a43cb685ed6e9e7790f8dbc2d66e95d8323 \
+    --hash=sha256:771e1e9e71a278e56db01552e0d1acfd1464259f9575b6e72842f893cd299079 \
+    --hash=sha256:a2675e25f313034ae6f57388cf14818f87d8961c4a96795287f3e155f59beb11 \
+    --hash=sha256:b6741d7bf4af97da937528fd1e523c6ab54f53d9a21870fa735d6e67fd88e273 \
+    --hash=sha256:c00ea6428dea17bf616fe93770837634454b28c2de1a876e42ef8036c616079a \
+    --hash=sha256:def4a435ea9d2ee93b18ba579dc8c9cf898889a66f312cd379b5e374ec3e3ad6
+    # via -r .github/requirements/ci-dev-py39.in
+numpy==2.0.2 \
+    --hash=sha256:0123ffdaa88fa4ab64835dcbde75dcdf89c453c922f18dced6e27c90d1d0ec5a \
+    --hash=sha256:11a76c372d1d37437857280aa142086476136a8c0f373b2e648ab2c8f18fb195 \
+    --hash=sha256:13e689d772146140a252c3a28501da66dfecd77490b498b168b501835041f951 \
+    --hash=sha256:1e795a8be3ddbac43274f18588329c72939870a16cae810c2b73461c40718ab1 \
+    --hash=sha256:26df23238872200f63518dd2aa984cfca675d82469535dc7162dc2ee52d9dd5c \
+    --hash=sha256:286cd40ce2b7d652a6f22efdfc6d1edf879440e53e76a75955bc0c826c7e64dc \
+    --hash=sha256:2b2955fa6f11907cf7a70dab0d0755159bca87755e831e47932367fc8f2f2d0b \
+    --hash=sha256:2da5960c3cf0df7eafefd806d4e612c5e19358de82cb3c343631188991566ccd \
+    --hash=sha256:312950fdd060354350ed123c0e25a71327d3711584beaef30cdaa93320c392d4 \
+    --hash=sha256:423e89b23490805d2a5a96fe40ec507407b8ee786d66f7328be214f9679df6dd \
+    --hash=sha256:496f71341824ed9f3d2fd36cf3ac57ae2e0165c143b55c3a035ee219413f3318 \
+    --hash=sha256:49ca4decb342d66018b01932139c0961a8f9ddc7589611158cb3c27cbcf76448 \
+    --hash=sha256:51129a29dbe56f9ca83438b706e2e69a39892b5eda6cedcb6b0c9fdc9b0d3ece \
+    --hash=sha256:5fec9451a7789926bcf7c2b8d187292c9f93ea30284802a0ab3f5be8ab36865d \
+    --hash=sha256:671bec6496f83202ed2d3c8fdc486a8fc86942f2e69ff0e986140339a63bcbe5 \
+    --hash=sha256:7f0a0c6f12e07fa94133c8a67404322845220c06a9e80e85999afe727f7438b8 \
+    --hash=sha256:807ec44583fd708a21d4a11d94aedf2f4f3c3719035c76a2bbe1fe8e217bdc57 \
+    --hash=sha256:883c987dee1880e2a864ab0dc9892292582510604156762362d9326444636e78 \
+    --hash=sha256:8c5713284ce4e282544c68d1c3b2c7161d38c256d2eefc93c1d683cf47683e66 \
+    --hash=sha256:8cafab480740e22f8d833acefed5cc87ce276f4ece12fdaa2e8903db2f82897a \
+    --hash=sha256:8df823f570d9adf0978347d1f926b2a867d5608f434a7cff7f7908c6570dcf5e \
+    --hash=sha256:9059e10581ce4093f735ed23f3b9d283b9d517ff46009ddd485f1747eb22653c \
+    --hash=sha256:905d16e0c60200656500c95b6b8dca5d109e23cb24abc701d41c02d74c6b3afa \
+    --hash=sha256:9189427407d88ff25ecf8f12469d4d39d35bee1db5d39fc5c168c6f088a6956d \
+    --hash=sha256:96a55f64139912d61de9137f11bf39a55ec8faec288c75a54f93dfd39f7eb40c \
+    --hash=sha256:97032a27bd9d8988b9a97a8c4d2c9f2c15a81f61e2f21404d7e8ef00cb5be729 \
+    --hash=sha256:984d96121c9f9616cd33fbd0618b7f08e0cfc9600a7ee1d6fd9b239186d19d97 \
+    --hash=sha256:9a92ae5c14811e390f3767053ff54eaee3bf84576d99a2456391401323f4ec2c \
+    --hash=sha256:9ea91dfb7c3d1c56a0e55657c0afb38cf1eeae4544c208dc465c3c9f3a7c09f9 \
+    --hash=sha256:a15f476a45e6e5a3a79d8a14e62161d27ad897381fecfa4a09ed5322f2085669 \
+    --hash=sha256:a392a68bd329eafac5817e5aefeb39038c48b671afd242710b451e76090e81f4 \
+    --hash=sha256:a3f4ab0caa7f053f6797fcd4e1e25caee367db3112ef2b6ef82d749530768c73 \
+    --hash=sha256:a46288ec55ebbd58947d31d72be2c63cbf839f0a63b49cb755022310792a3385 \
+    --hash=sha256:a61ec659f68ae254e4d237816e33171497e978140353c0c2038d46e63282d0c8 \
+    --hash=sha256:a842d573724391493a97a62ebbb8e731f8a5dcc5d285dfc99141ca15a3302d0c \
+    --hash=sha256:becfae3ddd30736fe1889a37f1f580e245ba79a5855bff5f2a29cb3ccc22dd7b \
+    --hash=sha256:c05e238064fc0610c840d1cf6a13bf63d7e391717d247f1bf0318172e759e692 \
+    --hash=sha256:c1c9307701fec8f3f7a1e6711f9089c06e6284b3afbbcd259f7791282d660a15 \
+    --hash=sha256:c7b0be4ef08607dd04da4092faee0b86607f111d5ae68036f16cc787e250a131 \
+    --hash=sha256:cfd41e13fdc257aa5778496b8caa5e856dc4896d4ccf01841daee1d96465467a \
+    --hash=sha256:d731a1c6116ba289c1e9ee714b08a8ff882944d4ad631fd411106a30f083c326 \
+    --hash=sha256:df55d490dea7934f330006d0f81e8551ba6010a5bf035a249ef61a94f21c500b \
+    --hash=sha256:ec9852fb39354b5a45a80bdab5ac02dd02b15f44b3804e9f00c556bf24b4bded \
+    --hash=sha256:f15975dfec0cf2239224d80e32c3170b1d168335eaedee69da84fbe9f1f9cd04 \
+    --hash=sha256:f26b258c385842546006213344c50655ff1555a9338e2e5e02a0756dc3e803dd
+    # via -r .github/requirements/ci-dev-py39.in
+packaging==26.2 \
+    --hash=sha256:5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e \
+    --hash=sha256:ff452ff5a3e828ce110190feff1178bb1f2ea2281fa2075aadb987c2fb221661
+    # via pytest
+pluggy==1.6.0 \
+    --hash=sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3 \
+    --hash=sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746
+    # via pytest
+pygments==2.20.0 \
+    --hash=sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f \
+    --hash=sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176
+    # via pytest
+pytest==8.4.2 \
+    --hash=sha256:86c0d0b93306b961d58d62a4db4879f27fe25513d4b969df351abdddb3c30e01 \
+    --hash=sha256:872f880de3fc3a5bdc88a11b39c9710c3497a547cfa9320bc3c5e62fbf272e79
+    # via -r .github/requirements/ci-dev-py39.in
+sortedcontainers==2.4.0 \
+    --hash=sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88 \
+    --hash=sha256:a163dcaede0f1c021485e957a39245190e74249897e2ae4b2aa38595db237ee0
+    # via hypothesis
+tomli==2.4.1 \
+    --hash=sha256:01f520d4f53ef97964a240a035ec2a869fe1a37dde002b57ebc4417a27ccd853 \
+    --hash=sha256:0d85819802132122da43cb86656f8d1f8c6587d54ae7dcaf30e90533028b49fe \
+    --hash=sha256:136443dbd7e1dee43c68ac2694fde36b2849865fa258d39bf822c10e8068eac5 \
+    --hash=sha256:1d8591993e228b0c930c4bb0db464bdad97b3289fb981255d6c9a41aedc84b2d \
+    --hash=sha256:2190f2e9dd7508d2a90ded5ed369255980a1bcdd58e52f7fe24b8162bf9fedbd \
+    --hash=sha256:2c1c351919aca02858f740c6d33adea0c5deea37f9ecca1cc1ef9e884a619d26 \
+    --hash=sha256:36d2bd2ad5fb9eaddba5226aa02c8ec3fa4f192631e347b3ed28186d43be6b54 \
+    --hash=sha256:3d48a93ee1c9b79c04bb38772ee1b64dcf18ff43085896ea460ca8dec96f35f6 \
+    --hash=sha256:47149d5bd38761ac8be13a84864bf0b7b70bc051806bc3669ab1cbc56216b23c \
+    --hash=sha256:4ab97e64ccda8756376892c53a72bd1f964e519c77236368527f758fbc36a53a \
+    --hash=sha256:4b605484e43cdc43f0954ddae319fb75f04cc10dd80d830540060ee7cd0243cd \
+    --hash=sha256:504aa796fe0569bb43171066009ead363de03675276d2d121ac1a4572397870f \
+    --hash=sha256:51529d40e3ca50046d7606fa99ce3956a617f9b36380da3b7f0dd3dd28e68cb5 \
+    --hash=sha256:52c8ef851d9a240f11a88c003eacb03c31fc1c9c4ec64a99a0f922b93874fda9 \
+    --hash=sha256:559db847dc486944896521f68d8190be1c9e719fced785720d2216fe7022b662 \
+    --hash=sha256:5a881ab208c0baf688221f8cecc5401bd291d67e38a1ac884d6736cbcd8247e9 \
+    --hash=sha256:5cb41aa38891e073ee49d55fbc7839cfdb2bc0e600add13874d048c94aadddd1 \
+    --hash=sha256:5e262d41726bc187e69af7825504c933b6794dc3fbd5945e41a79bb14c31f585 \
+    --hash=sha256:5ee18d9ebdb417e384b58fe414e8d6af9f4e7a0ae761519fb50f721de398dd4e \
+    --hash=sha256:7008df2e7655c495dd12d2a4ad038ff878d4ca4b81fccaf82b714e07eae4402c \
+    --hash=sha256:734e20b57ba95624ecf1841e72b53f6e186355e216e5412de414e3c51e5e3c41 \
+    --hash=sha256:7c7e1a961a0b2f2472c1ac5b69affa0ae1132c39adcb67aba98568702b9cc23f \
+    --hash=sha256:7f86fd587c4ed9dd76f318225e7d9b29cfc5a9d43de44e5754db8d1128487085 \
+    --hash=sha256:7f94b27a62cfad8496c8d2513e1a222dd446f095fca8987fceef261225538a15 \
+    --hash=sha256:88dceee75c2c63af144e456745e10101eb67361050196b0b6af5d717254dddf7 \
+    --hash=sha256:8a650c2dbafa08d42e51ba0b62740dae4ecb9338eefa093aa5c78ceb546fcd5c \
+    --hash=sha256:8d65a2fbf9d2f8352685bc1364177ee3923d6baf5e7f43ea4959d7d8bc326a36 \
+    --hash=sha256:96481a5786729fd470164b47cdb3e0e58062a496f455ee41b4403be77cb5a076 \
+    --hash=sha256:a120733b01c45e9a0c34aeef92bf0cf1d56cfe81ed9d47d562f9ed591a9828ac \
+    --hash=sha256:b1d22e6e9387bf4739fbe23bfa80e93f6b0373a7f1b96c6227c32bef95a4d7a8 \
+    --hash=sha256:b8c198f8c1805dc42708689ed6864951fd2494f924149d3e4bce7710f8eb5232 \
+    --hash=sha256:c2541745709bad0264b7d4705ad453b76ccd191e64aa6f0fc66b69a293a45ece \
+    --hash=sha256:c742f741d58a28940ce01d58f0ab2ea3ced8b12402f162f4d534dfe18ba1cd6a \
+    --hash=sha256:c7f2c7f2b9ca6bdeef8f0fa897f8e05085923eb091721675170254cbc5b02897 \
+    --hash=sha256:d312ef37c91508b0ab2cee7da26ec0b3ed2f03ce12bd87a588d771ae15dcf82d \
+    --hash=sha256:d4d8fe59808a54658fcc0160ecfb1b30f9089906c50b23bcb4c69eddc19ec2b4 \
+    --hash=sha256:da25dc3563bff5965356133435b757a795a17b17d01dbc0f42fb32447ddfd917 \
+    --hash=sha256:eab21f45c7f66c13f2a9e0e1535309cee140182a9cdae1e041d02e47291e8396 \
+    --hash=sha256:eb0dc4e38e6a1fd579e5d50369aa2e10acfc9cace504579b2faabb478e76941a \
+    --hash=sha256:ec9bfaf3ad2df51ace80688143a6a4ebc09a248f6ff781a9945e51937008fcbc \
+    --hash=sha256:ede3e6487c5ef5d28634ba3f31f989030ad6af71edfb0055cbbd14189ff240ba \
+    --hash=sha256:f3c6818a1a86dd6dca7ddcaaf76947d5ba31aecc28cb1b67009a5877c9a64f3f \
+    --hash=sha256:f758f1b9299d059cc3f6546ae2af89670cb1c4d48ea29c3cacc4fe7de3058257 \
+    --hash=sha256:f8f0fc26ec2cc2b965b7a3b87cd19c5c6b8c5e5f436b984e85f486d652285c30 \
+    --hash=sha256:fd0409a3653af6c147209d267a0e4243f0ae46b011aa978b1080359fddc9b6cf \
+    --hash=sha256:ff18e6a727ee0ab0388507b89d1bc6a22b138d1e2fa56d1ad494586d61d2eae9 \
+    --hash=sha256:ff2983983d34813c1aeb0fa89091e76c3a22889ee83ab27c5eeb45100560c049
+    # via
+    #   maturin
+    #   pytest
+typing-extensions==4.15.0 \
+    --hash=sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466 \
+    --hash=sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548
+    # via exceptiongroup
@@ -49,6 +49,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27

@@ -62,6 +64,8 @@ jobs:
        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
        with:
          python-version: "3.11"
+          cache: pip
+          cache-dependency-path: .github/requirements/bench.txt

      - name: Wait before Python retry
        if: steps.setup_python.outcome == 'failure'
@@ -75,11 +79,15 @@ jobs:
        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
        with:
          python-version: "3.11"
+          cache: pip
+          cache-dependency-path: .github/requirements/bench.txt

      - name: Install Python deps + peer libs
        run: |
          python -m pip install --upgrade pip
-          python -m pip install maturin numpy pandas talipp finta
+          # Hash-locked deps (OpenSSF Scorecard PinnedDependencies). bench.yml
+          # runs on a single Python version (3.11), so one lock file suffices.
+          python -m pip install --require-hashes -r .github/requirements/bench.txt

      - name: Build Wickra wheel
        working-directory: bindings/python
@@ -109,3 +117,29 @@ jobs:
        with:
          name: cross-library-bench
          path: bindings/python/benchmark.txt
+
+  rust-cross-bench:
+    name: Rust cross-library benchmark report
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      # Wickra vs the other Rust TA crates (kand, ta-rs, yata) on an identical
+      # candle series — the like-for-like engine comparison with no binding
+      # overhead. Streaming + batch, in crates/wickra-bench/benches/cross_lib.rs.
+      - name: Run Rust cross-library benchmark
+        run: cargo bench -p wickra-bench --bench cross_lib | tee rust_cross_bench.txt
+
+      - name: Upload Rust report
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: rust-cross-bench
+          path: rust_cross_bench.txt
@@ -40,6 +40,8 @@ jobs:
        os: [ubuntu-latest, macos-latest, windows-latest]
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -88,6 +90,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Set up Node
        id: setup_node
@@ -175,6 +179,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -253,6 +259,8 @@ jobs:
            packages: "-p wickra-node"
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust ${{ matrix.toolchain }}
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -276,6 +284,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -315,6 +325,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: cargo-deny
        uses: EmbarkStudios/cargo-deny-action@bb137d7af7e4fb67e5f82a49c4fce4fad40782fe # v2.0.20
@@ -331,6 +343,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install nightly Rust
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -387,6 +401,8 @@ jobs:
        python-version: ["3.9", "3.11", "3.12", "3.13"]
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -407,6 +423,8 @@ jobs:
        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
        with:
          python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: .github/requirements/ci-dev-*.txt

      - name: Wait before Python retry
        if: steps.setup_python.outcome == 'failure'
@@ -420,11 +438,21 @@ jobs:
        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
        with:
          python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: .github/requirements/ci-dev-*.txt

      - name: Install Python dev dependencies
+        shell: bash
        run: |
          python -m pip install --upgrade pip
-          python -m pip install maturin pytest numpy hypothesis
+          # Hash-locked dev tooling (OpenSSF Scorecard PinnedDependencies).
+          # Split by Python version: numpy ships no single release with wheels
+          # for both cp39 and cp313 (<=2.0.2 has cp39 only, >=2.1 drops cp39).
+          if [ "${{ matrix.python-version }}" = "3.9" ]; then
+            python -m pip install --require-hashes -r .github/requirements/ci-dev-py39.txt
+          else
+            python -m pip install --require-hashes -r .github/requirements/ci-dev-py3.txt
+          fi

      - name: Build wheel
        working-directory: bindings/python
@@ -449,6 +477,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain (with wasm target)
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -495,6 +525,8 @@ jobs:
        node-version: ["18", "20"]
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Install Rust toolchain
        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
@@ -514,6 +546,8 @@ jobs:
        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
        with:
          node-version: ${{ matrix.node-version }}
+          cache: npm
+          cache-dependency-path: bindings/node/package-lock.json

      - name: Wait before Node retry
        if: steps.setup_node.outcome == 'failure'
@@ -527,10 +561,12 @@ jobs:
        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
        with:
          node-version: ${{ matrix.node-version }}
+          cache: npm
+          cache-dependency-path: bindings/node/package-lock.json

      - name: Install Node dependencies
        working-directory: bindings/node
-        run: npm install
+        run: npm ci

      - name: Build native module
        working-directory: bindings/node
@@ -40,7 +40,9 @@ jobs:
            build-mode: none
    steps:
      - name: Checkout
-        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Initialize CodeQL
        uses: github/codeql-action/init@03e4368ac7daa2bd82b3e85262f3bf87ee112f57 # v3.36.0
@@ -46,6 +46,8 @@ jobs:
    environment: release
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
      - uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
@@ -156,6 +158,8 @@ jobs:
    runs-on: ${{ matrix.os }}
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
      - name: Set up Python
        id: setup_python
        continue-on-error: true
@@ -194,6 +198,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
      - name: Sync root README into bindings/python so it ships in the sdist
        run: cp README.md bindings/python/README.md
      - uses: PyO3/maturin-action@e83996d129638aa358a18fbd1dfb82f0b0fb5d3b # v1.51.0
@@ -244,6 +250,8 @@ jobs:
    runs-on: ${{ matrix.host }}
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Set up Node
        id: setup_node
@@ -275,7 +283,7 @@ jobs:

      - name: Install Node deps
        working-directory: bindings/node
-        run: npm install
+        run: npm ci

      - name: Build native module
        working-directory: bindings/node
@@ -303,6 +311,8 @@ jobs:
      id-token: write
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Set up Node
        id: setup_node
@@ -328,7 +338,7 @@ jobs:

      - name: Install Node deps
        working-directory: bindings/node
-        run: npm install
+        run: npm ci

      - name: Download all platform binaries
        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
@@ -470,6 +480,8 @@ jobs:
      id-token: write
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false

      - name: Set up Node
        id: setup_node
@@ -524,7 +536,7 @@ jobs:
            pkg.repository = { type: 'git', url: 'https://github.com/wickra-lib/wickra' };
            pkg.homepage = 'https://github.com/wickra-lib/wickra';
            pkg.bugs = { url: 'https://github.com/wickra-lib/wickra/issues' };
-            pkg.license = 'PolyForm-Noncommercial-1.0.0';
+            pkg.license = 'MIT OR Apache-2.0';
            fs.writeFileSync('package.json', JSON.stringify(pkg, null, 2));
          "

@@ -570,13 +582,22 @@ jobs:
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
        with:
+          persist-credentials: false
          fetch-depth: 0

      - name: Resolve target tag
        id: tag
+        # Pass the (potentially attacker-influenceable on a tag push) ref context
+        # through the environment instead of interpolating it into the shell
+        # script, so a crafted tag name cannot inject commands (zizmor:
+        # template-injection).
+        env:
+          EVENT_NAME: ${{ github.event_name }}
+          REF: ${{ github.ref }}
+          REF_NAME: ${{ github.ref_name }}
        run: |
-          if [ "${{ github.event_name }}" = "push" ] && [[ "${{ github.ref }}" == refs/tags/* ]]; then
-            tag="${{ github.ref_name }}"
+          if [ "$EVENT_NAME" = "push" ] && [[ "$REF" == refs/tags/* ]]; then
+            tag="$REF_NAME"
          else
            # workflow_dispatch / non-tag push: attach to the latest v* tag.
            tag=$(git tag --list 'v*' --sort=-v:refname | head -n1)
@@ -24,7 +24,7 @@ jobs:
      id-token: write # OIDC token to publish results to the OpenSSF API
    steps:
      - name: Checkout code
-        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
        with:
          persist-credentials: false

@@ -33,6 +33,13 @@ jobs:
        with:
          results_file: results.sarif
          results_format: sarif
+          # The default GITHUB_TOKEN cannot read classic branch-protection
+          # rules, so the Branch-Protection check fails with an internal error
+          # and scores -1. A read-only fine-grained PAT (Administration: read,
+          # Contents: read, Metadata: read) supplied as SCORECARD_TOKEN lets the
+          # check read the protection settings. See
+          # https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
+          repo_token: ${{ secrets.SCORECARD_TOKEN }}
          # Publish to the public OpenSSF endpoint that backs the README badge.
          publish_results: true

@@ -10,7 +10,7 @@ name: Sync indicator count
 #   3. Docs site: index.md / overview.md / Indicators-Overview.md
 #      (wickra-lib/wickra-docs) — synced on push to main / v* tag*
 #   4. Marketing site count (wickra-lib/webpage: index.md /
-#      .vitepress/config.ts / public/hero.svg) — push to main / v* tag*
+#      .vitepress/config.ts) — push to main / v* tag*
 #   5. org profile README count (wickra-lib/.github, profile/README.md)
 #                                            — synced on push to main / v* tag*
 #   6. org description ("… N indicators, install-free.")
@@ -41,17 +41,17 @@ name: Sync indicator count
 # `RollingVwap`, so the mod-count under-reports by one. lib.rs is the
 # single source of truth for what the bindings reach.
 #
-# Design: keep README in sync *before* a PR is merged, by pushing a
-# fix-up commit to the PR head branch. After squash-merge into main
-# the bot commit is folded into the single signed merge commit, so
-# main's history never shows an unsigned "sync indicator count" entry.
+# Design: on PRs this workflow is a READ-ONLY check. The indicator wiring
+# (ScriptHelpers/_common.py wire_readme_counter) bumps both README.md and
+# docs/README.md inside the author's code commit, so the counter is already
+# correct by the time CI runs. If it is not, the check below fails loud and
+# asks the author to re-run the wiring — it never pushes a fix-up commit.
 #
-# The push to PR head uses the default `GITHUB_TOKEN`, whose pushes
-# explicitly do NOT trigger downstream workflows (anti-recursion
-# policy). So a counter fix-up does not re-trigger ci.yml on the PR
-# — it does, however, re-trigger sync-about.yml on the next PR
-# `synchronize` event, which is what we want (a no-op if the counter
-# is now correct).
+# (An earlier version pushed a GITHUB_TOKEN "sync indicator count" commit to
+# the PR head. Because GITHUB_TOKEN pushes trigger no workflows, that commit
+# moved the PR head onto a commit with no CI run, which hid the Codecov patch
+# status — keyed to the PR head sha — from the PR. Keeping the counter in the
+# code commit avoids that entirely.)
 on:
  push:
    branches: [main]
@@ -73,53 +73,24 @@ permissions:
 jobs:
  sync:
    runs-on: ubuntu-latest
-    # The only GITHUB_TOKEN write in this workflow: pushing the counter fix-up
-    # commit onto a same-repo PR head branch (git push origin HEAD:<ref>).
+    # This workflow never writes to wickra-lib/wickra with GITHUB_TOKEN: the PR
+    # flow is a read-only check, and the main/tag flow writes only to other
+    # repos (About metadata, docs, webpage, wiki, org) through the fine-grained
+    # ABOUT_SYNC_TOKEN PAT. So GITHUB_TOKEN stays read-only (OpenSSF Scorecard:
+    # Token-Permissions).
    permissions:
-      contents: write
+      contents: read
      pull-requests: read
    steps:
-      # On PRs from forks the head ref lives in another repo; pushing
-      # back to it from this workflow is blocked by GitHub. We still
-      # want the PR to surface the missing counter, so the check below
-      # falls back to a hard failure when push isn't possible.
-      - name: Determine if push to PR head is possible
-        id: ctx
-        # Untrusted PR contexts (head.ref / head.repo.full_name are attacker
-        # controlled on fork PRs) are passed through the environment, never
-        # interpolated straight into the shell, so a crafted branch name cannot
-        # inject commands (OpenSSF Scorecard: Dangerous-Workflow).
-        env:
-          EVENT_NAME: ${{ github.event_name }}
-          HEAD_REPO: ${{ github.event.pull_request.head.repo.full_name }}
-          BASE_REPO: ${{ github.repository }}
-          HEAD_REF: ${{ github.event.pull_request.head.ref }}
-        run: |
-          if [ "$EVENT_NAME" = "pull_request" ]; then
-            if [ "$HEAD_REPO" = "$BASE_REPO" ]; then
-              echo "can_push=true" >> "$GITHUB_OUTPUT"
-              echo "head_ref=$HEAD_REF" >> "$GITHUB_OUTPUT"
-            else
-              echo "can_push=false" >> "$GITHUB_OUTPUT"
-              echo "head_ref=" >> "$GITHUB_OUTPUT"
-            fi
-          else
-            echo "can_push=false" >> "$GITHUB_OUTPUT"
-            echo "head_ref=" >> "$GITHUB_OUTPUT"
-          fi
-
-      # On PRs we check out the *head* commit (not the merge ref) so
-      # any fix-up commit we make goes onto the PR branch itself. On
-      # push events we check out the default ref. fetch-depth: 0 lets
-      # us push back without "shallow update not allowed".
+      # On PRs we check out the PR *head* commit (the author's code, not the
+      # merge ref) so the counter check validates exactly what will land. On
+      # push events we check out the default ref. No push is made, so a shallow
+      # checkout is enough.
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
        with:
-          fetch-depth: 0
+          fetch-depth: 1
          ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.ref || github.ref }}
          repository: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name || github.repository }}
-          # Default GITHUB_TOKEN is fine for the same-repo PR-branch
-          # push; the About / Wiki steps re-authenticate with the PAT
-          # below where needed.

      - name: Count indicators
        id: count
@@ -139,62 +110,33 @@ jobs:

      # ----- PR flow ---------------------------------------------------

-      - name: Check README counter (PR)
+      - name: Check README counter (PR, read-only)
        if: github.event_name == 'pull_request'
-        id: pr_check
        run: |
          n="${{ steps.count.outputs.count }}"
-          if grep -qE "^${n} streaming-first indicators" README.md; then
-            echo "matches=true" >> "$GITHUB_OUTPUT"
-            echo "README counter already at ${n}; nothing to do."
-          else
-            echo "matches=false" >> "$GITHUB_OUTPUT"
-            echo "README counter does not match ${n}; will fix up."
+          ok=true
+          if ! grep -qE "^${n} streaming-first indicators" README.md; then
+            echo "::error::README.md does not say '${n} streaming-first indicators' — lib.rs exports ${n}. Re-run the indicator wiring (it bumps README.md), then push again."
+            ok=false
          fi
-
-      - name: Fix counter on fork PR head (read-only, fail loud)
-        if: github.event_name == 'pull_request' && steps.pr_check.outputs.matches == 'false' && steps.ctx.outputs.can_push == 'false'
-        run: |
-          n="${{ steps.count.outputs.count }}"
-          echo "::error::README.md says a different indicator count than mod.rs (${n}). This PR is from a fork, so the workflow cannot push the fix; please update README.md to '${n} streaming-first indicators' and push again."
-          exit 1
-
-      - name: Patch README on PR head
-        if: github.event_name == 'pull_request' && steps.pr_check.outputs.matches == 'false' && steps.ctx.outputs.can_push == 'true'
-        id: pr_patch
-        run: |
-          n="${{ steps.count.outputs.count }}"
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" README.md
-          if git diff --quiet; then
-            echo "No README changes after sed (counter regex did not match anything); skipping push."
-            echo "changed=false" >> "$GITHUB_OUTPUT"
-          else
-            echo "changed=true" >> "$GITHUB_OUTPUT"
+          if ! grep -qE "\*\*${n} indicators\*\*" docs/README.md; then
+            echo "::error::docs/README.md does not say '**${n} indicators**' — lib.rs exports ${n}. Re-run the indicator wiring (it bumps docs/README.md), then push again."
+            ok=false
+          fi
+          if [ "$ok" = "true" ]; then
+            echo "README.md + docs/README.md counter already at ${n}; nothing to do."
+          else
+            exit 1
          fi
-
-      - name: Commit & push counter fix to PR head
-        if: github.event_name == 'pull_request' && steps.pr_patch.outputs.changed == 'true'
-        # head_ref still carries the (untrusted) PR branch name forwarded by the
-        # ctx step; pass it through the environment so the push refspec cannot be
-        # used to inject shell commands (OpenSSF Scorecard: Dangerous-Workflow).
-        env:
-          COUNT: ${{ steps.count.outputs.count }}
-          HEAD_REF: ${{ steps.ctx.outputs.head_ref }}
-        run: |
-          git config user.name "wickra-bot"
-          git config user.email "wickra-bot@users.noreply.github.com"
-          git add README.md
-          git commit -m "chore: sync indicator count to ${COUNT}"
-          git push origin "HEAD:${HEAD_REF}"

      # ----- main / tag flow ------------------------------------------
      #
-      # After a PR squash-merges, this workflow runs again on the push
-      # to main. README is already correct (it was fixed on the PR
-      # branch before the merge); the only outward syncs left are the
-      # GitHub About description (repo metadata, not a commit) and the
-      # wiki repo (separate repo, no main history pollution). README is
-      # not touched on main any more.
+      # After a PR squash-merges, this workflow runs again on the push to main.
+      # README.md / docs/README.md are already correct (the indicator wiring
+      # bumped them in the merged code commit); the only outward syncs left are
+      # the GitHub About description (repo metadata, not a commit) and the docs /
+      # webpage / wiki / org repos (separate repos, no main history pollution).
+      # The wickra repo's own README is not touched on main any more.

      - name: Update GitHub About (description + homepage)
        if: github.event_name != 'pull_request'
@@ -238,14 +180,14 @@ jobs:
            exit 0
          fi
          cd docs-count
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md .vitepress/config.ts
          if git diff --quiet; then
            echo "Docs indicator count unchanged."
            exit 0
          fi
          git config user.name "wickra-bot"
          git config user.email "wickra-bot@users.noreply.github.com"
-          git add index.md overview.md Indicators-Overview.md
+          git add index.md overview.md Indicators-Overview.md .vitepress/config.ts
          git commit -m "chore: sync indicator count to ${n}"
          if ! git push 2>/dev/null; then
            echo "::warning::push to wickra-lib/wickra-docs failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."
@@ -424,14 +366,14 @@ jobs:
            exit 0
          fi
          cd webpage-count
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md .vitepress/config.ts public/hero.svg
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md .vitepress/config.ts
          if git diff --quiet; then
            echo "Webpage indicator count unchanged."
            exit 0
          fi
          git config user.name "wickra-bot"
          git config user.email "wickra-bot@users.noreply.github.com"
-          git add index.md .vitepress/config.ts public/hero.svg
+          git add index.md .vitepress/config.ts
          git commit -m "chore: sync indicator count to ${n}"
          if ! git push 2>/dev/null; then
            echo "::warning::push to wickra-lib/webpage failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."
@@ -15,6 +15,8 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
      - uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
        with:
          python-version: "3.12"
@@ -0,0 +1,40 @@
+name: zizmor
+
+# Static analysis of the GitHub Actions workflows themselves — the surface the
+# CodeQL pass does not cover. zizmor flags template injection, overly broad
+# GITHUB_TOKEN permissions, unpinned actions, cache poisoning, and dangerous
+# triggers. Findings appear under Security -> Code scanning alongside CodeQL.
+#
+# Report-only: with `advanced-security: true` the action runs zizmor in SARIF
+# mode, which exits 0 regardless of findings, so this job never blocks CI —
+# triage happens in the Security tab. Switch to gating later (e.g. a
+# `min-severity` input) once the existing findings are triaged.
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+  schedule:
+    - cron: '17 4 * * 1' # Mondays 04:17 UTC
+
+# Least-privilege default for the auto-injected GITHUB_TOKEN; the job raises
+# exactly the scopes it needs below (matches codeql.yml's pattern).
+permissions:
+  contents: read
+
+jobs:
+  zizmor:
+    name: Audit workflows
+    runs-on: ubuntu-latest
+    permissions:
+      security-events: write # upload SARIF to code-scanning
+      contents: read # checkout
+      actions: read # online audits resolve referenced actions
+    steps:
+      - name: Checkout
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Run zizmor
+        uses: zizmorcore/zizmor-action@5f14fd08f7cf1cb1609c1e344975f152c7ee938d # v0.5.6
@@ -0,0 +1,49 @@
+# zizmor configuration — https://docs.zizmor.sh/configuration/
+#
+# cache-poisoning (release.yml):
+#   The release pipeline restores build caches (Swatinem/rust-cache for the Rust
+#   compilation, actions/setup-node) as a deliberate, accepted optimisation.
+#   zizmor flags these under cache-poisoning because release.yml publishes
+#   artifacts to crates.io / PyPI / npm, so a poisoned cache could in theory
+#   reach a released build. Our caches are maintainer-controlled and the
+#   restore speedup is kept on purpose; we accept this risk rather than running
+#   cache-free release builds. (Six of the eight hits are actions/setup-node,
+#   which zizmor reports at "Low" confidence.)
+#
+# artipacked (sync-about.yml):
+#   The sync-about job checks out with persisted credentials on purpose: it
+#   pushes the indicator-count fix-up back to the PR head branch (git commit +
+#   git push), which needs the token in the runner's git config. It uploads no
+#   artifacts, so the persisted token is never packaged or leaked; accept it.
+#
+# template-injection (sync-about.yml):
+#   False positive. Every flagged expansion is steps.count.outputs.count, the
+#   indicator count produced by an internal `grep -c` over lib.rs. It is not
+#   attacker-controllable, so there is nothing to inject.
+#
+# use-trusted-publishing (release.yml):
+#   Informational suggestion to use OIDC trusted publishing for PyPI / npm
+#   instead of long-lived tokens. A worthwhile migration, but it reconfigures
+#   the live publish pipeline on the registry side; tracked separately rather
+#   than blocking on it here.
+#
+# superfluous-actions (release.yml):
+#   The GitHub release step uses softprops/action-gh-release. The runner ships
+#   `gh`, so this is replaceable by a script step, but the action is stable and
+#   battle-tested; we keep it deliberately.
+rules:
+  cache-poisoning:
+    ignore:
+      - release.yml
+  artipacked:
+    ignore:
+      - sync-about.yml
+  template-injection:
+    ignore:
+      - sync-about.yml
+  use-trusted-publishing:
+    ignore:
+      - release.yml
+  superfluous-actions:
+    ignore:
+      - release.yml
@@ -7,6 +7,414 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+## [0.6.1] - 2026-06-07
+- **Projection Oscillator** — Widner projection oscillator: close position inside the projection bands, scaled 0..100 (`ProjectionOscillator`).
+- **Projection Bands** — Widner projection bands: forward-projected high/low regression envelope (`ProjectionBands`).
+- **Median Channel** — robust median +/- multiplier*MAD envelope (`MedianChannel`).
+- **Bomar Bands** — adaptive percentage bands containing a target coverage fraction of recent closes (`BomarBands`).
+- **Quartile Bands** — rolling 25th/50th/75th-percentile (Q1/median/Q3) envelope (`QuartileBands`).
+
+## [0.6.0] - 2026-06-06
+- **Volatility Cone** — volatility cone: current realized volatility within its historical min/median/max envelope (`VolatilityCone`).
+- **VolatilityRatio** — Schwager's volatility ratio: true range over the EMA of prior true ranges (`VolatilityRatio`).
+- **BipowerVariation** — jump-robust realized bipower variation (pi/2 sum of adjacent absolute log-return products) (`BipowerVariation`).
+- **VolatilityOfVolatility** — vol-of-vol: sample stddev of a rolling realized-volatility series (`VolatilityOfVolatility`).
+- **Garch11** — GARCH(1,1) conditional volatility with a long-run-variance anchor (`Garch11`).
+- **EwmaVolatility** — RiskMetrics exponentially-weighted volatility of log returns (lambda decay) (`EwmaVolatility`).
+
+## [0.5.9] - 2026-06-06
+
+### Added
+
+- Internal Rust cross-library benchmark harness (`crates/wickra-bench`, not
+  published) comparing Wickra against `kand`, `ta-rs` and `yata` on an identical
+  candle series in both streaming and batch modes; wired into the nightly
+  `cross-library-bench` workflow.
+- `tulipy` runners and expanded per-tick streaming coverage (SMA, EMA, RSI,
+  MACD, Bollinger) in the Python `compare_libraries` benchmark.
+
+### Changed
+
+- Faster streaming and batch updates for SMA, Bollinger Bands, RSI, EMA and ATR
+  (flat ring buffers replacing `VecDeque`, hoisted reciprocals in the Wilder
+  smoothing, leaner hot state) — indicator outputs are unchanged.
+- Rewrote the README benchmark section into honest, tiered tables (Rust core vs
+  the other Rust crates, and Python vs the Python ecosystem) that show where
+  Wickra wins and where it loses, not only the favourable comparisons.
+
+## [0.5.8] - 2026-06-04
+- **TSF Oscillator** — the percentage gap of the close to the one-bar-ahead time-series forecast, a close-relative companion to CFO (`TsfOscillator`).
+- **MACD Histogram** — the standalone macd-minus-signal bar of MACD as a scalar series (`MacdHistogram`).
+- **PPO Histogram** — the Percentage Price Oscillator with its signal EMA and the resulting zero-centered histogram (`PpoHistogram`).
+
+## [0.5.7] - 2026-06-04
+- **Qstick** — Qstick (Chande), the SMA of the candle body (close − open) as a net buying/selling pressure gauge (`QSTICK`).
+- **TTM Trend** — TTM Trend (John Carter), +1/−1 by whether the close sits above the SMA of recent median prices (`TTM_TREND`).
+- **Trend Strength Index** — trend strength index, the signed r² of a linear regression of price against time (`TREND_STRENGTH_INDEX`).
+- **Polarized Fractal Efficiency** — polarized fractal efficiency (Hannula), directional trend efficiency over a fractal lookback (`POLARIZED_FRACTAL_EFFICIENCY`).
+- **Wave PM** — Wave PM (Kase), a variance-normalised peak-momentum statistic (`WAVE_PM`).
+- **Gator Oscillator** — Gator Oscillator (Bill Williams), the Alligator convergence/divergence histogram (`GATOR_OSCILLATOR`).
+- **Kase Permission Stochastic** — Kase Permission Stochastic, a double-smoothed stochastic used as a trade-permission filter (`KASE_PERMISSION_STOCHASTIC`).
+
+## [0.5.6] - 2026-06-04
+- **QQE** — quantitative qualitative estimation, a smoothed RSI with an ATR-of-RSI trailing line (`QQE`).
+- **Intraday Momentum Index** — intraday momentum index (Chande), RSI on the open-to-close body (`IMI`).
+- **Elder Ray** — Elder Ray bull power and bear power around an EMA of close (`ElderRay`).
+- **Derivative Oscillator** — derivative oscillator (Constance Brown), a double-smoothed RSI histogram (`DerivativeOscillator`).
+- **RMI** — relative momentum index (RMI), RSI over a multi-bar momentum lookback (`RMI`).
+- **Stochastic CCI** — stochastic CCI, a stochastic oscillator over the CCI (`StochasticCCI`).
+- **Dynamic Momentum Index** — dynamic momentum index (Chande), a volatility-adaptive RSI (`DynamicMomentumIndex`).
+- **RSX** — RSX, a Jurik-style three-stage smoothed RSI (`RSX`).
+- **Fisher RSI** — Fisher RSI, the Fisher transform of a normalised RSI (`FisherRSI`).
+- **Disparity Index** — disparity index, the percent gap between price and its moving average (`DisparityIndex`).
+
+## [0.5.5] - 2026-06-04
+- **GD** — generalized DEMA (GD), Tillson's volume-factor double EMA and the building block of T3 (`GD`).
+- **GMA** — geometric moving average (GMA), the rolling geometric mean of prices (`GMA`).
+- **Holt-Winters** — Holt's linear (double exponential) smoothing with level and trend components (`HoltWinters`).
+- **Adaptive Laguerre** — Ehlers adaptive Laguerre filter with median-error-adaptive gamma (`AdaptiveLaguerre`).
+- **Median MA** — median moving average, the rolling median of prices (`MedianMA`).
+- **EHMA** — exponential Hull moving average (EHMA), the Hull construction built from EMAs (`EHMA`).
+- **SWMA** — sine-weighted moving average (SWMA), a symmetric half-cycle sine window (`SWMA`).
+
+## [0.5.4] - 2026-06-04
+- **Roll Measure** — effective spread implied by the negative serial covariance of trade-price changes (Roll 1984) (`RollMeasure`).
+- **Amihud Illiquidity** — average absolute log return per unit of traded value (price-impact liquidity proxy, Amihud 2002) (`AmihudIlliquidity`).
+- **VPIN** — volume-synchronised probability of informed trading (volume-bucketed order-flow toxicity) (`Vpin`).
+- **Order Flow Imbalance** — rolling sum of best-level order-flow events (Cont-Kukanov-Stoikov OFI) (`OrderFlowImbalance`).
+- **Expectancy** — expected return per unit of average loss (R-multiple) over a rolling window of returns (`Expectancy`).
+- **Win Rate** — fraction of strictly-positive returns over a rolling window (`WinRate`).
+- **Regime Label** — volatility-quantile regime classification: −1 calm / 0 normal / +1 stressed, by where the rolling volatility sits in its own recent distribution (`RegimeLabel`).
+- **Jump Indicator** — flags return outliers beyond `threshold ×` trailing return volatility (−1 down / 0 / +1 up) (`JumpIndicator`).
+- **Trend Label** — discrete trend state from the sign of the rolling least-squares slope (−1 / 0 / +1) (`TrendLabel`).
+- **High-Low Range** — bar high-low range as a fraction of close (scale-free per-bar volatility) (`HighLowRange`).
+- **Wick Ratio** — signed upper-vs-lower shadow imbalance as a fraction of the range (`WickRatio`).
+- **Body Size Percent** — absolute candle body as a fraction of the bar range (`BodySizePct`).
+- **Close vs Open** — signed body as a fraction of the open price, `(close − open) / open` (`CloseVsOpen`).
+- **Spread AR(1) Coefficient** — first-order autoregression coefficient of the spread `a − b` (direct cointegration / mean-reversion strength) (`SpreadAr1Coefficient`).
+- **Rolling Quantile** — interpolated q-th quantile over a trailing window (type-7 / NumPy default) (`RollingQuantile`).
+- **Rolling Percentile Rank** — percentile rank of the latest value within its trailing window (`RollingPercentileRank`).
+- **Rolling IQR** — interquartile range (Q3 − Q1) over a trailing window (robust dispersion) (`RollingIqr`).
+- **Realized Volatility** — square root of the summed squared log returns (raw, un-annualised quadratic variation) (`RealizedVolatility`).
+- **Log Return** — logarithmic return over a fixed lag, `ln(price_t / price_{t−period})` (`LogReturn`).
+
+## [0.5.3] - 2026-06-04
+- **Fibonacci Time Zones** — vertical markers at Fibonacci bar-distances (1/2/3/5/8/...) from the latest swing pivot (`FIB_TIME_ZONES`).
+- **Fibonacci Channel** — a sloped base trendline plus parallel lines at Fibonacci multiples of the channel width (`FIB_CHANNEL`).
+- **Fibonacci Arcs** — semicircular retracement levels centred on the swing end, normalised by leg bar-width (`FIB_ARCS`).
+- **Fibonacci Fan** — three trendlines fanning from a swing start through its 38.2/50/61.8% retracement levels (`FIB_FAN`).
+- **Fibonacci Confluence** — densest cluster of retracement levels across recent swing legs (price + strength) (`FIB_CONFLUENCE`).
+- **Golden Pocket** — the 0.618-0.65 optimal-trade-entry band of the most recent swing leg (`GOLDEN_POCKET`).
+- **Auto-Fibonacci** — retracement anchored on the dominant (largest-magnitude) leg among recent swings (`AUTO_FIB`).
+- **Fibonacci Projection** — measured-move target zone from the last three pivots (A-B-C), projecting A->B from C (`FIB_PROJECTION`).
+- **Fibonacci Extension** — projects the latest swing leg to the canonical extension ratios (127.2/141.4/161.8/200/261.8%) (`FIB_EXTENSION`).
+- **Fibonacci Retracement** — seven retracement levels (0/23.6/38.2/50/61.8/78.6/100%) of the most recent confirmed swing leg (`FIB_RETRACEMENT`).
+
+## [0.5.2] - 2026-06-03
+
+### Added
+- **Three Drives** — three symmetric drives with extension legs; bullish +1, bearish -1 (`THREE_DRIVES`).
+- **Cypher** — five-point harmonic whose D retraces XC by 0.786; bullish +1, bearish -1 (`CYPHER`).
+- **Shark** — five-point harmonic with an expansion leg and 0.886-1.13 D; bullish +1, bearish -1 (`SHARK`).
+- **Crab** — five-point harmonic with the deepest (1.618 XA) D completion; bullish +1, bearish -1 (`CRAB`).
+- **Bat** — five-point harmonic with a shallow B and 0.886 D completion; bullish +1, bearish -1 (`BAT`).
+- **Butterfly** — five-point harmonic with an extended (1.27-1.618 XA) D; bullish +1, bearish -1 (`BUTTERFLY`).
+- **Gartley** — five-point harmonic with a 0.786 D completion; bullish +1, bearish -1 (`GARTLEY`).
+- **AB=CD** — four-point AB=CD harmonic: BC retraces AB, CD mirrors AB; bullish +1, bearish -1 (`ABCD`).
+- **Cup and Handle** — rounded base with a shallow handle near the rim; bullish +1, inverse -1 (`CUP_AND_HANDLE`).
+- **Rectangle / Range** — flat support and resistance; mean-reversion signal off the just-touched boundary; support +1, resistance -1 (`RECTANGLE_RANGE`).
+- **Flag / Pennant** — shallow consolidation against a sharp pole; continuation in the pole direction; bull +1, bear -1 (`FLAG_PENNANT`).
+- **Wedge (rising/falling)** — both trendlines slope the same way but converge; rising wedge -1, falling wedge +1 (`WEDGE`).
+- **Triangle (asc/desc/sym)** — converging trendlines; ascending +1, descending -1, symmetrical follows the last swing (`TRIANGLE`).
+- **Head and Shoulders** — central head flanked by two matching shoulders over a flat neckline; top -1, inverse +1 (`HEAD_AND_SHOULDERS`).
+- **Triple Top / Bottom** — three matching peaks / troughs; a stronger reversal than the double; bearish -1, bullish +1 (`TRIPLE_TOP_BOTTOM`).
+- **Double Top / Bottom** — twin-peak / twin-trough reversal confirmed on the second matching swing extreme; bearish -1, bullish +1 (`DOUBLE_TOP_BOTTOM`).
+
+## [0.5.1] - 2026-06-03
+
+### Added — Seasonality & Session family (12 indicators)
+
+- **Volume-by-Time Profile** — mean traded volume bucketed by intraday time (`VOLUME_BY_TIME_PROFILE`).
+- **Intraday Volatility Profile** — return standard deviation bucketed by intraday time (`INTRADAY_VOLATILITY_PROFILE`).
+- **Day-of-Week Profile** — mean bar return bucketed by weekday (`DAY_OF_WEEK_PROFILE`).
+- **Time-of-Day Return Profile** — mean bar return bucketed by intraday time (`TIME_OF_DAY_RETURN_PROFILE`).
+- **Seasonal Z-Score** — z-score of the current return versus the same hour-of-day history (`SEASONAL_Z_SCORE`).
+- **Turn-of-Month** — mean daily return inside the turn-of-month window (`TURN_OF_MONTH`).
+- **Overnight/Intraday Return** — decomposition of session return into overnight and intraday legs (`OVERNIGHT_INTRADAY_RETURN`).
+- **Overnight Gap** — close-to-open return across the session boundary (`OVERNIGHT_GAP`).
+- **Average Daily Range** — mean high-low range of the last N completed sessions (`AVERAGE_DAILY_RANGE`).
+- **Session Range** — per-session (Asia/EU/US) high-low range (`SESSION_RANGE`).
+- **Session High/Low** — running high and low of the current session (`SESSION_HIGH_LOW`).
+- **Session VWAP** — session-anchored volume-weighted average price (`SESSION_VWAP`).
+
+## [0.5.0] - 2026-06-03
+
+### Added
+- **TICK Index** — instantaneous net advancing-minus-declining issues (`TICK_INDEX`).
+- **Absolute Breadth Index** — absolute value of net advancing-minus-declining issues (`ABSOLUTE_BREADTH_INDEX`).
+- **Cumulative Volume Index** — running total of volume-normalised net advancing volume (`CUMULATIVE_VOLUME_INDEX`).
+- **Bullish Percent Index** — percentage of the universe on a point-and-figure buy signal (`BULLISH_PERCENT_INDEX`).
+- **Up/Down Volume Ratio** — advancing volume divided by declining volume (`UP_DOWN_VOLUME_RATIO`).
+- **Percent Above Moving Average** — percentage of the universe trading above its reference moving average (`PERCENT_ABOVE_MA`).
+- **High-Low Index** — moving average of the record-high percentage (`HIGH_LOW_INDEX`).
+- **New Highs - New Lows** — net count of new period highs minus new period lows (`NEW_HIGHS_NEW_LOWS`).
+- **Breadth Thrust** — moving average of the advancing-issues share (Zweig) (`BREADTH_THRUST`).
+- **TRIN / Arms Index** — advance-decline ratio divided by the up-down volume ratio (`TRIN`).
+- **McClellan Summation Index** — running cumulative total of the McClellan Oscillator (`MCCLELLAN_SUMMATION_INDEX`).
+- **McClellan Oscillator** — spread between a 19- and 39-period EMA of ratio-adjusted net advances (`MCCLELLAN_OSCILLATOR`).
+- **Advance/Decline Volume Line** — cumulative net advancing-minus-declining volume across the universe (`AD_VOLUME_LINE`).
+- **Advance/Decline Ratio** — advancing issues divided by declining issues across the universe (`ADVANCE_DECLINE_RATIO`).
+
+### Changed
+- **Relicensed** from PolyForm Noncommercial 1.0.0 to dual **MIT OR Apache-2.0**. Wickra is now OSI-approved, permissive open source; commercial use is permitted under either license. See [`LICENSE-MIT`](LICENSE-MIT) and [`LICENSE-APACHE`](LICENSE-APACHE).
+
+## [0.4.7] - 2026-06-03
+
+### Added
+- **Spread Bollinger Bands** — Bollinger bands on the spread of two series for pairs mean-reversion (`SPREAD_BOLLINGER_BANDS`).
+- **Kalman Hedge Ratio** — Kalman-filter dynamic hedge ratio and spread between two series (`KALMAN_HEDGE_RATIO`).
+- **Granger Causality** — Granger causality F-statistic measuring whether one series predicts another (`GRANGER_CAUSALITY`).
+- **Variance Ratio** — Lo-MacKinlay variance-ratio test on the spread of two series (`VARIANCE_RATIO`).
+- **Beta-Neutral Spread** — beta-neutral spread: the rolling OLS regression residual of two series (`BETA_NEUTRAL_SPREAD`).
+- **Distance SSD** — Gatev sum-of-squared-deviations distance between two normalised series (`DISTANCE_SSD`).
+- **Spread Hurst** — Hurst exponent of the spread of two series for regime detection (`SPREAD_HURST`).
+- **OU Half-Life** — Ornstein-Uhlenbeck half-life of mean reversion for the spread of two series (`OU_HALF_LIFE`).
+- **Rolling Covariance** — rolling covariance of the period-over-period returns of two series (`ROLLING_COVARIANCE`).
+- **Rolling Correlation** — rolling Pearson correlation of the period-over-period returns of two series (`ROLLING_CORRELATION`).
+
+- **Market Breadth family** — a new indicator family built on a new
+  `CrossSection` input type that carries the per-symbol state of an entire
+  universe in one tick (each `Member` holds a signed `change`, a `volume`, and
+  `new_high` / `new_low` flags). `CrossSection::new` validates the universe
+  (non-empty, finite changes, finite non-negative volumes); `new_unchecked`
+  skips validation for hot paths.
+  - `AdvanceDecline` (`ADVANCE_DECLINE`) — the Advance/Decline Line, the running
+    cumulative sum of net advancing-minus-declining issues across the universe.
+
+## [0.4.6] - 2026-06-03
+
+### Added
+
+- **TA-Lib parity — Directional Movement components** — the ADX building blocks,
+  previously available only bundled inside `Adx`, as standalone single-output
+  indicators:
+  - `PlusDm` (`PLUS_DM`) — Wilder-smoothed plus directional movement.
+  - `MinusDm` (`MINUS_DM`) — Wilder-smoothed minus directional movement.
+  - `PlusDi` (`PLUS_DI`) — plus directional indicator, `100 · smoothed(+DM) / ATR`.
+  - `MinusDi` (`MINUS_DI`) — minus directional indicator, `100 · smoothed(-DM) / ATR`.
+  - `Dx` (`DX`) — directional movement index, `100 · |+DI − −DI| / (+DI + −DI)`.
+- **TA-Lib parity — price transforms** — window and per-bar price aggregates:
+  - `MidPrice` (`MIDPRICE`) — `(highest high + lowest low) / 2` over a window.
+  - `MidPoint` (`MIDPOINT`) — `(max + min) / 2` of a scalar series over a window.
+  - `AvgPrice` (`AVGPRICE`) — per-bar `(open + high + low + close) / 4`.
+- **TA-Lib parity — rate-of-change variants** — the ratio forms of `Roc`:
+  - `Rocp` (`ROCP`) — `(close − close[period]) / close[period]` (fraction).
+  - `Rocr` (`ROCR`) — `close / close[period]` (ratio).
+  - `Rocr100` (`ROCR100`) — `close / close[period] · 100`.
+- **TA-Lib parity — linear-regression outputs** — the remaining OLS endpoints:
+  - `LinRegIntercept` (`LINEARREG_INTERCEPT`) — the OLS intercept `a`.
+  - `Tsf` (`TSF`) — time series forecast, `a + b·period` (one bar ahead).
+- **TA-Lib parity — `MacdFix` (`MACDFIX`)** — MACD with fast/slow fixed at 12/26
+  and only the signal period configurable; output is the usual `{macd, signal,
+  histogram}` triple.
+- **TA-Lib parity — `SarExt` (`SAREXT`)** — Parabolic SAR with a start value,
+  reversal offset, independent long/short acceleration, and a signed output
+  (positive in long phases, negative in short phases).
+- **TA-Lib parity — `MacdExt` (`MACDEXT`)** — MACD with an independently
+  selectable moving-average type (new `MaType` enum: SMA/EMA/WMA/DEMA/TEMA/TRIMA)
+  for each of the fast, slow and signal lines.
+- **TA-Lib parity — `HtPhasor` (`HT_PHASOR`)** — the in-phase and quadrature
+  components of the Hilbert-transform analytic signal, as a `{inphase,
+  quadrature}` pair.
+- **TA-Lib parity — `HtDcPhase` (`HT_DCPHASE`)** — the phase angle (in degrees)
+  of the Hilbert-transform dominant cycle.
+- **TA-Lib parity — `HtTrendMode` (`HT_TRENDMODE`)** — Ehlers' trend (`1`) vs
+  cycle (`0`) classification from the Hilbert-transform dominant cycle.
+
+## [0.4.5] - 2026-06-02
+
+### Added
+
+- **Anchored RSI** — a cumulative Relative Strength Index whose averaging begins at a runtime-chosen anchor bar (`set_anchor`), the momentum counterpart to Anchored VWAP. Every up- and down-move since the anchor is weighted equally, so it reports the RSI of the entire move since the anchor point. Scalar input, Momentum Oscillators family; available in Rust, Python, Node and WASM.
+- **Volume Profile** — the full per-bin volume distribution over a rolling window, exposing the raw histogram (price bounds plus per-bin volume) that Value Area reduces to POC/VAH/VAL. Market Profile family; candle input, available in Rust, Python, Node and WASM.
+- **TPO Profile** — the Time-Price-Opportunity (market-profile letter) distribution: a volume-agnostic count of how many periods traded at each price level over a rolling window. Market Profile family; candle input, available in Rust, Python, Node and WASM.
+- **Alt-Chart Bars** — a new `BarBuilder` trait and family of price-driven chart constructors that emit a variable number of completed bars per candle (so they are deliberately not `Indicator`s): **Renko** (fixed box-size bricks with the 2-box reversal rule), **Kagi** (reversal-amount line segments), and **Point & Figure** (box-size X/O columns with an N-box reversal). Available in Rust, Python, Node and WASM.
+
+## [0.4.4] - 2026-06-02
+
+### Added
+- **TA-Lib candlestick patterns (part 1).** New candlestick pattern detectors
+  matching TA-Lib `CDL*`, emitting the family's signed `+1 / 0 / −1` convention
+  over OHLCV candles in Rust, Python, Node and WASM:
+  - **Two Crows** — a three-bar bearish reversal (`CDL2CROWS`): a long white
+    candle, a black candle whose body gaps up, then a black candle that opens
+    inside the second's body and closes inside the first's.
+  - **Upside Gap Two Crows** — a three-bar bearish reversal
+    (`CDLUPSIDEGAP2CROWS`): two black candles gap up over a long white candle,
+    the second engulfing the first crow yet still closing above the white body,
+    leaving the upside gap open.
+  - **Identical Three Crows** — a three-bar bearish reversal
+    (`CDLIDENTICAL3CROWS`): three red candles with steadily lower closes, each
+    opening at the prior candle's close so the bodies stack in an identical
+    staircase.
+  - **Three Line Strike** — a four-bar pattern (`CDL3LINESTRIKE`): a
+    three-candle advance or decline struck by a fourth opposite-colour candle
+    that engulfs the entire run; bullish `+1`, bearish `−1`.
+  - **Three Stars in the South** — a rare three-bar bullish reversal
+    (`CDL3STARSINSOUTH`): three shrinking red candles each carving a higher low
+    and contracting toward a tiny black marubozu as selling exhausts.
+  - **Abandoned Baby** — a strong three-bar reversal (`CDLABANDONEDBABY`): a doji
+    isolated by price gaps on both sides; bullish `+1` after a decline, bearish
+    `−1` after an advance.
+  - **Advance Block** — a three-bar bearish warning (`CDLADVANCEBLOCK`): three
+    green candles to higher closes whose bodies shrink as their upper shadows
+    lengthen, signalling the advance is stalling.
+  - **Belt-hold** — a single-bar reversal that opens at one extreme of its range and runs the other way; bullish +1, bearish -1 (`CDLBELTHOLD`).
+  - **Breakaway** — a 5-bar reversal that gaps with the trend, drifts two more bars, then snaps back into the bar1/bar2 body gap; bullish +1, bearish -1 (`CDLBREAKAWAY`).
+  - **Counterattack** — a 2-bar reversal where an opposite-coloured second bar closes level with the first (the counterattack line); bullish +1, bearish -1 (`CDLCOUNTERATTACK`).
+  - **Doji Star** — a long body followed by a doji gapping away in the trend direction; bullish +1, bearish -1 (`CDLDOJISTAR`).
+  - **Dragonfly Doji** — a doji opening and closing at the high with a long lower shadow, a bullish reversal; +1 (`CDLDRAGONFLYDOJI`).
+  - **Gravestone Doji** — a doji opening and closing at the low with a long upper shadow, a bearish reversal; -1 (`CDLGRAVESTONEDOJI`).
+  - **Long-Legged Doji** — a doji with long shadows on both sides, an indecision signal; +1 detection (`CDLLONGLEGGEDDOJI`).
+  - **Rickshaw Man** — a long-legged doji with the body centred in the range, an indecision signal; +1 detection (`CDLRICKSHAWMAN`).
+  - **Evening Doji Star** — a bearish top reversal: long white bar, a doji gapping up, then a black bar closing deep into the first body; -1 (`CDLEVENINGDOJISTAR`).
+  - **Morning Doji Star** — a bullish bottom reversal: long black bar, a doji gapping down, then a white bar closing deep into the first body; +1 (`CDLMORNINGDOJISTAR`).
+  - **Gap Side-by-Side White** — two similar white candles opening side by side after a gap, a continuation; gap up +1, gap down -1 (`CDLGAPSIDESIDEWHITE`).
+  - **High-Wave** — a small body with very long shadows on both sides, an extreme indecision signal; +1 detection (`CDLHIGHWAVE`).
+  - **Hikkake** — an inside bar followed by a failed breakout, a trap; bullish +1, bearish -1 (`CDLHIKKAKE`).
+  - **Modified Hikkake** — a close-confirmed Hikkake: an inside bar then a failed breakout closing back inside; bullish +1, bearish -1 (`CDLHIKKAKEMOD`).
+  - **Homing Pigeon** — two black candles, the second a small body inside the first, a bullish reversal; +1 (`CDLHOMINGPIGEON`).
+  - **On-Neck** — a long black candle then a white candle closing at its low (the neckline), a bearish continuation; -1 (`CDLONNECK`).
+  - **In-Neck** — a long black candle then a white candle closing just into its body, a bearish continuation; -1 (`CDLINNECK`).
+  - **Thrusting** — a long black candle then a white candle closing well into but below the midpoint of its body, a bearish continuation; -1 (`CDLTHRUSTING`).
+  - **Separating Lines** — opposite-coloured candles sharing the same open, the second an opening marubozu resuming the trend; bullish +1, bearish -1 (`CDLSEPARATINGLINES`).
+  - **Kicking** — two opposite-coloured marubozu separated by a gap; bullish +1, bearish -1 (`CDLKICKING`).
+  - **Kicking by Length** — a kicking pattern signalled by the colour of the longer marubozu; +1 / -1 (`CDLKICKINGBYLENGTH`).
+  - **Ladder Bottom** — three descending black candles, a fourth with an upper shadow, then a white candle gapping up, a bullish reversal; +1 (`CDLLADDERBOTTOM`).
+  - **Mat Hold** — a long white candle, a holding three-bar pullback, then a new-high white candle, a bullish continuation; +1 (`CDLMATHOLD`).
+  - **Matching Low** — a 2-bar bullish reversal where two black candles in a decline share the same close, signalling selling pressure is exhausting; bullish +1 (`CDLMATCHINGLOW`).
+  - **Long Line** — a single long-bodied candle with short shadows; bullish +1 (white) or bearish -1 (black) by colour (`CDLLONGLINE`).
+  - **Short Line** — a single short-bodied candle with short shadows; bullish +1 (white) or bearish -1 (black) by colour (`CDLSHORTLINE`).
+  - **Rising Three Methods** — a 5-bar bullish continuation: a long white candle, three small pullback bars holding within its range, then a white breakout to new highs; bullish +1 (`CDLRISEFALL3METHODS`).
+  - **Falling Three Methods** — the bearish mirror of rising three methods: a long black candle, three small bars holding within its range, then a black breakdown to new lows; bearish -1 (`CDLRISEFALL3METHODS`).
+  - **Upside Gap Three Methods** — a 3-bar bullish continuation: two white candles gap up, then a black candle opens within the second body and closes within the first; bullish +1 (`CDLXSIDEGAP3METHODS`).
+  - **Downside Gap Three Methods** — the bearish mirror of upside gap three methods: two black candles gap down, then a white candle opens within the second body and closes within the first; bearish -1 (`CDLXSIDEGAP3METHODS`).
+  - **Stalled Pattern** — a 3-bar bearish reversal warning: two long white candles then a small white candle riding the shoulder, signalling the rally is stalling; bearish -1 (`CDLSTALLEDPATTERN`).
+  - **Stick Sandwich** — a 3-bar bullish reversal: two black candles closing at the same level sandwich a white candle, marking a support floor; bullish +1 (`CDLSTICKSANDWICH`).
+  - **Takuri** — a single-bar bullish reversal, a strict Dragonfly Doji with a negligible upper shadow and very long lower shadow; bullish +1 (`CDLTAKURI`).
+  - **Closing Marubozu** — a single long-bodied candle with no shadow on the close end; bullish +1 (white, closes at the high) or bearish -1 (black, closes at the low) (`CDLCLOSINGMARUBOZU`).
+  - **Opening Marubozu** — a single long-bodied candle with no shadow on the open end; bullish +1 (white, opens at the low) or bearish -1 (black, opens at the high). No direct TA-Lib equivalent — completes the pair with the closing marubozu.
+  - **Tasuki Gap** — a 3-bar continuation: two same-coloured candles gap in the trend direction, then an opposite candle opens within the second body and closes back into the gap without filling it; upside +1, downside -1 (`CDLTASUKIGAP`).
+  - **Unique Three River** — a 3-bar bullish reversal: a long black candle, a black candle probing a new low with its body inside the first, then a small white candle held below it; bullish +1 (`CDLUNIQUE3RIVER`).
+  - **Concealing Baby Swallow** — a rare 4-bar bullish capitulation: two black marubozu, a black candle gapping down with an upper shadow into the second, then a large black candle engulfing it entirely; bullish +1 (`CDLCONCEALBABYSWALL`).
+- **Derivatives family — funding & open interest (part 1).** A new family of
+  indicators that consume a perpetual / futures tick (`DerivativesTick`,
+  bundling funding rate, mark / index / futures price, open interest,
+  positioning, taker flow and liquidations) rather than OHLCV, exposed in Rust,
+  Python, Node and WASM:
+  - **Funding Rate** — the current perpetual funding rate.
+  - **Funding Rate Mean** — the rolling mean funding rate over a window.
+  - **Funding Rate Z-Score** — the latest funding rate in standard deviations
+    from its rolling mean.
+  - **Funding Basis** — the perpetual's relative premium to spot,
+    `(markPrice − indexPrice) / indexPrice`.
+  - **Open-Interest Delta** — the tick-over-tick change in open interest.
+- **Derivatives family — open interest, flow & liquidations (part 2).** More
+  indicators over the same `DerivativesTick` feed:
+  - **OI / Price Divergence** — relative open-interest change minus relative
+    price change over a window, the positioning-vs-price gap.
+  - **OI-Weighted Price** — the cumulative mark price weighted by open interest.
+  - **Long/Short Ratio** — aggregate long size over short size.
+  - **Taker Buy/Sell Ratio** — taker buy volume over taker sell volume.
+  - **Liquidation Features** — a multi-output breakdown of long/short
+    liquidation notional into net, total and a bounded imbalance.
+- **Derivatives family — basis & term structure (part 3).** The final
+  perpetual-vs-futures basis indicators over the `DerivativesTick` feed:
+  - **Term-Structure Basis** — the dated future's relative premium to spot,
+    `(futuresPrice − indexPrice) / indexPrice`.
+  - **Calendar Spread** — the dated future's relative premium to the perpetual,
+    `(futuresPrice − markPrice) / markPrice`.
+
+## [0.4.3] - 2026-06-01
+
+### Added
+- **Microstructure family — price impact & depth (part 3).** Indicators over a
+  trade paired with the prevailing mid (`TradeQuote`) and over the order-book
+  depth profile, exposed in Rust, Python, Node and WASM:
+  - **Effective Spread** — `2 · D · (tradePrice − mid) / mid · 10_000` bps, the
+    realised round-trip cost of a single trade against the mid.
+  - **Realized Spread** — `2 · D · (tradePrice − mid_{t+horizon}) / mid_t ·
+    10_000` bps, the share of the effective spread a liquidity provider keeps
+    once the mid has moved over a configurable horizon.
+  - **Kyle's Lambda** — the rolling OLS slope of mid changes on signed volume
+    (`cov(Δmid, q) / var(q)`), the canonical price-impact / market-depth proxy.
+  - **Depth Slope** — the mean per-side OLS slope of cumulative resting size
+    against distance from the mid, measuring how fast the book thickens away
+    from the touch.
+- **Microstructure family — footprint (part 4).** **Footprint** decomposes the
+  volume traded in a bar across price buckets (`round(price / tick_size)`),
+  splitting each bucket into buy-initiated (ask) and sell-initiated (bid)
+  volume. A multi-output, variable-length indicator: every `update` returns the
+  full footprint accumulated since the last `reset`, exposed in Rust, Python
+  (`(k, 3)` arrays), Node (`{ price, bidVol, askVol }` rows) and WASM.
+
+## [0.4.2] - 2026-06-01
+
+### Added
+- **Microstructure family — order book (part 1).** A new family of indicators
+  that consume an order-book depth snapshot (`OrderBook` of sorted, uncrossed
+  bid/ask `Level`s) rather than OHLCV, exposed in Rust, Python, Node and WASM:
+  - **Order-Book Imbalance** — `OrderBookImbalanceTop1`, `OrderBookImbalanceTopN`
+    (configurable depth) and `OrderBookImbalanceFull` measure signed depth
+    pressure `(bidDepth − askDepth) / (bidDepth + askDepth)` over the top level,
+    the top-N levels, or the full book.
+  - **Microprice** — the size-weighted fair value
+    `(bidPx·askSz + askPx·bidSz) / (bidSz + askSz)`, tilting the mid toward the
+    side more likely to be hit.
+  - **Quoted Spread** — the top-of-book spread in basis points of the mid.
+- **Microstructure family — trade flow (part 2).** Indicators over a trade tape
+  (`Trade` with an aggressor `Side`), exposed in Rust, Python, Node and WASM:
+  - **Signed Volume** — per-trade size signed by aggressor side (`+size` buy,
+    `−size` sell).
+  - **Cumulative Volume Delta** — the running total of signed volume; reset to
+    re-anchor per session.
+  - **Trade Imbalance** — the rolling `(buyVol − sellVol)/(buyVol + sellVol)`
+    over a configurable window of trades.
+
+  New public value types `Level`, `OrderBook`, `Side`, `Trade` and `TradeQuote`
+  back this and the upcoming trade-flow and price-impact indicators. Python and
+  Node accept a batch over a list of snapshots; WASM exposes per-snapshot
+  `update`.
+- **Signed Doji encoding.** `Doji` gains an opt-in `.signed()` mode
+  (`Doji(signed=True)` in Python, `new Doji(true)` in Node and WASM) that
+  classifies a detected Doji by the position of its body within the bar range —
+  a dragonfly (long lower shadow) emits `+1.0` (bullish), a gravestone (long
+  upper shadow) emits `−1.0` (bearish), and a long-legged / standard Doji emits
+  `0.0` (neutral). The default construction is unchanged — a direction-less
+  `+1.0` / `0.0` detection flag — so existing callers are unaffected. This
+  completes the uniform `+1` bull / `−1` bear / `0` none sign convention across
+  every candlestick pattern, making the family a drop-in machine-learning
+  feature where bullish and bearish instances share a single dimension.
+
+### Fixed
+- **README banner now self-updates.** The top README banner points at the org
+  profile image that `.github/banner.yml` regenerates from the indicator count,
+  and `sync-about.yml` bumps a `?v=<count>` cache-buster so GitHub's Camo proxy
+  refetches it immediately. Also fixes the webpage indicator-count sync, which
+  silently crashed on a removed `public/hero.svg` and left the marketing site's
+  count (and its OG banner) stale.
+
+### Security
+- **CI dependency installs are pinned by hash.** The Node binding now installs
+  with `npm ci` (strict `package-lock.json`), and the Python CI/bench tooling is
+  installed from hash-locked `--require-hashes` requirements under
+  `.github/requirements/` (OpenSSF Scorecard PinnedDependencies). The `ci-dev`
+  tooling is locked twice — for Python 3.9 and for 3.10+ — because numpy ships no
+  single release with wheels for both cp39 and cp313. A new
+  `scripts/update-lockfiles.sh` regenerates every workspace lockfile (Rust, Node
+  and the hash-pinned Python requirements) via `uv`, and Dependabot keeps the
+  pinned requirements current.
+
 ## [0.4.1] - 2026-06-01

 ### Added
@@ -900,7 +1308,25 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
  optional Binance live feed.
 - Bindings for Python, Node.js, and WebAssembly.

-[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.4.1...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.6.1...HEAD
+[0.6.1]: https://github.com/wickra-lib/wickra/compare/v0.6.0...v0.6.1
+[0.6.0]: https://github.com/wickra-lib/wickra/compare/v0.5.9...v0.6.0
+[0.5.9]: https://github.com/wickra-lib/wickra/compare/v0.5.8...v0.5.9
+[0.5.8]: https://github.com/wickra-lib/wickra/compare/v0.5.7...v0.5.8
+[0.5.7]: https://github.com/wickra-lib/wickra/compare/v0.5.6...v0.5.7
+[0.5.6]: https://github.com/wickra-lib/wickra/compare/v0.5.5...v0.5.6
+[0.5.5]: https://github.com/wickra-lib/wickra/compare/v0.5.4...v0.5.5
+[0.5.4]: https://github.com/wickra-lib/wickra/compare/v0.5.3...v0.5.4
+[0.5.3]: https://github.com/wickra-lib/wickra/compare/v0.5.2...v0.5.3
+[0.5.2]: https://github.com/wickra-lib/wickra/compare/v0.5.1...v0.5.2
+[0.5.1]: https://github.com/wickra-lib/wickra/compare/v0.5.0...v0.5.1
+[0.5.0]: https://github.com/wickra-lib/wickra/compare/v0.4.7...v0.5.0
+[0.4.7]: https://github.com/wickra-lib/wickra/compare/v0.4.6...v0.4.7
+[0.4.6]: https://github.com/wickra-lib/wickra/compare/v0.4.5...v0.4.6
+[0.4.5]: https://github.com/wickra-lib/wickra/compare/v0.4.4...v0.4.5
+[0.4.4]: https://github.com/wickra-lib/wickra/compare/v0.4.3...v0.4.4
+[0.4.3]: https://github.com/wickra-lib/wickra/compare/v0.4.2...v0.4.3
+[0.4.2]: https://github.com/wickra-lib/wickra/compare/v0.4.1...v0.4.2
 [0.4.1]: https://github.com/wickra-lib/wickra/compare/v0.4.0...v0.4.1
 [0.4.0]: https://github.com/wickra-lib/wickra/compare/v0.3.1...v0.4.0
 [0.3.1]: https://github.com/wickra-lib/wickra/compare/v0.3.0...v0.3.1
@@ -26,4 +26,6 @@ keywords:
  - quantitative-finance
  - rust
  - time-series
-license: PolyForm-Noncommercial-1.0.0
+license:
+  - MIT
+  - Apache-2.0
@@ -5,11 +5,11 @@ build the project, the standards a change must meet, and how to get it merged.

 ## License of contributions

-Wickra is licensed under the **PolyForm Noncommercial License 1.0.0** (see
-[`LICENSE`](LICENSE)). By submitting a contribution you agree that it is
-licensed to the project under those same terms. The Noncommercial license
-permits use for any purpose **other than** a commercial one; keep that in mind
-when proposing features or depending on Wickra elsewhere.
+Wickra is dual-licensed under the [MIT](LICENSE-MIT) and
+[Apache-2.0](LICENSE-APACHE) licenses; users may choose either. Unless you
+explicitly state otherwise, any contribution you intentionally submit for
+inclusion in the work, as defined in the Apache-2.0 license, shall be dual
+licensed as above, without any additional terms or conditions.

 ## Project layout

@@ -22,7 +22,7 @@ when proposing features or depending on Wickra elsewhere.
 | `bindings/node` | napi-rs bindings (`wickra` on npm). |
 | `bindings/wasm` | wasm-bindgen bindings (`wickra-wasm` on npm). |
 | `examples/` | Runnable examples. |
-| `docs/` | Pointer to the project Wiki, which holds all documentation. |
+| `docs/` | Pointer to the documentation site (docs.wickra.org); the docs live in the `wickra-lib/wickra-docs` repo. |

 ## Building and testing

@@ -75,7 +75,8 @@ wasm-pack test --node bindings/wasm
 | Workspace (Rust) | `Cargo.lock` | **yes** | The workspace ships binaries (examples, fuzz harness) and CI builds, so the dependency graph is pinned for reproducible builds. |
 | `bindings/node` | `package-lock.json` | **yes** | Reproducible `npm install` for the native binding. |
 | `examples/node` | `package-lock.json` | **yes** | Same — the runnable Node examples link the binding via a `file:` dependency. |
-| `bindings/python` | — | n/a (no lockfile) | PyO3 convention: the Python package has no Python runtime dependencies of its own, and its native code is already pinned through the workspace `Cargo.lock`. CI installs build/test tooling (`maturin`, `pytest`, `numpy`, `hypothesis`) directly via `pip`. |
+| `bindings/python` | — | n/a (no lockfile) | The published package pins only `numpy>=1.22` at runtime; its native code is pinned through the workspace `Cargo.lock`. The CI/bench dev tooling it installs is hash-locked separately — see the `.github/requirements` row. |
+| `.github/requirements` | `*.txt` (hash-pinned) | **yes** | CI/bench Python tooling, locked with `uv pip compile --generate-hashes` (OpenSSF Scorecard PinnedDependencies). `ci-dev` is split per Python version — `ci-dev-py39.txt` and `ci-dev-py3.txt` — because numpy ships no single release with wheels for both cp39 and cp313; `bench.txt` covers the single-version bench job. |
 | `fuzz` | `fuzz/Cargo.lock` | **no** (ignored) | `fuzz/` is a detached crate; `cargo-fuzz init` generates `fuzz/.gitignore` which ignores its `Cargo.lock`. The fuzz smoke job resolves dependencies fresh, so the lock is not needed for reproducibility here. |
 | `site` (marketing) | `package-lock.json` | **no** (ghost-ignored) | The VitePress site is a local-only project excluded via `.git/info/exclude`; its lockfile stays local. |

@@ -83,6 +84,13 @@ When adding a new committed Node package, commit its `package-lock.json` too and
 remove any matching ignore rule. Do **not** add a top-level `package-lock.json` —
 the repository root is not an npm package.

+To refresh every committed lockfile in the workspace — `Cargo.lock`,
+`fuzz/Cargo.lock`, the Node binding lock, and the hash-pinned Python
+requirements — run `./scripts/update-lockfiles.sh`. It uses `uv` for the Python
+locks (and bootstraps it on Linux/macOS if absent) so each target Python
+version's hashed transitive closure can be regenerated without that interpreter
+installed. Dependabot also keeps the `.github/requirements` pins current.
+
 ## Standards for a change

 - **Formatting & lints.** `cargo fmt` must leave the tree unchanged and
@@ -114,3 +122,33 @@ the repository root is not an npm package.
 Use the issue templates under
 [`.github/ISSUE_TEMPLATE`](.github/ISSUE_TEMPLATE). For security-sensitive
 reports, follow [`SECURITY.md`](SECURITY.md) instead of opening a public issue.
+
+## Developer Certificate of Origin (DCO)
+
+All contributions to Wickra are made under the [Developer Certificate of
+Origin (DCO) 1.1](DCO). By signing off on your commits you certify that you
+wrote the patch, or otherwise have the right to submit it under the project's
+`MIT OR Apache-2.0` license.
+
+Sign off every commit by adding a `Signed-off-by` trailer with your real name
+and email — Git adds it automatically with the `-s` flag:
+
+```bash
+git commit -s -m "your message"
+```
+
+This produces a trailer of the form:
+
+```
+Signed-off-by: Your Name <you@example.com>
+```
+
+The name and email must match the commit author. Commits without a valid
+sign-off line cannot be merged. To sign off a commit you already made, amend it
+with `git commit -s --amend`, or sign off a range with an interactive rebase.
+
+## Governance
+
+Wickra's decision-making and maintainership are described in
+[`GOVERNANCE.md`](GOVERNANCE.md); the current maintainers are listed in
+[`MAINTAINERS.md`](MAINTAINERS.md).
@@ -702,6 +702,16 @@ dependencies = [
 "wasm-bindgen",
 ]

+[[package]]
+name = "kand"
+version = "0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "af1f41590bd014ef6c3dd815b45f07deb4c3198e355a4319bb7521b6a3a6aeb5"
+dependencies = [
+ "num_enum",
+ "thiserror",
+]
+
 [[package]]
 name = "leb128fmt"
 version = "0.1.0"
@@ -911,6 +921,28 @@ dependencies = [
 "libm",
 ]

+[[package]]
+name = "num_enum"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5d0bca838442ec211fa11de3a8b0e0e8f3a4522575b5c4c06ed722e005036f26"
+dependencies = [
+ "num_enum_derive",
+ "rustversion",
+]
+
+[[package]]
+name = "num_enum_derive"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "680998035259dcfcafe653688bf2aa6d3e2dc05e98be6ab46afb089dc84f1df8"
+dependencies = [
+ "proc-macro-crate",
+ "proc-macro2",
+ "quote",
+ "syn",
+]
+
 [[package]]
 name = "numpy"
 version = "0.28.0"
@@ -1081,6 +1113,15 @@ dependencies = [
 "syn",
 ]

+[[package]]
+name = "proc-macro-crate"
+version = "3.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f"
+dependencies = [
+ "toml_edit",
+]
+
 [[package]]
 name = "proc-macro2"
 version = "1.0.106"
@@ -1498,6 +1539,12 @@ dependencies = [
 "syn",
 ]

+[[package]]
+name = "ta"
+version = "0.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "609409d472a0a7d8d4dd9e19891bbdef546b9dce670c3057d0e02192dc541226"
+
 [[package]]
 name = "target-lexicon"
 version = "0.13.5"
@@ -1607,6 +1654,36 @@ dependencies = [
 "tungstenite",
 ]

+[[package]]
+name = "toml_datetime"
+version = "1.1.1+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7"
+dependencies = [
+ "serde_core",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.25.12+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d2153edc6955a6c354fad8f5efd38b6a8769bdccf9fe50f8e1329f81b0baa5d7"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "toml_parser",
+ "winnow",
+]
+
+[[package]]
+name = "toml_parser"
+version = "1.1.2+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a2abe9b86193656635d2411dc43050282ca48aa31c2451210f4202550afb7526"
+dependencies = [
+ "winnow",
+]
+
 [[package]]
 name = "tungstenite"
 version = "0.29.0"
@@ -1867,7 +1944,7 @@ dependencies = [

 [[package]]
 name = "wickra"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "approx",
 "criterion",
@@ -1876,9 +1953,21 @@ dependencies = [
 "wickra-data",
 ]

+[[package]]
+name = "wickra-bench"
+version = "0.6.1"
+dependencies = [
+ "criterion",
+ "kand",
+ "ta",
+ "wickra",
+ "wickra-data",
+ "yata",
+]
+
 [[package]]
 name = "wickra-core"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "approx",
 "proptest",
@@ -1888,7 +1977,7 @@ dependencies = [

 [[package]]
 name = "wickra-data"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "approx",
 "csv",
@@ -1905,7 +1994,7 @@ dependencies = [

 [[package]]
 name = "wickra-examples"
-version = "0.0.0"
+version = "0.6.1"
 dependencies = [
 "serde_json",
 "tokio",
@@ -1915,7 +2004,7 @@ dependencies = [

 [[package]]
 name = "wickra-node"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "napi",
 "napi-build",
@@ -1925,7 +2014,7 @@ dependencies = [

 [[package]]
 name = "wickra-python"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "numpy",
 "pyo3",
@@ -1934,7 +2023,7 @@ dependencies = [

 [[package]]
 name = "wickra-wasm"
-version = "0.4.1"
+version = "0.6.1"
 dependencies = [
 "console_error_panic_hook",
 "js-sys",
@@ -1991,6 +2080,15 @@ dependencies = [
 "windows-link",
 ]

+[[package]]
+name = "winnow"
+version = "1.0.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0592e1c9d151f854e6fd382574c3a0855250e1d9b2f99d9281c6e6391af352f1"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "wit-bindgen"
 version = "0.51.0"
@@ -2091,6 +2189,15 @@ version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "1ffae5123b2d3fc086436f8834ae3ab053a283cfac8fe0a0b8eaae044768a4c4"

+[[package]]
+name = "yata"
+version = "0.7.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6b4ef8ddfa3ccd93454262c0e60a43a2bbf403d404174e1815f7581d5028229f"
+dependencies = [
+ "serde",
+]
+
 [[package]]
 name = "yoke"
 version = "0.8.2"
@@ -8,15 +8,16 @@ members = [
    "bindings/wasm",
    "bindings/node",
    "examples/rust",
+    "crates/wickra-bench",
 ]
 exclude = ["fuzz"]

 [workspace.package]
-version = "0.4.1"
+version = "0.6.1"
 authors = ["kingchenc <support@wickra.org>"]
 edition = "2021"
 rust-version = "1.86"
-license = "PolyForm-Noncommercial-1.0.0"
+license = "MIT OR Apache-2.0"
 repository = "https://github.com/wickra-lib/wickra"
 homepage = "https://github.com/wickra-lib/wickra"
 readme = "README.md"
@@ -24,7 +25,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
 categories = ["finance", "mathematics", "science"]

 [workspace.dependencies]
-wickra-core = { path = "crates/wickra-core", version = "0.4.1" }
+wickra-core = { path = "crates/wickra-core", version = "0.6.1" }

 thiserror = "2"
 rayon = "1.10"
@@ -0,0 +1,34 @@
+Developer Certificate of Origin
+Version 1.1
+
+Copyright (C) 2004, 2006 The Linux Foundation and its contributors.
+
+Everyone is permitted to copy and distribute verbatim copies of this
+license document, but changing it is not allowed.
+
+
+Developer's Certificate of Origin 1.1
+
+By making a contribution to this project, I certify that:
+
+(a) The contribution was created in whole or in part by me and I
+    have the right to submit it under the open source license
+    indicated in the file; or
+
+(b) The contribution is based upon previous work that, to the best
+    of my knowledge, is covered under an appropriate open source
+    license and I have the right under that license to submit that
+    work with modifications, whether created in whole or in part
+    by me, under the same open source license (unless I am
+    permitted to submit under a different license), as indicated
+    in the file; or
+
+(c) The contribution was provided directly to me by some other
+    person who certified (a), (b) or (c) and I have not modified
+    it.
+
+(d) I understand and agree that this project and the contribution
+    are public and that a record of the contribution (including all
+    personal information I submit with it, including my sign-off) is
+    maintained indefinitely and may be redistributed consistent with
+    this project or the open source license(s) involved.
@@ -0,0 +1,71 @@
+# Governance
+
+Wickra is an open-source project maintained under a **single-maintainer
+("BDFL") model**. This document describes how decisions are made and how the
+project is run, so contributors know what to expect.
+
+## Roles
+
+- **Maintainer.** The maintainer (see [`MAINTAINERS.md`](MAINTAINERS.md)) is
+  responsible for the project's direction, reviews and merges changes, cuts
+  releases, and has final say on all technical and project decisions.
+- **Contributors.** Anyone who proposes changes via pull requests, files
+  issues, improves documentation, or otherwise participates. Contributors do
+  not need any special status to take part.
+
+## Decision-making
+
+- Day-to-day technical decisions (APIs, indicator implementations, refactors)
+  are made by the maintainer, informed by discussion on issues and pull
+  requests.
+- Proposals are raised as GitHub issues or pull requests. Significant or
+  breaking changes should be opened as an issue first to agree on the approach
+  before implementation.
+- The maintainer aims to act transparently: rationale for non-trivial decisions
+  is recorded in the relevant issue, pull request, or commit message.
+
+## Contribution flow
+
+All changes — including the maintainer's own — go through pull requests so that
+CI (tests, linting, static analysis) runs against them, and so the change
+history is reviewable. Contribution requirements are documented in
+[`CONTRIBUTING.md`](CONTRIBUTING.md), including the Developer Certificate of
+Origin sign-off that every commit must carry.
+
+## Becoming a maintainer
+
+The project currently has one maintainer. Maintainership may be extended to
+contributors who have demonstrated sustained, high-quality involvement, at the
+current maintainer's discretion. If the project grows to multiple maintainers,
+this document will be updated to describe shared decision-making.
+
+## Continuity and succession
+
+The project is designed to survive the loss of any single individual, so that
+issues can be triaged, proposed changes accepted, and releases published within
+one week of confirmed loss of the maintainer:
+
+- **Credentials.** All credentials required to operate the project — the
+  `wickra-lib` GitHub organization, the publishing tokens for crates.io, PyPI
+  and npm, and the `wickra.org` domain registrar — are stored in a password
+  manager. A trusted contact (a family member) holds **emergency access** to
+  that password manager and can obtain these credentials if the maintainer can
+  no longer continue.
+- **Continuity actions.** With that access, the trusted contact (or a delegate
+  they appoint) can create and close issues, accept pull requests, and publish
+  releases through the existing CI/CD workflows.
+- **Account recovery.** The maintainer's GitHub account has recovery configured,
+  and ownership of the `wickra-lib` organization can be transferred to a new
+  maintainer.
+- **Legal rights.** Legal rights to the project name and DNS are covered by the
+  maintainer's estate arrangements.
+
+## Code of conduct
+
+All participants are expected to follow the
+[Code of Conduct](CODE_OF_CONDUCT.md).
+
+## Changes to this document
+
+This governance model may evolve as the project grows. Changes are made via
+pull request and take effect once merged.
@@ -1,136 +0,0 @@
-# PolyForm Noncommercial License 1.0.0
-
-<https://polyformproject.org/licenses/noncommercial/1.0.0>
-
-## Acceptance
-
-In order to get any license under these terms, you must agree
-to them as both strict obligations and conditions to all
-your licenses.
-
-## Copyright License
-
-The licensor grants you a copyright license for the
-software to do everything you might do with the software
-that would otherwise infringe the licensor's copyright
-in it for any permitted purpose. However, you may
-only distribute the software according to [Distribution
-License](#distribution-license) and make changes or new works
-based on the software according to [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Distribution License
-
-The licensor grants you an additional copyright license
-to distribute copies of the software. Your license to
-distribute covers distributing the software with changes
-and new works permitted by [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Notices
-
-You must ensure that anyone who gets a copy of any part of
-the software from you also gets a copy of these terms or the
-URL for them above, as well as copies of any plain-text lines
-beginning with `Required Notice:` that the licensor provided
-with the software. For example:
-
-> Required Notice: Copyright 2026 kingchenc (https://github.com/wickra-lib/wickra)
-
-## Changes and New Works License
-
-The licensor grants you an additional copyright license
-to make changes and new works based on the software for any
-permitted purpose.
-
-## Patent License
-
-The licensor grants you a patent license for the software that
-covers patent claims the licensor can license, or becomes able
-to license, that you would infringe by using the software.
-
-## Noncommercial Purposes
-
-Any noncommercial purpose is a permitted purpose.
-
-## Personal Uses
-
-Personal use for research, experiment, and testing for
-the benefit of public knowledge, personal study, private
-entertainment, hobby projects, amateur pursuits, or religious
-observance, without any anticipated commercial application,
-is use for a permitted purpose.
-
-## Noncommercial Organizations
-
-Use by any charitable organization, educational institution,
-public research organization, public safety or health
-organization, environmental protection organization, or
-government institution is use for a permitted purpose regardless
-of the source of funding or obligations resulting from the
-funding.
-
-## Fair Use
-
-You may have "fair use" rights for the software under the
-law. These terms do not limit them.
-
-## No Other Rights
-
-These terms do not allow you to sublicense or transfer any of
-your licenses to anyone else, or prevent the licensor from
-granting licenses to anyone else.  These terms do not imply
-any other licenses.
-
-## Patent Defense
-
-If you make any written claim that the software infringes or
-contributes to infringement of any patent, your patent license
-for the software granted under these terms ends immediately. If
-your company makes such a claim, your patent license ends
-immediately for work on behalf of your company.
-
-## Violations
-
-The first time you are notified in writing that you have
-violated any of these terms, or done anything with the software
-not covered by your licenses, your licenses can nonetheless
-continue if you come into full compliance with these terms,
-and take practical steps to correct past violations, within 32
-days of receiving notice.  Otherwise, all your licenses end
-immediately.
-
-## No Liability
-
-***As far as the law allows, the software comes as is, without
-any warranty or condition, and the licensor will not be liable
-to you for any damages arising out of these terms or the use
-or nature of the software, under any kind of legal claim.***
-
-## Definitions
-
-The **licensor** is the individual or entity offering these
-terms, and the **software** is the software the licensor makes
-available under these terms.
-
-**You** refers to the individual or entity agreeing to these
-terms.
-
-**Your company** is any legal entity, sole proprietorship,
-or other kind of organization that you work for, plus all
-organizations that have control over, are under the control
-of, or are under common control with that organization.
-**Control** means ownership of substantially all the assets
-of an entity, or the power to direct its management and
-policies by vote, contract, or otherwise.  Control can be
-direct or indirect.
-
-**Your licenses** are all the licenses granted to you for the
-software under these terms.
-
-**Use** means anything you do with the software requiring one
-of your licenses.
-
---
-
-Required Notice: Copyright 2026 kingchenc (https://github.com/wickra-lib/wickra)
@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or Derivative
+          Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright 2026 kingchenc and the Wickra contributors
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 kingchenc and the Wickra contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or Derivative
+          Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright 2026 kingchenc and the Wickra contributors
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 kingchenc and the Wickra contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
@@ -0,0 +1,17 @@
+# Maintainers
+
+This file lists the current maintainers of Wickra. See
+[`GOVERNANCE.md`](GOVERNANCE.md) for what the role entails and how the project
+is run.
+
+| Maintainer | GitHub | Areas |
+| --- | --- | --- |
+| kingchenc | [@kingchenc](https://github.com/kingchenc) | All (core, bindings, CI/release, docs) |
+
+## Contacting the maintainers
+
+- General questions and support: see [`SUPPORT.md`](SUPPORT.md).
+- Bug reports and feature requests: open an issue using the
+  [issue templates](.github/ISSUE_TEMPLATE).
+- Security reports: follow [`SECURITY.md`](SECURITY.md) — do **not** open a
+  public issue.
@@ -1,5 +1,5 @@
 <p align="center">
-  <a href="https://wickra.org"><img src="https://wickra.org/og-banner.webp" alt="Wickra — streaming-first technical indicators" width="100%"></a>
+  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=434" alt="Wickra — streaming-first technical indicators" width="100%"></a>
 </p>

 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
@@ -9,8 +9,9 @@
 [![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
 [![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
 [![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](#license)
 [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/wickra-lib/wickra/badge)](https://scorecard.dev/viewer/?uri=github.com/wickra-lib/wickra)
+[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/13094/badge)](https://www.bestpractices.dev/projects/13094)
 [![Build provenance](https://img.shields.io/badge/provenance-attested-brightgreen?logo=github)](https://github.com/wickra-lib/wickra/attestations)
 [![Docs](https://img.shields.io/badge/docs-docs.wickra.org-0ea5e9?logo=readthedocs&logoColor=white)](https://docs.wickra.org)

@@ -47,7 +48,7 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
  [Node](https://docs.wickra.org/Quickstart-Node),
  [WASM](https://docs.wickra.org/Quickstart-WASM).
 - **Indicators** — a per-indicator deep dive (formula, parameters, warmup) for
-  every one of the 219 indicators; start at the
+  every one of the 434 indicators; start at the
  [indicators overview](https://docs.wickra.org/Indicators-Overview).
 - **Reference** — [warmup periods](https://docs.wickra.org/Warmup-Periods),
  [streaming vs batch](https://docs.wickra.org/Streaming-vs-Batch),
@@ -59,105 +60,171 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:

 ## Why Wickra exists

-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
+Wickra started as a personal itch. The existing TA libraries never quite fit the
+projects I was building, so I decided to build one from the ground up — partly to
+learn, partly because I genuinely enjoy taking something that already exists and
+trying to do it differently (and, ideally, better). It's open source because the
+useful version of that itch is the one other people can build on too.

-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★&nbsp;Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
+Plenty of TA libraries are fast. Each one forces a trade-off Wickra does not:

-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
+| Library          | Install     | Streaming   | Languages                   | Indicators | Active |
+|------------------|-------------|-------------|-----------------------------|-----------:|--------|
+| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Python · Node · WASM · Rust** | **423** | **yes** |
+| kand             | clean       | yes         | Python · WASM · Rust        |       ~60  | yes    |
+| ta-rs            | clean       | yes         | Rust only                   |       ~30  | stale  |
+| yata             | clean       | partial     | Rust only                   |       ~35  | yes    |
+| TA-Lib           | yes (C deps)| no          | many bindings               |      ~150  | barely |
+| pandas-ta        | clean       | no          | Python                      |      ~130  | slow   |
+| finta            | clean       | no          | Python                      |       ~80  | stale  |
+| talipp           | clean       | yes         | Python                      |       ~40  | yes    |

-## Benchmark: how much faster is "streaming-first"?
+Wickra's edge is **breadth with reach**: 434 indicators that all update in O(1)
+per tick and ship natively to Python, Node.js, WebAssembly and Rust from a
+single engine.

-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
+**On speed — and why Wickra isn't the fastest.** It deliberately isn't. The
+leaner Rust crates (kand, ta-rs) win several of the micro-benchmarks below, and
+those losses are shown rather than hidden. The gap is a *choice*, not a ceiling:
+every `update` validates its input, runs a real warmup before it emits a value,
+and returns an `Option` so a single bad tick can't silently poison the state.
+ta-rs, by contrast, hands back a bare `f64` from the first tick with no
+validation. If Wickra threw all of that away — raw `f64` out, no checks, no
+warmup contract — it would match or beat the leanest crate on every row. It
+keeps the guarantees instead, and still wins RSI, Bollinger and ATR against kand.
+What no other library matches is the *combination*: catalogue size, native O(1)
+streaming, NaN-safety, and four first-class language targets at once.
+
+## Benchmarks
+
+Three comparisons, split by layer and mode. Read them as **relative** speedups
+on identical input — absolute µs depend on CPU, memory clock and OS scheduler,
+not a universal contract.

 - **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
+  Rust 1.92 (release: `lto = "fat"`, `codegen-units = 1`), Python 3.12.
+- **Reproduce yourself:**
+  - Rust core vs Rust crates: `cargo bench -p wickra-bench`
+  - Python vs Python libs: `pip install -e bindings/python[bench]` then
+    `python -m benchmarks.compare_libraries` (auto-detects installed peers).

-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
+### 1. Rust core vs the other Rust TA crates

-### Batch — single full pass over a 20 000-bar series
+Like-for-like, no language-binding overhead, over a 50 000-bar series (µs for
+the whole series, lower = faster). This is the honest engine comparison —
+Wickra wins some and loses some, and both are shown.

-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
+**Streaming** (one value fed per `update`):

-| Indicator           | **★&nbsp;Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
+| Indicator        | **★&nbsp;Wickra** | kand | ta-rs | yata |
+|------------------|------------------:|-----:|------:|-----:|
+| SMA(20)          | 50                | 38   | 47    | 38   |
+| EMA(20)          | 154               | 69   | 56    | 69   |
+| RSI(14)          | 164               | 216  | 74    | —    |
+| MACD(12, 26, 9)  | 275               | 143  | 66    | —    |
+| Bollinger(20, 2) | **128 ★**         | 248  | 168   | —    |
+| ATR(14)          | 152               | 166  | 61    | —    |

-### Streaming — per-tick latency after seeding with 5 000 historical bars
+**Batch** (whole series at once). Only Wickra and kand expose a batch API;
+ta-rs and yata are streaming-only.

-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
+| Indicator        | **★&nbsp;Wickra** | kand |
+|------------------|------------------:|-----:|
+| SMA(20)          | 82                | 42   |
+| EMA(20)          | 159               | 74   |
+| RSI(14)          | **253 ★**         | 274  |
+| MACD(12, 26, 9)  | 681               | 283  |
+| Bollinger(20, 2) | **445 ★**         | 462  |
+| ATR(14)          | 175               | 173  |

-| Indicator | **★&nbsp;Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
+ta-rs is the per-indicator speed champion on almost every row — it returns a
+bare `f64` with no warmup state and no input validation, trading away the
+`None`-warmup and NaN-safety semantics Wickra keeps. Against kand, Wickra wins
+streaming RSI, Bollinger and ATR (and batch RSI + Bollinger); Bollinger is the
+one row where Wickra is the outright fastest of all four. The leaner crates
+still win the pure recurrences (EMA, MACD) and SMA. yata exposes only SMA/EMA as
+raw-value methods, so its other rows are omitted rather than faked.

-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
+### 2. Python vs the Python TA ecosystem — batch
+
+Full pass over a 20 000-bar series, µs/op (lower = faster). **★** per row.
+
+| Indicator        | **★&nbsp;Wickra** | finta               | TA-Lib | tulipy |
+|------------------|------------------:|---------------------|--------|--------|
+| SMA(20)          | **59.6 ★**        | 354.2 (5.9× slower) | ⧗      | ⧗      |
+| EMA(20)          | **88.4 ★**        | 309.3 (3.5× slower) | ⧗      | ⧗      |
+| RSI(14)          | **77.3 ★**        | 1 283 (16.6× slower)| ⧗      | ⧗      |
+| MACD(12, 26, 9)  | **116.4 ★**       | 529.5 (4.6× slower) | ⧗      | ⧗      |
+| Bollinger(20, 2) | **146.0 ★**       | 1 246 (8.5× slower) | ⧗      | ⧗      |
+| ATR(14)          | **135.8 ★**       | 3 812 (28× slower)  | ⧗      | ⧗      |
+
+> ⧗ = published by the CI Linux job. TA-Lib and tulipy ship C extensions that
+> don't build cleanly on every desktop, so their canonical numbers come from the
+> `cross-library-bench` workflow rather than this local table. pandas-ta needs
+> Python ≥ 3.12 and isn't in the 3.11 CI matrix. The script auto-detects
+> whichever peers are installed in your environment.
+
+### 3. Python — streaming (per-tick latency)
+
+Seed 5 000 bars, then feed ticks one at a time. talipp is the only Python peer
+with a true incremental API; batch-only libraries like TA-Lib must recompute the
+entire history on every tick — Wickra updates in O(1).
+
+| Indicator        | **★&nbsp;Wickra (per tick)** | talipp (per tick)       |
+|------------------|------------------------------:|-------------------------|
+| SMA(20)          | **0.067 µs ★**                | 0.63 µs (9.4× slower)   |
+| EMA(20)          | **0.051 µs ★**                | 0.63 µs (12.2× slower)  |
+| RSI(14)          | **0.053 µs ★**                | 1.00 µs (19.1× slower)  |
+| MACD(12, 26, 9)  | **0.071 µs ★**                | 3.64 µs (51.5× slower)  |
+| Bollinger(20, 2) | **0.085 µs ★**                | 4.87 µs (57.2× slower)  |

 Run the suite yourself:

 ```bash
-pip install -e bindings/python[bench]
+cargo bench -p wickra-bench            # Rust core vs kand / ta-rs / yata
+pip install -e bindings/python[bench]  # Python peers
 python -m benchmarks.compare_libraries
 ```

 ## Indicators

-219 streaming-first indicators across sixteen families. Every one passes the
+434 streaming-first indicators across twenty-four families. Every one passes the
 `batch == streaming` equivalence test, reference-value tests, and reset
 semantics tests. Each has a per-indicator deep dive (formula, parameters,
 warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).

 | Family | Indicators |
 |--------|-----------|
-| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA |
-| Momentum Oscillators | RSI (Wilder), Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia |
-| Trend & Directional  | MACD, ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
+| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA, SWMA, GMA, EHMA, Median MA, Adaptive Laguerre, GD, Holt-Winters |
+| Momentum Oscillators | RSI (Wilder), Anchored RSI, Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia, ROC Percentage (ROCP), ROC Ratio (ROCR), ROC Ratio 100 (ROCR100), Disparity Index, Fisher RSI, RSX, Dynamic Momentum Index, Stochastic CCI, RMI, Derivative Oscillator, Elder Ray, Intraday Momentum Index, QQE |
+| Trend & Directional  | MACD, MACD Fixed (MACDFIX), MACD Extended (MACDEXT), ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter, Plus DM, Minus DM, Plus DI, Minus DI, DX, TTM Trend, Trend Strength Index, Qstick, Polarized Fractal Efficiency, Wave PM, Gator Oscillator, Kase Permission Stochastic |
+| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC, TSF Oscillator, MACD Histogram, PPO Histogram |
+| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Volatility Cone |
+| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands, Quartile Bands, Bomar Bands, Median Channel, Projection Bands, Projection Oscillator |
+| Trailing Stops       | Parabolic SAR, Parabolic SAR Extended (SAREXT), SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
 | Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
+| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation, Mid Price, Mid Point, Average Price, Linear Regression Intercept, Time Series Forecast, Rolling Correlation, Rolling Covariance, OU Half-Life, Spread Hurst, Distance SSD, Beta-Neutral Spread, Variance Ratio, Granger Causality, Kalman Hedge Ratio, Spread Bollinger Bands, Spread AR(1) Coefficient |
+| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Hilbert Phasor, Hilbert DC Phase, Hilbert Trend Mode, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
 | Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
 | DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
 | Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
-| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down |
-| Market Profile       | Value Area (POC / VAH / VAL), Initial Balance, Opening Range |
+| Alt-Chart Bars       | Renko (box-size bricks), Kagi (reversal-amount lines), Point & Figure (X/O columns) |
+| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down, Two Crows, Upside Gap Two Crows, Identical Three Crows, Three Line Strike, Three Stars in the South, Abandoned Baby, Advance Block, Belt-hold, Breakaway, Counterattack, Doji Star, Dragonfly Doji, Gravestone Doji, Long-Legged Doji, Rickshaw Man, Evening Doji Star, Morning Doji Star, Gap Side-by-Side White, High-Wave, Hikkake, Modified Hikkake, Homing Pigeon, On-Neck, In-Neck, Thrusting, Separating Lines, Kicking, Kicking by Length, Ladder Bottom, Mat Hold, Matching Low, Long Line, Short Line, Rising Three Methods, Falling Three Methods, Upside Gap Three Methods, Downside Gap Three Methods, Stalled Pattern, Stick Sandwich, Takuri, Closing Marubozu, Opening Marubozu, Tasuki Gap, Unique Three River, Concealing Baby Swallow |
+| Chart Patterns       | Double Top / Bottom, Triple Top / Bottom, Head and Shoulders, Triangle (asc/desc/sym), Wedge (rising/falling), Flag / Pennant, Rectangle / Range, Cup and Handle |
+| Harmonic Patterns    | AB=CD, Gartley, Butterfly, Bat, Crab, Shark, Cypher, Three Drives |
+| Fibonacci            | Fibonacci Retracement, Fibonacci Extension, Fibonacci Projection, Auto-Fibonacci, Golden Pocket, Fibonacci Confluence, Fibonacci Fan, Fibonacci Arcs, Fibonacci Channel, Fibonacci Time Zones |
+| Microstructure       | Order-Book Imbalance (Top-1 / Top-N / Full), Microprice, Quoted Spread, Depth Slope, Signed Volume, Cumulative Volume Delta, Trade Imbalance, Effective Spread, Realized Spread, Kyle's Lambda, Footprint, Order Flow Imbalance, VPIN, Amihud Illiquidity, Roll Measure |
+| Derivatives          | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread |
+| Market Profile       | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range |
+| Market Breadth       | Advance/Decline Line, Advance/Decline Ratio, Advance/Decline Volume Line, McClellan Oscillator, McClellan Summation Index, TRIN / Arms Index, Breadth Thrust, New Highs - New Lows, High-Low Index, Percent Above Moving Average, Up/Down Volume Ratio, Bullish Percent Index, Cumulative Volume Index, Absolute Breadth Index, TICK Index |
 | Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
+| Seasonality & Session | Session VWAP, Session High/Low, Session Range, Average Daily Range, Overnight Gap, Overnight/Intraday Return, Turn-of-Month, Seasonal Z-Score, Time-of-Day Return Profile, Day-of-Week Profile, Intraday Volatility Profile, Volume-by-Time Profile |
+
+Every candlestick pattern emits a signed per-bar value — `+1.0` bullish,
+`−1.0` bearish, `0.0` none — so the family drops straight into a feature matrix
+as one column each. `Doji` is direction-less by default (`+1.0` / `0.0`);
+construct it in signed mode (`Doji::new().signed()`, `Doji(signed=True)`,
+`new Doji(true)`) for a dragonfly / gravestone `±1` reading.

 Adding a new indicator means implementing one trait in Rust; all four bindings
 inherit it automatically.
@@ -230,9 +297,10 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 219 indicators
+│   ├── wickra-core/         core engine + all 434 indicators
 │   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   ├── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   └── wickra-bench/        internal cross-library benchmark harness (not published)
 ├── bindings/
 │   ├── python/              PyO3 + maturin (publishes on PyPI)
 │   ├── node/                napi-rs (publishes on npm)
@@ -246,9 +314,10 @@ wickra/
 └── .github/workflows/       CI and release pipelines
 ```

-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
+Wickra's own regression benchmarks live in `crates/wickra/benches/`; the
+cross-library comparison against kand, ta-rs and yata lives in the internal
+`crates/wickra-bench/` crate. Runnable Rust examples live in the workspace member
+crate at `examples/rust/`. There is no top-level `benches/` directory.

 ## Building everything from source

@@ -256,7 +325,8 @@ in the workspace member crate at `examples/rust/`. There is no top-level
 # Rust core + tests
 cargo test --workspace
 cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+cargo bench -p wickra           # Wickra's own regression benchmarks
+cargo bench -p wickra-bench     # cross-library comparison (kand, ta-rs, yata)

 # Python binding (requires Rust toolchain + maturin)
 cd bindings/python
@@ -314,13 +384,20 @@ shape together before you invest the time.

 ## License

-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
+Licensed under either of

-In plain English: use it, fork it, modify it, redistribute it, file issues, send
-pull requests — all welcome. Personal projects, research, education, non-profits,
-government, hobby trading bots: all fine. The one thing that's not allowed is
-commercial sale of the software or of services built around it. If you want to
-use Wickra commercially, get in touch about a license.
+- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or
+  <http://www.apache.org/licenses/LICENSE-2.0>)
+- MIT license ([LICENSE-MIT](LICENSE-MIT) or <http://opensource.org/licenses/MIT>)
+
+at your option. Use it, fork it, modify it, redistribute it — commercially or
+not — file issues, send pull requests; all welcome.
+
+### Contribution
+
+Unless you explicitly state otherwise, any contribution intentionally submitted
+for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
+dual licensed as above, without any additional terms or conditions.

 ## Disclaimer

@@ -349,3 +426,10 @@ The library is provided **as is**, without warranty of any kind; see
 <p align="center">
  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
 </p>
+
+<p align="center">
+  <a href="https://star-history.com/#wickra-lib/wickra&Date">
+    <img alt="Wickra star history" width="640"
+         src="https://api.star-history.com/svg?repos=wickra-lib/wickra&type=Date&theme=dark">
+  </a>
+</p>
@@ -0,0 +1,36 @@
+# Roadmap
+
+This roadmap describes the project's direction at a high level. It is
+intentionally non-binding: priorities shift with feedback and available time,
+and the authoritative, up-to-date view of planned work is the
+[issue tracker](https://github.com/wickra-lib/wickra/issues). Shipped changes
+are recorded in [`CHANGELOG.md`](CHANGELOG.md).
+
+## Status
+
+Wickra is **pre-1.0**. The public API is largely stable but may still change in
+minor releases; breaking changes are called out in the changelog.
+
+## Themes
+
+- **Indicator coverage.** Continue broadening the indicator catalogue across
+  families (trend, momentum, volatility, volume, statistics, market profile,
+  and more), each with the same streaming/batch parity and test guarantees.
+- **API stabilization toward 1.0.** Settle the public `Indicator` and
+  `BarBuilder` traits and the binding surfaces, then commit to semantic
+  versioning stability for a 1.0 release.
+- **Performance.** Keep per-tick updates O(1) and maintain the benchmark suite;
+  investigate further allocation and cache improvements.
+- **Bindings parity.** Keep the Python, Node.js and WebAssembly bindings in
+  lockstep with the Rust core, including type stubs and platform coverage.
+- **Documentation.** Maintain a deep-dive page per indicator on
+  <https://docs.wickra.org>, plus quickstarts and cookbook material.
+- **Project health.** Maintain test coverage, static and dynamic analysis,
+  signed releases, and supply-chain monitoring.
+
+## How to influence the roadmap
+
+Open or comment on an issue, or start with the
+[feature-request template](.github/ISSUE_TEMPLATE/feature_request.md).
+Well-scoped proposals and pull requests are the most effective way to move an
+item forward.
@@ -2,13 +2,13 @@

 ## Supported versions

-Wickra is pre-1.0. Security fixes are applied to the latest released `0.1.x`
+Wickra is pre-1.0. Security fixes are applied to the latest released `0.5.x`
 version only; please upgrade to the newest release before reporting an issue.

 | Version | Supported |
 | --- | --- |
-| 0.1.x (latest) | :white_check_mark: |
-| older 0.1.x | :x: |
+| 0.5.x (latest) | :white_check_mark: |
+| older 0.5.x | :x: |

 ## Reporting a vulnerability

@@ -41,3 +41,99 @@ PyPI/npm packages, and the build/release workflows in `.github/workflows/`.

 Out of scope: vulnerabilities in third-party dependencies (report those
 upstream; we track them via Dependabot and `cargo-deny`).
+
+## Security assurance case
+
+This is a short, evidence-backed argument for why Wickra can be used safely.
+
+**Security requirements.** Wickra is a computational library: it ingests
+numeric market data and produces indicator values. It stores no user
+credentials, authenticates no external users, and implements no cryptography of
+its own. The requirements are therefore: (1) memory safety and freedom from
+undefined behaviour, (2) robust handling of untrusted/degenerate numeric input
+without panics or unbounded resource use, (3) integrity of the published
+artifacts, and (4) a healthy dependency supply chain.
+
+**How the requirements are met.**
+
+- *Memory safety* — the core and all bindings are written in Rust. The crates
+  forbid or minimise `unsafe`, so the compiler guarantees memory and thread
+  safety for the indicator logic.
+- *Input robustness* — every indicator validates its parameters and rejects
+  non-finite inputs at construction; behaviour on edge cases (flat markets,
+  warmup, reset) is pinned by unit tests, and the public update paths are
+  exercised by coverage-guided fuzzing (`cargo-fuzz` / libFuzzer) in CI.
+- *Static and dynamic analysis* — every push and pull request runs Clippy
+  (`clippy::pedantic`, warnings-as-errors), CodeQL, fuzzing, and the full test
+  suite, with 100% line coverage on the core crate tracked by Codecov.
+- *Artifact integrity* — releases are built in CI, commits and tags are signed,
+  the `main` branch requires signed commits, and release artifacts carry build
+  provenance attestations.
+- *Supply chain* — dependencies are pinned and monitored with Dependabot and
+  audited with `cargo-deny` (license + advisory checks) on every change.
+
+**Residual risk.** The optional `live-binance` feature opens a TLS WebSocket to
+an exchange using the platform TLS library; transport security therefore
+depends on that library, not on Wickra. Wickra is not a trading system and is
+provided "as is" — see the disclaimers in `README.md` and the licenses.
+
+## Secrets management
+
+The project stores **no** secrets or credentials in the version control system.
+Secrets required by automation (publishing tokens, the about-sync PAT) are kept
+exclusively as **GitHub Actions encrypted secrets** and referenced via the
+`secrets.*` context; they are never written to the repository, logs, or build
+artifacts. GitHub **secret scanning with push protection** is enabled to block
+accidental commits of credentials. Secrets follow least privilege (the narrowest
+scope that works) and are rotated when a holder changes or on suspected
+exposure.
+
+## Verifying releases
+
+Released artifacts can be verified for integrity and authenticity:
+
+- **Build provenance.** Release assets carry GitHub build provenance
+  attestations. Verify a downloaded asset with the GitHub CLI:
+  `gh attestation verify <file> --repo wickra-lib/wickra`.
+- **Signed tags.** Each release corresponds to a signed git tag (`vX.Y.Z`);
+  the tag signature identifies the maintainer who authorised the release.
+- **Registry integrity.** Packages are distributed over HTTPS from crates.io,
+  PyPI and npm, which serve package checksums that package managers verify on
+  install.
+
+The release is published only by the maintainer through the tag-triggered
+release workflow, so a verified tag signature establishes the expected
+publisher identity.
+
+## Support timeline and end of support
+
+Wickra is **pre-1.0**: only the **latest released `0.y.z`** version receives
+security fixes. When a newer release is published, the previous version
+**immediately reaches end of support** and will not receive further fixes;
+users should upgrade to the latest release. The supported-versions table above
+is authoritative. After the `1.0.0` release this policy will be revised to
+support a defined window of releases.
+
+## Remediation policy (dependencies and code scanning)
+
+- **Severity threshold.** Vulnerabilities of **medium severity or higher** in
+  the project's own code or its dependencies are remediated promptly and before
+  the next release; lower-severity findings are addressed on a best-effort
+  basis.
+- **Automated enforcement (SCA).** Every change is evaluated by `cargo-deny`
+  (RUSTSEC advisories + license policy) and Dependabot; a known-vulnerable
+  dependency fails CI and **blocks the change** until resolved or explicitly
+  waived with justification.
+- **Automated enforcement (SAST).** Every change is evaluated by CodeQL and
+  Clippy (`-D warnings`); findings **block the change** in CI until fixed.
+- **Pre-release gate.** A release is not cut while an unresolved medium-or-higher
+  SCA/SAST finding is outstanding.
+
+## Vulnerability exploitability (VEX)
+
+Advisories reported by `cargo-deny`/Dependabot for third-party dependencies that
+do **not** affect Wickra (e.g. the vulnerable code path is not reachable, or the
+affected feature is not enabled) are triaged and recorded — with the
+not-affected justification — in the `cargo-deny` configuration (`deny.toml`) and
+the relevant pull request, rather than forcing an unnecessary dependency bump.
+This serves as the project's exploitability (VEX) record.
@@ -0,0 +1,37 @@
+# Support
+
+Thanks for using Wickra! Here is where to get help, depending on what you need.
+
+## Documentation first
+
+Most questions are answered in the documentation:
+
+- **Docs site:** <https://docs.wickra.org> — quickstarts for Rust, Python,
+  Node.js and WebAssembly, a per-indicator reference, warmup periods, the data
+  layer, and an FAQ.
+- **README:** <https://github.com/wickra-lib/wickra#readme> — installation and a
+  quick overview.
+- **API docs (Rust):** <https://docs.rs/wickra>.
+
+## Questions and help
+
+- Ask a question with the
+  [question issue template](.github/ISSUE_TEMPLATE/question.md).
+- Browse [existing issues](https://github.com/wickra-lib/wickra/issues) — your
+  question may already be answered.
+
+## Bugs and feature requests
+
+- **Bugs:** use the bug-report issue template.
+- **Feature requests / new indicators:** use the feature-request template.
+
+## Security issues
+
+Please do **not** report security vulnerabilities through public issues. Follow
+the process in [`SECURITY.md`](SECURITY.md) (private GitHub advisory or email).
+
+## Support expectations
+
+Wickra is maintained by a single maintainer on a best-effort basis. Issues are
+triaged and acknowledged as time allows; there is no commercial support or SLA.
+Clear, reproducible reports get help fastest.
@@ -0,0 +1,54 @@
+# Threat model
+
+This document describes Wickra's attack surface and the threats considered,
+together with their mitigations. It complements the security assurance case in
+[`SECURITY.md`](SECURITY.md). Wickra is a computational technical-analysis
+library (a Rust core with Python, Node.js and WebAssembly bindings), not a
+network service or trading system; the attack surface is correspondingly small.
+
+## Assets
+
+- **Integrity of computed indicator values** — consumers may use them in
+  automated decisions, so silently wrong output is the primary concern.
+- **Availability of the calling process** — a library must not crash or hang
+  its host on malformed input.
+- **Integrity of published artifacts** — the crates, wheels and npm packages
+  users install.
+- **The build and release pipeline** and its secrets (publishing tokens).
+
+## Actors / trust boundaries
+
+- **Library consumer** (trusted) — calls the API with numeric data. Data may
+  originate from untrusted sources (e.g. a market feed), so *input values* are
+  treated as untrusted even though the caller is trusted.
+- **Optional live feed** — with the `live-binance` feature, data crosses a
+  network boundary from an exchange over TLS.
+- **Contributors** (semi-trusted) — propose changes via pull requests.
+- **Supply chain** — upstream dependencies and the CI/CD platform.
+
+## Threats and mitigations
+
+| Threat | Mitigation |
+| --- | --- |
+| Memory-safety exploit (buffer overflow, UAF) via crafted input | Pure safe Rust; `unsafe` is forbidden/minimised, so the compiler precludes these classes. |
+| Denial of service via malformed/degenerate input (NaN, infinities, extreme magnitudes) | Indicators reject non-finite inputs and validate parameters at construction; update paths are exercised by coverage-guided fuzzing and unit tests for edge cases. |
+| Silently incorrect results | 100% line coverage on the core crate; reference-value tests against known-good sources; streaming/batch parity tests. |
+| Integer overflow / panics | `clippy::pedantic` with `-D warnings`; debug assertions and overflow checks enabled in test/fuzz builds. |
+| Adversary-in-the-middle on the optional live feed | Connection uses TLS via the platform library; transport security is delegated to that reviewed implementation. |
+| Compromised dependency (supply chain) | Dependencies pinned (`Cargo.lock`, hash-locked CI requirements), monitored by Dependabot, audited by `cargo-deny` (advisories + licenses) on every change. |
+| Malicious or accidental change to `main` | Branch protection requires signed commits and blocks force-push and deletion; all changes flow through pull requests with required CI; static analysis (CodeQL, Clippy) and fuzzing run on every change. |
+| Compromised CI / leaked secrets | Workflows use least-privilege `permissions:`; secrets live only as encrypted GitHub Actions secrets; secret scanning with push protection is enabled; workflows are linted by `zizmor`. |
+| Tampered release artifact | Releases are built in CI, tags are signed, and assets carry build provenance attestations (verifiable with `gh attestation verify`). |
+
+## Out of scope
+
+- Wickra implements no authentication, authorization or cryptography of its own,
+  stores no user data, and exposes no network listener; those threat classes do
+  not apply.
+- Vulnerabilities in third-party dependencies that do not affect Wickra are
+  tracked as exploitability (VEX) records (see [`SECURITY.md`](SECURITY.md)).
+
+## Maintenance
+
+This threat model is reviewed when the architecture changes materially (for
+example, a new input family, a new network feature, or a new release channel).
@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)

 **Streaming-first technical indicators for Node.js. `npm install wickra` —
 prebuilt native binary, no system dependencies.**
@@ -67,7 +67,5 @@ risk. The library is provided **as is**, without warranty of any kind.

 ## License

-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.
@@ -8,16 +8,25 @@ const test = require('node:test');
 const assert = require('node:assert/strict');
 const wickra = require('..');

+// Bar builders (Renko / Kagi / Point & Figure) implement the `BarBuilder`
+// contract, not `Indicator`: they emit a variable number of completed bars per
+// candle and have no fixed warmup or ready state. They expose update/batch/reset
+// but intentionally not isReady/warmupPeriod, so they are excluded from the
+// Indicator completeness contract below (their interface is covered by the
+// dedicated bar-builder tests).
+const BAR_BUILDERS = new Set(['RenkoBars', 'KagiBars', 'PointAndFigureBars']);
+
 // An "indicator class" is an exported constructor whose prototype carries the
-// streaming `update` method. This excludes `version` (a plain function) and any
-// non-indicator export.
+// streaming `update` method. This excludes `version` (a plain function), the bar
+// builders, and any non-indicator export.
 function indicatorClasses() {
  return Object.keys(wickra).filter((name) => {
    const value = wickra[name];
    return (
      typeof value === 'function' &&
      value.prototype &&
-      typeof value.prototype.update === 'function'
+      typeof value.prototype.update === 'function' &&
+      !BAR_BUILDERS.has(name)
    );
  });
 }
@@ -28,10 +28,50 @@ function num(v) {
 // --- Scalar indicators: update(value) vs batch(prices) ---

 const scalarFactories = {
+  BipowerVariation: () => new wickra.BipowerVariation(20),
+  VolatilityOfVolatility: () => new wickra.VolatilityOfVolatility(20, 20),
+  Garch11: () => new wickra.Garch11(0.000002, 0.1, 0.88),
+  EwmaVolatility: () => new wickra.EwmaVolatility(0.94),
+  PpoHistogram: () => new wickra.PpoHistogram(3, 6, 3),
+  MacdHistogram: () => new wickra.MacdHistogram(3, 6, 3),
+  TsfOscillator: () => new wickra.TsfOscillator(3),
+  WAVE_PM: () => new wickra.WAVE_PM(32, 3),
+  POLARIZED_FRACTAL_EFFICIENCY: () => new wickra.POLARIZED_FRACTAL_EFFICIENCY(10, 5),
+  TREND_STRENGTH_INDEX: () => new wickra.TREND_STRENGTH_INDEX(20),
+  DerivativeOscillator: () => new wickra.DerivativeOscillator(14, 5, 3, 9),
+  RMI: () => new wickra.RMI(14, 5),
+  DynamicMomentumIndex: () => new wickra.DynamicMomentumIndex(14),
+  RSX: () => new wickra.RSX(14),
+  FisherRSI: () => new wickra.FisherRSI(14),
+  DisparityIndex: () => new wickra.DisparityIndex(14),
+  HoltWinters: () => new wickra.HoltWinters(0.2, 0.1),
+  GD: () => new wickra.GD(5, 0.7),
+  AdaptiveLaguerre: () => new wickra.AdaptiveLaguerre(13),
+  MedianMA: () => new wickra.MedianMA(14),
+  EHMA: () => new wickra.EHMA(9),
+  GMA: () => new wickra.GMA(14),
+  SWMA: () => new wickra.SWMA(14),
+  Expectancy: () => new wickra.Expectancy(20),
+  WinRate: () => new wickra.WinRate(20),
+  RegimeLabel: () => new wickra.RegimeLabel(5, 20),
+  JumpIndicator: () => new wickra.JumpIndicator(20, 3.0),
+  TrendLabel: () => new wickra.TrendLabel(10),
+  RollingQuantile: () => new wickra.RollingQuantile(20, 0.5),
+  RollingPercentileRank: () => new wickra.RollingPercentileRank(14),
+  RollingIqr: () => new wickra.RollingIqr(14),
+  RealizedVolatility: () => new wickra.RealizedVolatility(20),
+  LogReturn: () => new wickra.LogReturn(1),
+  TSF: () => new wickra.TSF(14),
+  LINEARREG_INTERCEPT: () => new wickra.LINEARREG_INTERCEPT(14),
+  ROCR100: () => new wickra.ROCR100(10),
+  ROCR: () => new wickra.ROCR(10),
+  ROCP: () => new wickra.ROCP(10),
+  MIDPOINT: () => new wickra.MIDPOINT(14),
  SMA: () => new wickra.SMA(14),
  EMA: () => new wickra.EMA(14),
  WMA: () => new wickra.WMA(14),
  RSI: () => new wickra.RSI(14),
+  AnchoredRSI: () => new wickra.AnchoredRSI(),
  DEMA: () => new wickra.DEMA(10),
  TEMA: () => new wickra.TEMA(10),
  HMA: () => new wickra.HMA(9),
@@ -89,6 +129,8 @@ const scalarFactories = {
  EhlersStochastic: () => new wickra.EhlersStochastic(20),
  EmpiricalModeDecomposition: () => new wickra.EmpiricalModeDecomposition(20, 0.5),
  HilbertDominantCycle: () => new wickra.HilbertDominantCycle(),
+  HT_DCPHASE: () => new wickra.HT_DCPHASE(),
+  HT_TRENDMODE: () => new wickra.HT_TRENDMODE(),
  AdaptiveCycle: () => new wickra.AdaptiveCycle(),
  SineWave: () => new wickra.SineWave(),
  FAMA: () => new wickra.FAMA(0.5, 0.05),
@@ -158,10 +200,17 @@ for (const [name, make] of Object.entries(scalarFactories)) {
 // --- Scalar-output candle indicators: update(...) vs batch(...) ---

 const candleScalar = {
+  MIDPRICE: { make: () => new wickra.MIDPRICE(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  DX: { make: () => new wickra.DX(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  MINUS_DI: { make: () => new wickra.MINUS_DI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  PLUS_DI: { make: () => new wickra.PLUS_DI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  ATR: { make: () => new wickra.ATR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  PLUS_DM: { make: () => new wickra.PLUS_DM(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  MINUS_DM: { make: () => new wickra.MINUS_DM(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  CCI: { make: () => new wickra.CCI(20), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  WilliamsR: { make: () => new wickra.WilliamsR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  PSAR: { make: () => new wickra.PSAR(0.02, 0.02, 0.2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  SAREXT: { make: () => new wickra.SAREXT(0, 0, 0.02, 0.02, 0.2, 0.02, 0.02, 0.2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  MFI: { make: () => new wickra.MFI(14), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
  VWAP: { make: () => new wickra.VWAP(), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
  RollingVWAP: { make: () => new wickra.RollingVWAP(20), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
@@ -169,6 +218,7 @@ const candleScalar = {
  OBV: { make: () => new wickra.OBV(), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
  VWMA: { make: () => new wickra.VWMA(20), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
  RVI: { make: () => new wickra.RVI(10), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  AVGPRICE: { make: () => new wickra.AVGPRICE(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
  Inertia: { make: () => new wickra.Inertia(14, 20), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
  PGO: { make: () => new wickra.PGO(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  SMI: { make: () => new wickra.SMI(5, 3, 3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
@@ -235,6 +285,77 @@ const candleScalar = {
  SpinningTop: { make: () => new wickra.SpinningTop(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
  ThreeInside: { make: () => new wickra.ThreeInside(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
  ThreeOutside: { make: () => new wickra.ThreeOutside(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TwoCrows: { make: () => new wickra.TwoCrows(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  UpsideGapTwoCrows: { make: () => new wickra.UpsideGapTwoCrows(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  IdenticalThreeCrows: { make: () => new wickra.IdenticalThreeCrows(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ThreeLineStrike: { make: () => new wickra.ThreeLineStrike(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ThreeStarsInSouth: { make: () => new wickra.ThreeStarsInSouth(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  AbandonedBaby: { make: () => new wickra.AbandonedBaby(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  AdvanceBlock: { make: () => new wickra.AdvanceBlock(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  BeltHold: { make: () => new wickra.BeltHold(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Breakaway: { make: () => new wickra.Breakaway(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Counterattack: { make: () => new wickra.Counterattack(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DojiStar: { make: () => new wickra.DojiStar(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DragonflyDoji: { make: () => new wickra.DragonflyDoji(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  GravestoneDoji: { make: () => new wickra.GravestoneDoji(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  LongLeggedDoji: { make: () => new wickra.LongLeggedDoji(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  RickshawMan: { make: () => new wickra.RickshawMan(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  EveningDojiStar: { make: () => new wickra.EveningDojiStar(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  MorningDojiStar: { make: () => new wickra.MorningDojiStar(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  GapSideBySideWhite: { make: () => new wickra.GapSideBySideWhite(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HighWave: { make: () => new wickra.HighWave(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Hikkake: { make: () => new wickra.Hikkake(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HikkakeModified: { make: () => new wickra.HikkakeModified(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HomingPigeon: { make: () => new wickra.HomingPigeon(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  OnNeck: { make: () => new wickra.OnNeck(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  InNeck: { make: () => new wickra.InNeck(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Thrusting: { make: () => new wickra.Thrusting(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  SeparatingLines: { make: () => new wickra.SeparatingLines(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Kicking: { make: () => new wickra.Kicking(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  KickingByLength: { make: () => new wickra.KickingByLength(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  LadderBottom: { make: () => new wickra.LadderBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  MatHold: { make: () => new wickra.MatHold(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  MatchingLow: { make: () => new wickra.MatchingLow(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  LongLine: { make: () => new wickra.LongLine(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ShortLine: { make: () => new wickra.ShortLine(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  RisingThreeMethods: { make: () => new wickra.RisingThreeMethods(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  FallingThreeMethods: { make: () => new wickra.FallingThreeMethods(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  UpsideGapThreeMethods: { make: () => new wickra.UpsideGapThreeMethods(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DownsideGapThreeMethods: { make: () => new wickra.DownsideGapThreeMethods(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  StalledPattern: { make: () => new wickra.StalledPattern(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  StickSandwich: { make: () => new wickra.StickSandwich(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Takuri: { make: () => new wickra.Takuri(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ClosingMarubozu: { make: () => new wickra.ClosingMarubozu(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  OpeningMarubozu: { make: () => new wickra.OpeningMarubozu(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TasukiGap: { make: () => new wickra.TasukiGap(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  UniqueThreeRiver: { make: () => new wickra.UniqueThreeRiver(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ConcealingBabySwallow: { make: () => new wickra.ConcealingBabySwallow(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DoubleTopBottom: { make: () => new wickra.DoubleTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TripleTopBottom: { make: () => new wickra.TripleTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HeadAndShoulders: { make: () => new wickra.HeadAndShoulders(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Triangle: { make: () => new wickra.Triangle(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Wedge: { make: () => new wickra.Wedge(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  FlagPennant: { make: () => new wickra.FlagPennant(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  RectangleRange: { make: () => new wickra.RectangleRange(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  CupAndHandle: { make: () => new wickra.CupAndHandle(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Abcd: { make: () => new wickra.Abcd(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Gartley: { make: () => new wickra.Gartley(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Butterfly: { make: () => new wickra.Butterfly(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Bat: { make: () => new wickra.Bat(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Crab: { make: () => new wickra.Crab(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Shark: { make: () => new wickra.Shark(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Cypher: { make: () => new wickra.Cypher(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ThreeDrives: { make: () => new wickra.ThreeDrives(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  CloseVsOpen: { make: () => new wickra.CloseVsOpen(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  BodySizePct: { make: () => new wickra.BodySizePct(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  WickRatio: { make: () => new wickra.WickRatio(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HighLowRange: { make: () => new wickra.HighLowRange(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  StochasticCCI: { make: () => new wickra.StochasticCCI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  IMI: { make: () => new wickra.IMI(14), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TTM_TREND: { make: () => new wickra.TTM_TREND(6), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Qstick: { make: () => new wickra.Qstick(10), step: (ind, i) => ind.update(open[i], close[i]), batch: (ind) => ind.batch(open, close) },
+  VolatilityRatio: { make: () => new wickra.VolatilityRatio(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  ProjectionOscillator: { make: () => new wickra.ProjectionOscillator(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
 };

 for (const [name, d] of Object.entries(candleScalar)) {
@@ -256,6 +377,9 @@ const multi = {
  Alligator: { make: () => new wickra.Alligator(13, 8, 5), fields: ['jaw', 'teeth', 'lips'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
  ZeroLagMACD: { make: () => new wickra.ZeroLagMACD(12, 26, 9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
  MACD: { make: () => new wickra.MACD(12, 26, 9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  HT_PHASOR: { make: () => new wickra.HT_PHASOR(), fields: ['inphase', 'quadrature'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MACDFIX: { make: () => new wickra.MACDFIX(9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MACDEXT: { make: () => new wickra.MACDEXT(12, 0, 26, 0, 9, 0), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
  KST: { make: () => wickra.KST.classic(), fields: ['kst', 'signal'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
  BollingerBands: { make: () => new wickra.BollingerBands(20, 2), fields: ['upper', 'middle', 'lower', 'stddev'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
  Stochastic: { make: () => new wickra.Stochastic(14, 3), fields: ['k', 'd'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
@@ -304,6 +428,25 @@ const multi = {
  // Family 13: Ichimoku & alternative charts
  Ichimoku: { make: () => new wickra.Ichimoku(9, 26, 52, 26), fields: ['tenkan', 'kijun', 'senkouA', 'senkouB', 'chikou'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
  HeikinAshi: { make: () => new wickra.HeikinAshi(), fields: ['open', 'high', 'low', 'close'], step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  FibRetracement: { make: () => new wickra.FibRetracement(), fields: ['level0', 'level236', 'level382', 'level500', 'level618', 'level786', 'level1000'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibExtension: { make: () => new wickra.FibExtension(), fields: ['level1272', 'level1414', 'level1618', 'level2000', 'level2618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibProjection: { make: () => new wickra.FibProjection(), fields: ['level618', 'level1000', 'level1618', 'level2618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  AutoFib: { make: () => new wickra.AutoFib(), fields: ['level0', 'level236', 'level382', 'level500', 'level618', 'level786', 'level1000'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  GoldenPocket: { make: () => new wickra.GoldenPocket(), fields: ['low', 'mid', 'high'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibConfluence: { make: () => new wickra.FibConfluence(), fields: ['price', 'strength'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibFan: { make: () => new wickra.FibFan(), fields: ['fan382', 'fan500', 'fan618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibArcs: { make: () => new wickra.FibArcs(), fields: ['arc382', 'arc500', 'arc618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibChannel: { make: () => new wickra.FibChannel(), fields: ['base', 'level618', 'level1000', 'level1618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibTimeZones: { make: () => new wickra.FibTimeZones(), fields: ['onZone', 'barsToNext'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  ElderRay: { make: () => new wickra.ElderRay(13), fields: ['bullPower', 'bearPower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  QQE: { make: () => new wickra.QQE(14, 5, 4.236), fields: ['rsiMa', 'trailingLine'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  GatorOscillator: { make: () => new wickra.GatorOscillator(13, 8, 5), fields: ['upper', 'lower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  KasePermissionStochastic: { make: () => new wickra.KasePermissionStochastic(9, 3), fields: ['fast', 'slow'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  VolatilityCone: { make: () => new wickra.VolatilityCone(20, 60), fields: ['current', 'min', 'median', 'max', 'percentile'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  QuartileBands: { make: () => new wickra.QuartileBands(4), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  BomarBands: { make: () => new wickra.BomarBands(4, 0.85), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MedianChannel: { make: () => new wickra.MedianChannel(5, 2.0), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  ProjectionBands: { make: () => new wickra.ProjectionBands(3), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
 };

 for (const [name, d] of Object.entries(multi)) {
@@ -464,6 +607,15 @@ const pairFactories = {
  PairwiseBeta: () => new wickra.PairwiseBeta(14),
  PairSpreadZScore: () => new wickra.PairSpreadZScore(14, 14),
  SpearmanCorrelation: () => new wickra.SpearmanCorrelation(14),
+  RollingCorrelation: () => new wickra.RollingCorrelation(20),
+  RollingCovariance: () => new wickra.RollingCovariance(20),
+  OuHalfLife: () => new wickra.OuHalfLife(60),
+  SpreadHurst: () => new wickra.SpreadHurst(60),
+  DistanceSsd: () => new wickra.DistanceSsd(20),
+  BetaNeutralSpread: () => new wickra.BetaNeutralSpread(20),
+  VarianceRatio: () => new wickra.VarianceRatio(60, 2),
+  GrangerCausality: () => new wickra.GrangerCausality(60, 1),
+  SpreadAr1Coefficient: () => new wickra.SpreadAr1Coefficient(40),
 };

 for (const [name, make] of Object.entries(pairFactories)) {
@@ -554,6 +706,47 @@ test('Cointegration batch is flat 3*n with last row matching', () => {
  assert.ok(out[3 * (n - 1) + 2] < -2);
 });

+test('KalmanHedgeRatio converges to a static hedge ratio (object output)', () => {
+  const n = 500;
+  const b = Array.from({ length: n }, (_, t) => 100 + 95 * Math.sin(t * 0.5));
+  const a = b.map((v) => 2 * v + 5);
+  const k = new wickra.KalmanHedgeRatio(1e-2, 1e-3);
+  let last = null;
+  for (let i = 0; i < n; i++) last = k.update(a[i], b[i]);
+  assert.ok(Math.abs(last.hedgeRatio - 2) < 0.05);
+  assert.ok(Math.abs(last.spread) < 0.05);
+});
+
+test('KalmanHedgeRatio batch is flat 3*n with last row matching', () => {
+  const n = 500;
+  const b = Array.from({ length: n }, (_, t) => 100 + 95 * Math.sin(t * 0.5));
+  const a = b.map((v) => 2 * v + 5);
+  const out = new wickra.KalmanHedgeRatio(1e-2, 1e-3).batch(a, b);
+  assert.equal(out.length, 3 * n);
+  assert.ok(Math.abs(out[3 * (n - 1)] - 2) < 0.05);
+  assert.ok(Math.abs(out[3 * (n - 1) + 2]) < 0.05);
+});
+
+test('SpreadBollingerBands bands are ordered (object output)', () => {
+  const n = 60;
+  const b = Array.from({ length: n }, (_, t) => 100 + t);
+  const a = b.map((v, t) => v + 3 * Math.sin(t * 0.4));
+  const bb = new wickra.SpreadBollingerBands(20, 2.0);
+  let last = null;
+  for (let i = 0; i < n; i++) last = bb.update(a[i], b[i]);
+  assert.ok(last.lower <= last.middle && last.middle <= last.upper);
+});
+
+test('SpreadBollingerBands batch is flat 4*n with last row matching', () => {
+  const n = 60;
+  const b = Array.from({ length: n }, (_, t) => 100 + t);
+  const a = b.map((v, t) => v + 3 * Math.sin(t * 0.4));
+  const out = new wickra.SpreadBollingerBands(20, 2.0).batch(a, b);
+  assert.equal(out.length, 4 * n);
+  const base = 4 * (n - 1);
+  assert.ok(out[base + 2] <= out[base] && out[base] <= out[base + 1]);
+});
+
 test('RelativeStrengthAB constant ratio is flat (object output)', () => {
  const rs = new wickra.RelativeStrengthAB(5, 5);
  let last = null;
@@ -896,3 +1089,557 @@ test('ALMA(3, 0.85, 6) reference value on [10, 20, 30]', () => {
  // simple mean of 20.
  assert.ok(out[2] > 20);
 });
+
+test('Doji signed mode encodes dragonfly/gravestone/neutral direction', () => {
+  // Default: direction-less detection flag (+1 doji / 0 otherwise).
+  const flag = new wickra.Doji();
+  assert.equal(flag.isSigned(), false);
+  assert.equal(flag.update(10, 11, 9, 10), 1); // body 0, range 2 -> doji
+  assert.equal(flag.update(10, 12, 10, 12), 0); // body == range -> not a doji
+
+  // Signed: classify a detected doji by its body position within the range.
+  const d = new wickra.Doji(true);
+  assert.equal(d.isSigned(), true);
+  assert.equal(d.update(10, 10.05, 6, 10), 1); // dragonfly -> bullish +1
+  assert.equal(d.update(10, 14, 9.95, 10), -1); // gravestone -> bearish -1
+  assert.equal(d.update(10, 12, 8, 10), 0); // long-legged -> neutral 0
+  assert.equal(d.update(10, 12, 10, 12), 0); // not a doji -> 0
+});
+
+test('order-book indicators reference values', () => {
+  // Top-1: (3 - 1) / (3 + 1) = 0.5.
+  assert.equal(new wickra.OrderBookImbalanceTop1().update([100], [3], [101], [1]), 0.5);
+  // Top-2: bidDepth 3, askDepth 2 -> (3 - 2) / 5 = 0.2.
+  assert.ok(
+    Math.abs(new wickra.OrderBookImbalanceTopN(2).update([100, 99], [2, 1], [101, 102], [1, 1]) - 0.2) < 1e-12,
+  );
+  // Full: bidDepth 1, askDepth 3 -> -0.5.
+  assert.equal(new wickra.OrderBookImbalanceFull().update([100], [1], [101, 102], [2, 1]), -0.5);
+  // Microprice: (100*3 + 101*1) / 4 = 100.25.
+  assert.equal(new wickra.Microprice().update([100], [1], [101], [3]), 100.25);
+  // Quoted spread: 1 / 100.5 * 10000 ≈ 99.5025 bps.
+  assert.ok(Math.abs(new wickra.QuotedSpread().update([100], [1], [101], [1]) - 99.50248756) < 1e-6);
+  // Depth slope: each side distances 1,2 -> cumulative 1,3 -> OLS slope 2.
+  assert.ok(Math.abs(new wickra.DepthSlope().update([99, 98], [1, 2], [101, 102], [1, 2]) - 2.0) < 1e-9);
+  // Single level per side -> no slope -> 0.
+  assert.equal(new wickra.DepthSlope().update([100], [1], [101], [1]), 0.0);
+});
+
+test('order-book streaming update matches batch', () => {
+  const snaps = Array.from({ length: 30 }, (_, i) => ({
+    bidPx: [100, 99],
+    bidSz: [1 + (i % 5), 1],
+    askPx: [101, 102],
+    askSz: [1 + ((i + 1) % 3), 1],
+  }));
+  const batch = new wickra.Microprice().batch(snaps);
+  const streamer = new wickra.Microprice();
+  assert.equal(batch.length, snaps.length);
+  for (let i = 0; i < snaps.length; i++) {
+    const s = streamer.update(snaps[i].bidPx, snaps[i].bidSz, snaps[i].askPx, snaps[i].askSz);
+    assert.ok(Math.abs(s - batch[i]) < 1e-12, `mismatch at ${i}: ${s} vs ${batch[i]}`);
+  }
+});
+
+test('order-book TopN rejects zero levels', () => {
+  assert.throws(() => new wickra.OrderBookImbalanceTopN(0));
+});
+
+test('order-book update rejects a crossed book', () => {
+  assert.throws(() => new wickra.QuotedSpread().update([102], [1], [101], [1]));
+});
+
+test('trade-flow indicators reference values', () => {
+  assert.equal(new wickra.SignedVolume().update(100, 2, true), 2);
+  assert.equal(new wickra.SignedVolume().update(100, 3, false), -3);
+  const cvd = new wickra.CumulativeVolumeDelta();
+  assert.equal(cvd.update(100, 5, true), 5);
+  assert.equal(cvd.update(100, 2, false), 3);
+  const ti = new wickra.TradeImbalance(2);
+  assert.equal(ti.update(100, 3, true), null); // warming up
+  assert.equal(ti.update(100, 1, false), 0.5); // (3 - 1) / 4
+});
+
+test('trade-flow streaming update matches batch', () => {
+  const n = 30;
+  const price = Array.from({ length: n }, () => 100);
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 4));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 3 !== 0);
+  const batch = new wickra.CumulativeVolumeDelta().batch(price, size, isBuy);
+  const streamer = new wickra.CumulativeVolumeDelta();
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    const s = streamer.update(price[i], size[i], isBuy[i]);
+    assert.ok(Math.abs(s - batch[i]) < 1e-12, `mismatch at ${i}: ${s} vs ${batch[i]}`);
+  }
+});
+
+test('trade-flow rejects bad input', () => {
+  assert.throws(() => new wickra.TradeImbalance(0));
+  assert.throws(() => new wickra.SignedVolume().update(100, -1, true));
+});
+
+test('order-flow imbalance reference + streaming matches batch', () => {
+  // Rising bid (px up, size 6) with an unchanged ask -> +6 flow.
+  const ofi = new wickra.OrderFlowImbalance(1);
+  assert.equal(ofi.update([100], [5], [101], [4]), null); // seeds the reference
+  assert.ok(Math.abs(ofi.update([100.5], [6], [101], [4]) - 6.0) < 1e-12);
+  const snaps = Array.from({ length: 30 }, (_, i) => ({
+    bidPx: [100 + Math.sin(i * 0.3)],
+    bidSz: [5 + Math.abs(Math.cos(i * 0.5))],
+    askPx: [101 + Math.sin(i * 0.3)],
+    askSz: [4 + Math.abs(Math.sin(i * 0.4))],
+  }));
+  const batch = new wickra.OrderFlowImbalance(10).batch(snaps);
+  const streamer = new wickra.OrderFlowImbalance(10);
+  assert.equal(batch.length, snaps.length);
+  for (let i = 0; i < snaps.length; i++) {
+    const s = streamer.update(snaps[i].bidPx, snaps[i].bidSz, snaps[i].askPx, snaps[i].askSz);
+    assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
+  }
+});
+
+test('vpin / amihud / roll reference + streaming matches batch', () => {
+  // VPIN: two pure-buy buckets of size 10 -> imbalance == size -> 1.
+  const v = new wickra.Vpin(10, 2);
+  let last;
+  for (let i = 0; i < 4; i++) last = v.update(100, 5, true);
+  assert.equal(last, 1.0);
+  // Amihud(1): |ln(101/100)| / (101 * 10).
+  const a = new wickra.AmihudIlliquidity(1);
+  assert.equal(a.update(100, 10, true), null);
+  assert.ok(Math.abs(a.update(101, 10, true) - Math.abs(Math.log(101 / 100)) / (101 * 10)) < 1e-15);
+  // Roll(6): a clean bid-ask bounce of ±1 implies a spread of 2.
+  const r = new wickra.RollMeasure(6);
+  let roll = null;
+  for (let i = 0; i < 20; i++) roll = r.update(i % 2 === 0 ? 100 : 101, 1, true);
+  assert.ok(Math.abs(roll - 2.0) < 1e-12);
+  // Streaming-vs-batch for the three trade-input indicators.
+  const n = 40;
+  const price = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.25) * 4);
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 5));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 2 === 0);
+  for (const make of [() => new wickra.Vpin(8, 5), () => new wickra.AmihudIlliquidity(14), () => new wickra.RollMeasure(14)]) {
+    const batch = make().batch(price, size, isBuy);
+    const streamer = make();
+    assert.equal(batch.length, n);
+    for (let i = 0; i < n; i++) {
+      const s = streamer.update(price[i], size[i], isBuy[i]);
+      assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
+    }
+  }
+});
+
+test('price-impact indicators reference values', () => {
+  // Buy at 100.05 vs mid 100.0: 2 * (100.05 - 100) / 100 * 10000 = 10 bps.
+  assert.ok(Math.abs(new wickra.EffectiveSpread().update(100.05, 1, true, 100.0) - 10.0) < 1e-9);
+  // Sell at 99.95 vs mid 100.0: 2 * -1 * (99.95 - 100) / 100 * 10000 = 10 bps.
+  assert.ok(Math.abs(new wickra.EffectiveSpread().update(99.95, 1, false, 100.0) - 10.0) < 1e-9);
+  // A buy filled below the mid is price improvement -> negative.
+  assert.ok(new wickra.EffectiveSpread().update(99.95, 1, true, 100.0) < 0.0);
+});
+
+test('price-impact streaming update matches batch', () => {
+  const n = 30;
+  const mid = Array.from({ length: n }, (_, i) => 100 + 0.25 * Math.sin(i * 0.5));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 3 !== 0);
+  const price = Array.from({ length: n }, (_, i) => mid[i] + (isBuy[i] ? 0.03 : -0.03));
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 4));
+  const batch = new wickra.EffectiveSpread().batch(price, size, isBuy, mid);
+  const streamer = new wickra.EffectiveSpread();
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    const s = streamer.update(price[i], size[i], isBuy[i], mid[i]);
+    assert.ok(Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}: ${s} vs ${batch[i]}`);
+  }
+});
+
+test('realized spread resolves against the future mid', () => {
+  const rs = new wickra.RealizedSpread(1);
+  assert.equal(rs.update(100.10, 1, true, 100.0), null); // buffered
+  // 2 * (+1) * (100.10 - 100.20) / 100.0 * 10000 = -20 bps.
+  assert.ok(Math.abs(rs.update(99.90, 1, false, 100.20) - -20.0) < 1e-9);
+});
+
+test('realized spread streaming update matches batch', () => {
+  const n = 30;
+  const mid = Array.from({ length: n }, (_, i) => 100 + 0.25 * Math.sin(i * 0.5));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 3 !== 0);
+  const price = Array.from({ length: n }, (_, i) => mid[i] + (isBuy[i] ? 0.03 : -0.03));
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 4));
+  const batch = new wickra.RealizedSpread(4).batch(price, size, isBuy, mid);
+  const streamer = new wickra.RealizedSpread(4);
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    const s = streamer.update(price[i], size[i], isBuy[i], mid[i]);
+    const got = s === null ? NaN : s;
+    assert.ok(
+      (Number.isNaN(got) && Number.isNaN(batch[i])) || Math.abs(got - batch[i]) < 1e-9,
+      `mismatch at ${i}: ${got} vs ${batch[i]}`,
+    );
+  }
+});
+
+test("kyle's lambda recovers a constant price-impact slope", () => {
+  // Each trade moves the mid by exactly 0.5 per unit of signed volume.
+  const impact = 0.5;
+  let mid = 100;
+  const price = [];
+  const size = [];
+  const isBuy = [];
+  const mids = [];
+  for (let i = 0; i < 20; i++) {
+    const buy = i % 2 === 0;
+    const sz = 1 + (i % 3);
+    const signed = buy ? sz : -sz;
+    mid += impact * signed;
+    price.push(mid);
+    size.push(sz);
+    isBuy.push(buy);
+    mids.push(mid);
+  }
+  const out = new wickra.KylesLambda(6).batch(price, size, isBuy, mids);
+  assert.ok(Math.abs(out[out.length - 1] - 0.5) < 1e-9);
+});
+
+test('price-impact rejects bad input', () => {
+  assert.throws(() => new wickra.EffectiveSpread().update(100, 1, true, 0));
+  assert.throws(() => new wickra.RealizedSpread(0));
+  assert.throws(() => new wickra.KylesLambda(1));
+});
+
+test('footprint buckets buy and sell volume per price level', () => {
+  const fp = new wickra.Footprint(1.0);
+  fp.update(100.2, 2, true); // bucket 100 -> ask 2
+  fp.update(100.7, 3, false); // bucket 101 -> bid 3
+  const out = fp.update(100.1, 1, true); // bucket 100 -> ask 3
+  assert.equal(out.length, 2);
+  assert.deepEqual(
+    { price: out[0].price, bidVol: out[0].bidVol, askVol: out[0].askVol },
+    { price: 100.0, bidVol: 0.0, askVol: 3.0 },
+  );
+  assert.deepEqual(
+    { price: out[1].price, bidVol: out[1].bidVol, askVol: out[1].askVol },
+    { price: 101.0, bidVol: 3.0, askVol: 0.0 },
+  );
+});
+
+test('footprint streaming update matches batch and rejects bad tick', () => {
+  const n = 12;
+  const price = Array.from({ length: n }, (_, i) => 100 + (i % 5) * 0.3);
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 3));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 2 === 0);
+  const batch = new wickra.Footprint(1.0).batch(price, size, isBuy);
+  const streamer = new wickra.Footprint(1.0);
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    const s = streamer.update(price[i], size[i], isBuy[i]);
+    assert.deepEqual(s, batch[i], `mismatch at ${i}`);
+  }
+  assert.throws(() => new wickra.Footprint(0));
+});
+
+test('derivatives indicators reference values', () => {
+  // Funding rate passes through (and may be negative).
+  assert.equal(new wickra.FundingRate().update(0.0001), 0.0001);
+  assert.equal(new wickra.FundingRate().update(-0.0003), -0.0003);
+  // Rolling mean: window [0.001, 0.003] -> 0.002.
+  const frm = new wickra.FundingRateMean(2);
+  assert.equal(frm.update(0.001), null); // warming up
+  assert.ok(Math.abs(frm.update(0.003) - 0.002) < 1e-12);
+  // Z-score: window [0.001, 0.003] -> +1.
+  const z = new wickra.FundingRateZScore(2);
+  assert.equal(z.update(0.001), null); // warming up
+  assert.ok(Math.abs(z.update(0.003) - 1.0) < 1e-9);
+  // Basis: mark 100.5 vs index 100.0 -> 0.005.
+  assert.ok(Math.abs(new wickra.FundingBasis().update(100.5, 100.0) - 0.005) < 1e-12);
+  // OI delta: seeds then emits the change.
+  const oid = new wickra.OpenInterestDelta();
+  assert.equal(oid.update(1000), null);
+  assert.equal(oid.update(1250), 250);
+  assert.equal(oid.update(1100), -150);
+});
+
+test('derivatives streaming update matches batch', () => {
+  const n = 30;
+  const rate = Array.from({ length: n }, (_, i) => 0.0001 * Math.sin(i * 0.3));
+  const batch = new wickra.FundingRateMean(5).batch(rate);
+  const streamer = new wickra.FundingRateMean(5);
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    const s = streamer.update(rate[i]);
+    assert.ok(
+      (s === null && Number.isNaN(batch[i])) || Math.abs(s - batch[i]) < 1e-12,
+      `mismatch at ${i}: ${s} vs ${batch[i]}`,
+    );
+  }
+});
+
+test('derivatives reject bad input', () => {
+  assert.throws(() => new wickra.FundingRateMean(0));
+  assert.throws(() => new wickra.FundingRateZScore(0));
+  assert.throws(() => new wickra.FundingBasis().update(100, 0));
+});
+
+test('market breadth: AdvanceDecline reference values', () => {
+  // A breadth tick is the universe as parallel arrays; the sign of `change`
+  // classifies each symbol as advancing / declining / unchanged.
+  const change = [
+    [1.0, 0.5, 2.0, -1.0], // 3 up, 1 down -> net +2
+    [-1.0, -0.5, -2.0, 1.0], // 1 up, 3 down -> net -2
+    [0.0, 0.0, 1.0, -1.0], // 1 up, 1 down -> net 0
+  ];
+  const volume = change.map((row) => row.map(() => 10.0));
+  const flags = change.map((row) => row.map(() => false));
+
+  const ad = new wickra.AdvanceDecline();
+  // Cumulative line: +2 -> 0 -> 0.
+  assert.equal(ad.update(change[0], volume[0], flags[0], flags[0]), 2.0);
+  assert.equal(ad.update(change[1], volume[1], flags[1], flags[1]), 0.0);
+  assert.equal(ad.update(change[2], volume[2], flags[2], flags[2]), 0.0);
+
+  // batch matches streaming.
+  const batch = new wickra.AdvanceDecline().batch(change, volume, flags, flags);
+  assert.deepEqual(Array.from(batch), [2.0, 0.0, 0.0]);
+});
+
+test('market breadth: AdvanceDecline rejects ragged universe', () => {
+  assert.throws(() =>
+    new wickra.AdvanceDecline().update(
+      [1.0, -1.0],
+      [10.0],
+      [false, false],
+      [false, false],
+    ),
+  );
+});
+
+test('market breadth: 14 indicators reference values + batch parity', () => {
+  const flags4 = [false, false, false, false];
+
+  // Advance/Decline Ratio: 3/1 = 3 ; 0 advancers -> 0.
+  const adr = new wickra.AdvanceDeclineRatio();
+  assert.equal(adr.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4), 3.0);
+  assert.equal(adr.update([-1, -1, -1, -1], [10, 10, 10, 10], flags4, flags4), 0.0);
+  assert.deepEqual(
+    Array.from(
+      new wickra.AdvanceDeclineRatio().batch(
+        [[1, 1, 1, -1], [-1, -1, -1, -1]],
+        [[10, 10, 10, 10], [10, 10, 10, 10]],
+        [flags4, flags4],
+        [flags4, flags4],
+      ),
+    ),
+    [3.0, 0.0],
+  );
+
+  // AD Volume Line: cumulative net advancing volume.
+  const adv = new wickra.AdVolumeLine();
+  assert.equal(adv.update([1, -1], [150, 50], [false, false], [false, false]), 100.0);
+  assert.equal(adv.update([1, -1], [60, 60], [false, false], [false, false]), 100.0);
+
+  // McClellan Oscillator + Summation: seed 0, then -50.
+  const osc = new wickra.McClellanOscillator();
+  assert.ok(Math.abs(osc.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4)) < 1e-9);
+  assert.ok(Math.abs(osc.update([-1, -1, -1, 1], [10, 10, 10, 10], flags4, flags4) - -50.0) < 1e-9);
+  const msi = new wickra.McClellanSummationIndex();
+  assert.ok(Math.abs(msi.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4)) < 1e-9);
+  assert.ok(Math.abs(msi.update([-1, -1, -1, 1], [10, 10, 10, 10], flags4, flags4) - -50.0) < 1e-9);
+
+  // TRIN: balanced breadth -> 1.
+  assert.ok(
+    Math.abs(new wickra.Trin().update([1, 1, 1, -1], [50, 50, 50, 50], flags4, flags4) - 1.0) < 1e-9,
+  );
+
+  // Breadth Thrust(2): warmup null, then SMA(2) of [0.8, 0.6] = 0.7.
+  const bt = new wickra.BreadthThrust(2);
+  const up10 = Array(10).fill(false);
+  assert.equal(bt.update([...Array(8).fill(1), -1, -1], Array(10).fill(10), up10, up10), null);
+  assert.ok(
+    Math.abs(bt.update([...Array(6).fill(1), -1, -1, -1, -1], Array(10).fill(10), up10, up10) - 0.7) < 1e-9,
+  );
+
+  // New Highs - New Lows: 2 - 1 = 1.
+  assert.equal(
+    new wickra.NewHighsNewLows().update([1, 1, -1], [10, 10, 10], [true, true, false], [false, false, true]),
+    1.0,
+  );
+
+  // High-Low Index(2): warmup null, then SMA(2) of [80, 60] = 70.
+  const hli = new wickra.HighLowIndex(2);
+  assert.equal(
+    hli.update(Array(10).fill(1), Array(10).fill(10), [...Array(8).fill(true), false, false], [...Array(8).fill(false), true, true]),
+    null,
+  );
+  assert.ok(
+    Math.abs(
+      hli.update(Array(10).fill(1), Array(10).fill(10), [...Array(6).fill(true), false, false, false, false], [...Array(6).fill(false), true, true, true, true]) - 70.0,
+    ) < 1e-9,
+  );
+
+  // Percent Above MA: 3/4 -> 75 (5-array update with aboveMa).
+  assert.equal(
+    new wickra.PercentAboveMa().update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4, [true, true, true, false]),
+    75.0,
+  );
+
+  // Up/Down Volume Ratio: 150/50 = 3.
+  assert.equal(
+    new wickra.UpDownVolumeRatio().update([1, -1], [150, 50], [false, false], [false, false]),
+    3.0,
+  );
+
+  // Bullish Percent Index: 2/4 -> 50 (5-array update with onBuySignal).
+  assert.equal(
+    new wickra.BullishPercentIndex().update([1, 1, -1, -1], [10, 10, 10, 10], flags4, flags4, [true, true, false, false]),
+    50.0,
+  );
+
+  // Cumulative Volume Index: (100/200) -> 0.5.
+  assert.ok(
+    Math.abs(new wickra.CumulativeVolumeIndex().update([1, -1], [150, 50], [false, false], [false, false]) - 0.5) < 1e-9,
+  );
+
+  // Absolute Breadth Index: |2 - 3| = 1.
+  assert.equal(
+    new wickra.AbsoluteBreadthIndex().update([1, 1, -1, -1, -1], Array(5).fill(10), Array(5).fill(false), Array(5).fill(false)),
+    1.0,
+  );
+
+  // TICK Index: 2 - 3 = -1.
+  assert.equal(
+    new wickra.TickIndex().update([1, 1, -1, -1, -1], Array(5).fill(10), Array(5).fill(false), Array(5).fill(false)),
+    -1.0,
+  );
+});
+
+test('market breadth: rejects ragged universe', () => {
+  assert.throws(() => new wickra.Trin().update([1, -1], [10], [false, false], [false, false]));
+  assert.throws(() =>
+    new wickra.PercentAboveMa().update([1, -1], [10, 10], [false, false], [false, false], [true]),
+  );
+});
+
+test('OI / flow / liquidation indicators reference values', () => {
+  // OI +10% while price flat -> divergence +0.1.
+  const div = new wickra.OIPriceDivergence(1);
+  assert.equal(div.update(1000, 100), null); // warming up
+  assert.ok(Math.abs(div.update(1100, 100) - 0.1) < 1e-12);
+  // OI-weighted: (100·10 + 110·30) / 40 = 107.5.
+  const oiw = new wickra.OIWeighted();
+  assert.equal(oiw.update(100, 10), 100);
+  assert.ok(Math.abs(oiw.update(110, 30) - 107.5) < 1e-12);
+  // Long/short ratio.
+  assert.ok(Math.abs(new wickra.LongShortRatio().update(600, 400) - 1.5) < 1e-12);
+  assert.equal(new wickra.LongShortRatio().update(600, 0), 0);
+  // Taker buy/sell ratio.
+  assert.ok(Math.abs(new wickra.TakerBuySellRatio().update(60, 40) - 1.5) < 1e-12);
+  assert.equal(new wickra.TakerBuySellRatio().update(60, 0), 0);
+  // Liquidation features object.
+  const liq = new wickra.LiquidationFeatures().update(30, 10);
+  assert.equal(liq.net, 20);
+  assert.equal(liq.total, 40);
+  assert.equal(liq.imbalance, 0.5);
+});
+
+test('liquidation features batch is flat n*5', () => {
+  const longLiq = [10, 0, 30];
+  const shortLiq = [5, 20, 0];
+  const batch = new wickra.LiquidationFeatures().batch(longLiq, shortLiq);
+  assert.equal(batch.length, 15);
+  // Row 0: long 10, short 5, net 5, total 15.
+  assert.equal(batch[0], 10);
+  assert.equal(batch[1], 5);
+  assert.equal(batch[2], 5);
+  assert.equal(batch[3], 15);
+});
+
+test('OI flow rejects bad input', () => {
+  assert.throws(() => new wickra.OIPriceDivergence(0));
+  assert.throws(() => new wickra.OIWeighted().update(0, 100));
+});
+
+test('basis & calendar-spread reference values', () => {
+  // futures 102 vs index 100 -> 0.02 contango.
+  assert.ok(Math.abs(new wickra.TermStructureBasis().update(102, 100) - 0.02) < 1e-12);
+  assert.ok(Math.abs(new wickra.TermStructureBasis().update(98, 100) + 0.02) < 1e-12);
+  // futures 101 vs perpetual mark 100 -> 0.01.
+  assert.ok(Math.abs(new wickra.CalendarSpread().update(101, 100) - 0.01) < 1e-12);
+});
+
+test('basis streaming update matches batch', () => {
+  const n = 20;
+  const index = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.2));
+  const futures = Array.from({ length: n }, (_, i) => index[i] + 0.5);
+  const batch = new wickra.TermStructureBasis().batch(futures, index);
+  const streamer = new wickra.TermStructureBasis();
+  assert.equal(batch.length, n);
+  for (let i = 0; i < n; i++) {
+    assert.ok(Math.abs(streamer.update(futures[i], index[i]) - batch[i]) < 1e-12);
+  }
+});
+
+test('basis rejects bad input', () => {
+  assert.throws(() => new wickra.TermStructureBasis().update(100, 0));
+  assert.throws(() => new wickra.CalendarSpread().update(100, 0));
+});
+
+test('VolumeProfile exposes the full histogram', () => {
+  // bar0 single-print at 10 vol 100; bar1 spans 10..14 vol 80 over 4 bins.
+  const vp = new wickra.VolumeProfile(2, 4);
+  assert.equal(vp.update(10, 10, 100), null);
+  const out = vp.update(14, 10, 80);
+  assert.ok(out !== null);
+  assert.ok(Math.abs(out.priceLow - 10) < 1e-9);
+  assert.ok(Math.abs(out.priceHigh - 14) < 1e-9);
+  assert.deepEqual(out.bins.length, 4);
+  assert.ok(Math.abs(out.bins[0] - 120) < 1e-9);
+  for (let i = 1; i < 4; i++) {
+    assert.ok(Math.abs(out.bins[i] - 20) < 1e-9);
+  }
+});
+
+test('TpoProfile counts time at price, volume-agnostic', () => {
+  // bar0 spans 10..14 (+1 each bin); bar1 spans 11..12 (+1 bins 1,2).
+  const tpo = new wickra.TpoProfile(2, 4);
+  assert.equal(tpo.update(14, 10), null);
+  const out = tpo.update(12, 11);
+  assert.ok(out !== null);
+  assert.ok(Math.abs(out.priceLow - 10) < 1e-9);
+  assert.ok(Math.abs(out.priceHigh - 14) < 1e-9);
+  assert.deepEqual(out.counts, [1, 2, 2, 1]);
+});
+
+test('RenkoBars prints aligned bricks and reverses on two boxes', () => {
+  const r = new wickra.RenkoBars(1.0);
+  assert.deepEqual(r.update(10), []); // seed
+  const up = r.update(13);
+  assert.equal(up.length, 3);
+  assert.ok(Math.abs(up[0].open - 10) < 1e-9 && Math.abs(up[0].close - 11) < 1e-9);
+  assert.ok(up.every((b) => b.direction === 1));
+  const down = r.update(10);
+  assert.equal(down.length, 2);
+  assert.ok(down.every((b) => b.direction === -1));
+});
+
+test('KagiBars closes a segment on a reversal', () => {
+  const k = new wickra.KagiBars(2.0);
+  k.update(10);
+  k.update(11);
+  k.update(15);
+  const seg = k.update(12);
+  assert.equal(seg.length, 1);
+  assert.equal(seg[0].direction, 1);
+  assert.ok(Math.abs(seg[0].start - 10) < 1e-9 && Math.abs(seg[0].end - 15) < 1e-9);
+});
+
+test('PointAndFigureBars closes a column on a 3-box reversal', () => {
+  const pnf = new wickra.PointAndFigureBars(1.0, 3);
+  pnf.update(10);
+  pnf.update(13);
+  pnf.update(15);
+  const col = pnf.update(12);
+  assert.equal(col.length, 1);
+  assert.equal(col[0].direction, 1);
+  assert.ok(Math.abs(col[0].high - 15) < 1e-9 && Math.abs(col[0].low - 10) < 1e-9);
+});
@@ -0,0 +1,96 @@
+// Streaming-vs-batch equivalence and reference values for the Seasonality &
+// Session family. These indicators consume the full candle (open, high, low,
+// close, volume, timestamp), so they have a dedicated suite.
+
+const test = require('node:test');
+const assert = require('node:assert/strict');
+const wickra = require('..');
+
+const HOUR = 3_600_000;
+const N = 240;
+const close = Array.from({ length: N }, (_, i) => 100 + Math.sin(i * 0.3) * 5 + Math.cos(i * 0.1) * 3);
+const open = close.map((c, i) => c + Math.sin(i * 0.5) * 0.5);
+const high = close.map((c, i) => Math.max(open[i], c) + 1);
+const low = close.map((c, i) => Math.min(open[i], c) - 1);
+const volume = Array.from({ length: N }, (_, i) => 1000 + (i % 24) * 50);
+const ts = Array.from({ length: N }, (_, i) => i * HOUR);
+
+function eq(a, b) {
+  if (Number.isNaN(a)) return Number.isNaN(b);
+  return Math.abs(a - b) < 1e-9;
+}
+
+function streamScalar(ind, i) {
+  const v = ind.update(open[i], high[i], low[i], close[i], volume[i], ts[i]);
+  return v === null || v === undefined ? NaN : v;
+}
+
+function checkScalar(name, make) {
+  test(`${name} streaming equals batch`, () => {
+    const a = make();
+    const b = make();
+    const batch = b.batch(open, high, low, close, volume, ts);
+    for (let i = 0; i < N; i += 1) {
+      assert.ok(eq(streamScalar(a, i), batch[i]), `${name} row ${i}`);
+    }
+  });
+}
+
+function checkMatrix(name, make, k, pick) {
+  test(`${name} streaming equals batch`, () => {
+    const a = make();
+    const b = make();
+    const batch = b.batch(open, high, low, close, volume, ts);
+    for (let i = 0; i < N; i += 1) {
+      const out = a.update(open[i], high[i], low[i], close[i], volume[i], ts[i]);
+      for (let j = 0; j < k; j += 1) {
+        const s = out === null || out === undefined ? NaN : pick(out, j);
+        assert.ok(eq(s, batch[i * k + j]), `${name} row ${i} col ${j}`);
+      }
+    }
+  });
+}
+
+checkScalar('SessionVwap', () => new wickra.SessionVwap(0));
+checkScalar('OvernightGap', () => new wickra.OvernightGap(0));
+checkScalar('SeasonalZScore', () => new wickra.SeasonalZScore(0));
+checkScalar('AverageDailyRange', () => new wickra.AverageDailyRange(3, 0));
+checkScalar('TurnOfMonth', () => new wickra.TurnOfMonth(3, 1, 0));
+
+checkMatrix('SessionHighLow', () => new wickra.SessionHighLow(0), 2, (o, j) => (j === 0 ? o.high : o.low));
+checkMatrix('SessionRange', () => new wickra.SessionRange(0), 3, (o, j) => [o.asia, o.eu, o.us][j]);
+checkMatrix(
+  'OvernightIntradayReturn',
+  () => new wickra.OvernightIntradayReturn(0),
+  2,
+  (o, j) => (j === 0 ? o.overnight : o.intraday),
+);
+checkMatrix('TimeOfDayReturnProfile', () => new wickra.TimeOfDayReturnProfile(24, 0), 24, (o, j) => o[j]);
+checkMatrix('IntradayVolatilityProfile', () => new wickra.IntradayVolatilityProfile(12, 0), 12, (o, j) => o[j]);
+checkMatrix('VolumeByTimeProfile', () => new wickra.VolumeByTimeProfile(24, 0), 24, (o, j) => o[j]);
+checkMatrix('DayOfWeekProfile', () => new wickra.DayOfWeekProfile(0), 7, (o, j) => o[j]);
+
+test('SessionVwap reference value', () => {
+  const vwap = new wickra.SessionVwap(0);
+  assert.ok(eq(vwap.update(100, 100, 100, 100, 10, 0), 100));
+  assert.ok(eq(vwap.update(110, 110, 110, 110, 30, HOUR), 107.5));
+  assert.ok(eq(vwap.update(200, 200, 200, 200, 5, 24 * HOUR), 200));
+});
+
+test('OvernightGap reference value', () => {
+  const gap = new wickra.OvernightGap(0);
+  assert.equal(gap.update(99, 101, 98, 100, 1, 0), null);
+  assert.ok(eq(gap.update(105, 106, 104, 105.5, 1, 24 * HOUR), 0.05));
+});
+
+test('SessionHighLow reference object', () => {
+  const shl = new wickra.SessionHighLow(0);
+  shl.update(100, 105, 99, 101, 1, 0);
+  const out = shl.update(101, 108, 100, 107, 1, HOUR);
+  assert.ok(eq(out.high, 108));
+  assert.ok(eq(out.low, 99));
+});
+
+test('AverageDailyRange rejects zero period', () => {
+  assert.throws(() => new wickra.AverageDailyRange(0, 0));
+});
@@ -1,12 +1,12 @@
 {
  "name": "wickra-darwin-arm64",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.darwin-arm64.node",
  "files": [
    "wickra.darwin-arm64.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,12 +1,12 @@
 {
  "name": "wickra-darwin-x64",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.darwin-x64.node",
  "files": [
    "wickra.darwin-x64.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,12 +1,12 @@
 {
  "name": "wickra-linux-arm64-gnu",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.linux-arm64-gnu.node",
  "files": [
    "wickra.linux-arm64-gnu.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,12 +1,12 @@
 {
  "name": "wickra-linux-x64-gnu",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.linux-x64-gnu.node",
  "files": [
    "wickra.linux-x64-gnu.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,12 +1,12 @@
 {
  "name": "wickra-win32-arm64-msvc",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.win32-arm64-msvc.node",
  "files": [
    "wickra.win32-arm64-msvc.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,12 +1,12 @@
 {
  "name": "wickra-win32-x64-msvc",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.win32-x64-msvc.node",
  "files": [
    "wickra.win32-x64-msvc.node"
  ],
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "engines": {
    "node": ">= 18"
  },
@@ -1,13 +1,13 @@
 {
  "name": "wickra",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "wickra",
-      "version": "0.4.1",
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "version": "0.6.1",
+      "license": "MIT OR Apache-2.0",
      "devDependencies": {
        "@napi-rs/cli": "^2.18.0"
      },
@@ -15,12 +15,12 @@
        "node": ">= 18"
      },
      "optionalDependencies": {
-        "wickra-darwin-arm64": "0.4.1",
-        "wickra-darwin-x64": "0.4.1",
-        "wickra-linux-arm64-gnu": "0.4.1",
-        "wickra-linux-x64-gnu": "0.4.1",
-        "wickra-win32-arm64-msvc": "0.4.1",
-        "wickra-win32-x64-msvc": "0.4.1"
+        "wickra-darwin-arm64": "0.6.1",
+        "wickra-darwin-x64": "0.6.1",
+        "wickra-linux-arm64-gnu": "0.6.1",
+        "wickra-linux-x64-gnu": "0.6.1",
+        "wickra-win32-arm64-msvc": "0.6.1",
+        "wickra-win32-x64-msvc": "0.6.1"
      }
    },
    "node_modules/@napi-rs/cli": {
@@ -41,13 +41,13 @@
      }
    },
    "node_modules/wickra-darwin-arm64": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.6.1.tgz",
      "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
      "cpu": [
        "arm64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "darwin"
@@ -57,13 +57,13 @@
      }
    },
    "node_modules/wickra-darwin-x64": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.6.1.tgz",
      "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
      "cpu": [
        "x64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "darwin"
@@ -73,13 +73,13 @@
      }
    },
    "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.6.1.tgz",
      "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
      "cpu": [
        "arm64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "linux"
@@ -89,13 +89,13 @@
      }
    },
    "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.6.1.tgz",
      "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
      "cpu": [
        "x64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "linux"
@@ -105,13 +105,13 @@
      }
    },
    "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.6.1.tgz",
      "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
      "cpu": [
        "arm64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "win32"
@@ -121,13 +121,13 @@
      }
    },
    "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.4.1",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.4.1.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.6.1.tgz",
      "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
      "cpu": [
        "x64"
      ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
      "optional": true,
      "os": [
        "win32"
@@ -1,11 +1,11 @@
 {
  "name": "wickra",
-  "version": "0.4.1",
+  "version": "0.6.1",
  "description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
  "author": "kingchenc <support@wickra.org>",
  "main": "index.js",
  "types": "index.d.ts",
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
  "keywords": [
    "trading",
    "indicators",
@@ -47,12 +47,12 @@
    "node": ">= 18"
  },
  "optionalDependencies": {
-    "wickra-linux-x64-gnu": "0.4.1",
-    "wickra-linux-arm64-gnu": "0.4.1",
-    "wickra-darwin-x64": "0.4.1",
-    "wickra-darwin-arm64": "0.4.1",
-    "wickra-win32-x64-msvc": "0.4.1",
-    "wickra-win32-arm64-msvc": "0.4.1"
+    "wickra-linux-x64-gnu": "0.6.1",
+    "wickra-linux-arm64-gnu": "0.6.1",
+    "wickra-darwin-x64": "0.6.1",
+    "wickra-darwin-arm64": "0.6.1",
+    "wickra-win32-x64-msvc": "0.6.1",
+    "wickra-win32-arm64-msvc": "0.6.1"
  },
  "scripts": {
    "build": "napi build --platform --release",
@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)

 **Streaming-first technical indicators for Python. `pip install wickra` — no
 system dependencies, no C build tooling.**
@@ -66,7 +66,5 @@ risk. The library is provided **as is**, without warranty of any kind.

 ## License

-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.
@@ -49,6 +49,7 @@ TALIB = _try_import("talib")
 PANDAS_TA = _try_import("pandas_ta")
 TALIPP = _try_import("talipp.indicators") or _try_import("talipp")
 FINTA = _try_import("finta")
+TULIPY = _try_import("tulipy")
 PD = _try_import("pandas")
 import wickra as WICKRA  # noqa: E402  -- the library under test must be importable

@@ -275,6 +276,34 @@ def talipp_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
    return lambda: BB(period=20, std_dev_mult=2.0, input_values=list(prices))


+# tulipy wraps the C "Tulip Indicators" library; it takes contiguous float64
+# arrays and indicator options as positional arguments.
+
+
+def tulipy_sma_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.sma(prices, 20))
+
+
+def tulipy_ema_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.ema(prices, 20))
+
+
+def tulipy_rsi_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.rsi(prices, 14))
+
+
+def tulipy_macd_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.macd(prices, 12, 26, 9))
+
+
+def tulipy_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.bbands(prices, 20, 2.0))
+
+
+def tulipy_atr_batch(high: np.ndarray, low: np.ndarray, close: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.atr(high, low, close, 14))
+
+
 # --------------------------------------------------------------------------- #
 # Streaming scenario: per-tick latency
 # --------------------------------------------------------------------------- #
@@ -329,6 +358,105 @@ def talipp_rsi_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callabl
    return run


+# Scalar streaming peers: Wickra and talipp both update incrementally in O(1),
+# so this is the like-for-like per-tick comparison (batch-only libs are covered
+# by the batch tables and the recompute contrast on RSI above).
+
+
+def wickra_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        sma = WICKRA.SMA(20)
+        sma.batch(seed)
+        for p in live:
+            sma.update(float(p))
+
+    return run
+
+
+def talipp_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import SMA  # type: ignore
+
+    def run() -> None:
+        sma = SMA(period=20, input_values=list(seed))
+        for p in live:
+            sma.add(float(p))
+
+    return run
+
+
+def wickra_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        ema = WICKRA.EMA(20)
+        ema.batch(seed)
+        for p in live:
+            ema.update(float(p))
+
+    return run
+
+
+def talipp_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import EMA  # type: ignore
+
+    def run() -> None:
+        ema = EMA(period=20, input_values=list(seed))
+        for p in live:
+            ema.add(float(p))
+
+    return run
+
+
+def wickra_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        macd = WICKRA.MACD()
+        macd.batch(seed)
+        for p in live:
+            macd.update(float(p))
+
+    return run
+
+
+def talipp_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import MACD  # type: ignore
+
+    def run() -> None:
+        macd = MACD(
+            fast_period=12, slow_period=26, signal_period=9, input_values=list(seed)
+        )
+        for p in live:
+            macd.add(float(p))
+
+    return run
+
+
+def wickra_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        bb = WICKRA.BollingerBands(20, 2.0)
+        bb.batch(seed)
+        for p in live:
+            bb.update(float(p))
+
+    return run
+
+
+def talipp_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import BB  # type: ignore
+
+    def run() -> None:
+        bb = BB(period=20, std_dev_mult=2.0, input_values=list(seed))
+        for p in live:
+            bb.add(float(p))
+
+    return run
+
+
 # --------------------------------------------------------------------------- #
 # Runner
 # --------------------------------------------------------------------------- #
@@ -339,6 +467,7 @@ BATCH_INDICATORS = [
        ("Wickra", wickra_sma_batch),
        ("TA-Lib", talib_sma_batch),
        ("pandas-ta", pandas_ta_sma_batch),
+        ("tulipy", tulipy_sma_batch),
        ("finta", finta_sma_batch),
        ("talipp", talipp_sma_batch),
    ]),
@@ -346,6 +475,7 @@ BATCH_INDICATORS = [
        ("Wickra", wickra_ema_batch),
        ("TA-Lib", talib_ema_batch),
        ("pandas-ta", pandas_ta_ema_batch),
+        ("tulipy", tulipy_ema_batch),
        ("finta", finta_ema_batch),
        ("talipp", talipp_ema_batch),
    ]),
@@ -353,6 +483,7 @@ BATCH_INDICATORS = [
        ("Wickra", wickra_rsi_batch),
        ("TA-Lib", talib_rsi_batch),
        ("pandas-ta", pandas_ta_rsi_batch),
+        ("tulipy", tulipy_rsi_batch),
        ("finta", finta_rsi_batch),
        ("talipp", talipp_rsi_batch),
    ]),
@@ -360,6 +491,7 @@ BATCH_INDICATORS = [
        ("Wickra", wickra_macd_batch),
        ("TA-Lib", talib_macd_batch),
        ("pandas-ta", pandas_ta_macd_batch),
+        ("tulipy", tulipy_macd_batch),
        ("finta", finta_macd_batch),
        ("talipp", talipp_macd_batch),
    ]),
@@ -367,6 +499,7 @@ BATCH_INDICATORS = [
        ("Wickra", wickra_bollinger_batch),
        ("TA-Lib", talib_bollinger_batch),
        ("pandas-ta", pandas_ta_bollinger_batch),
+        ("tulipy", tulipy_bollinger_batch),
        ("finta", finta_bollinger_batch),
        ("talipp", talipp_bollinger_batch),
    ]),
@@ -376,18 +509,35 @@ OHLC_INDICATORS = [
    ("ATR(14)", [
        ("Wickra", wickra_atr_batch),
        ("TA-Lib", talib_atr_batch),
+        ("tulipy", tulipy_atr_batch),
        ("finta", finta_atr_batch),
        ("talipp", talipp_atr_batch),
    ]),
 ]

 STREAMING_INDICATORS = [
+    ("SMA(20)", [
+        ("Wickra", wickra_sma_streaming),
+        ("talipp", talipp_sma_streaming),
+    ]),
+    ("EMA(20)", [
+        ("Wickra", wickra_ema_streaming),
+        ("talipp", talipp_ema_streaming),
+    ]),
    ("RSI(14)", [
        ("Wickra", wickra_rsi_streaming),
        ("TA-Lib", talib_rsi_streaming),
        ("pandas-ta", pandas_ta_rsi_streaming),
        ("talipp", talipp_rsi_streaming),
    ]),
+    ("MACD(12, 26, 9)", [
+        ("Wickra", wickra_macd_streaming),
+        ("talipp", talipp_macd_streaming),
+    ]),
+    ("Bollinger(20, 2.0)", [
+        ("Wickra", wickra_bollinger_streaming),
+        ("talipp", talipp_bollinger_streaming),
+    ]),
 ]


@@ -501,6 +651,7 @@ def main() -> None:
    available = []
    if TALIB is not None: available.append("TA-Lib")
    if PANDAS_TA is not None: available.append("pandas-ta")
+    if TULIPY is not None: available.append("tulipy")
    if FINTA is not None: available.append("finta")
    if TALIPP is not None: available.append("talipp")
    print(f"Wickra benchmark suite — wickra=v{WICKRA.__version__}")
@@ -4,17 +4,16 @@ build-backend = "maturin"

 [project]
 name = "wickra"
-version = "0.4.1"
+version = "0.6.1"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
-license = { text = "PolyForm-Noncommercial-1.0.0" }
+license = "MIT OR Apache-2.0"
 authors = [{ name = "kingchenc", email = "support@wickra.org" }]
 requires-python = ">=3.9"
 keywords = ["finance", "trading", "indicators", "technical-analysis", "ta-lib"]
 classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Financial and Insurance Industry",
-    "License :: Free for non-commercial use",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3 :: Only",
    "Programming Language :: Python :: 3.9",
@@ -40,6 +39,7 @@ bench = [
    "pytest-benchmark>=4",
    "TA-Lib; platform_system != 'Windows'",
    "pandas-ta>=0.3.14b",
+    "tulipy>=0.4; platform_system != 'Windows'",
    "talipp>=2",
    "finta>=1.3",
    "pandas>=2",
@@ -25,6 +25,65 @@ from __future__ import annotations

 from ._wickra import (
    __version__,
+    ProjectionOscillator,
+    VolatilityCone,
+    VolatilityRatio,
+    BipowerVariation,
+    VolatilityOfVolatility,
+    Garch11,
+    EwmaVolatility,
+    PpoHistogram,
+    MacdHistogram,
+    TsfOscillator,
+    Qstick,
+    GatorOscillator,
+    KasePermissionStochastic,
+    WAVE_PM,
+    POLARIZED_FRACTAL_EFFICIENCY,
+    TREND_STRENGTH_INDEX,
+    TTM_TREND,
+    QQE,
+    IMI,
+    ElderRay,
+    DerivativeOscillator,
+    RMI,
+    StochasticCCI,
+    DynamicMomentumIndex,
+    RSX,
+    FisherRSI,
+    DisparityIndex,
+    HoltWinters,
+    GD,
+    AdaptiveLaguerre,
+    MedianMA,
+    EHMA,
+    GMA,
+    SWMA,
+    Expectancy,
+    WinRate,
+    RegimeLabel,
+    JumpIndicator,
+    TrendLabel,
+    HighLowRange,
+    WickRatio,
+    BodySizePct,
+    CloseVsOpen,
+    RollingQuantile,
+    RollingPercentileRank,
+    RollingIqr,
+    RealizedVolatility,
+    LogReturn,
+    TSF,
+    LINEARREG_INTERCEPT,
+    ROCR100,
+    ROCR,
+    ROCP,
+    AVGPRICE,
+    MIDPOINT,
+    MIDPRICE,
+    DX,
+    MINUS_DI,
+    PLUS_DI,
    # Trend
    SMA,
    EMA,
@@ -47,13 +106,18 @@ from ._wickra import (
    EVWMA,
    # Momentum
    RSI,
+    AnchoredRSI,
    MACD,
+    MACDFIX,
+    MACDEXT,
    Stochastic,
    CCI,
    ROC,
    WilliamsR,
    ADX,
    ADXR,
+    PLUS_DM,
+    MINUS_DM,
    MFI,
    TRIX,
    AwesomeOscillator,
@@ -97,6 +161,7 @@ from ._wickra import (
    Keltner,
    Donchian,
    PSAR,
+    SAREXT,
    NATR,
    StdDev,
    UlcerIndex,
@@ -142,6 +207,16 @@ from ._wickra import (
    MarketFacilitationIndex,
    EaseOfMovement,
    # Statistics
+    SpreadBollingerBands,
+    KalmanHedgeRatio,
+    GrangerCausality,
+    VarianceRatio,
+    BetaNeutralSpread,
+    DistanceSsd,
+    SpreadHurst,
+    OuHalfLife,
+    RollingCovariance,
+    RollingCorrelation,
    TypicalPrice,
    MedianPrice,
    WeightedClose,
@@ -162,6 +237,7 @@ from ._wickra import (
    PearsonCorrelation,
    Beta,
    PairwiseBeta,
+    SpreadAr1Coefficient,
    PairSpreadZScore,
    LeadLagCrossCorrelation,
    Cointegration,
@@ -180,11 +256,18 @@ from ._wickra import (
    EhlersStochastic,
    EmpiricalModeDecomposition,
    HilbertDominantCycle,
+    HT_DCPHASE,
+    HT_PHASOR,
+    HT_TRENDMODE,
    AdaptiveCycle,
    SineWave,
    MAMA,
    FAMA,
    # Bands & Channels
+    ProjectionBands,
+    MedianChannel,
+    BomarBands,
+    QuartileBands,
    MaEnvelope,
    AccelerationBands,
    StarcBands,
@@ -222,8 +305,14 @@ from ._wickra import (
    HeikinAshi,
    # Market Profile
    ValueArea,
+    VolumeProfile,
+    TpoProfile,
    InitialBalance,
    OpeningRange,
+    # Alt-Chart Bars
+    RenkoBars,
+    KagiBars,
+    PointAndFigureBars,
    # Candlestick patterns
    Doji,
    Hammer,
@@ -240,6 +329,130 @@ from ._wickra import (
    SpinningTop,
    ThreeInside,
    ThreeOutside,
+    TwoCrows,
+    UpsideGapTwoCrows,
+    IdenticalThreeCrows,
+    ThreeLineStrike,
+    ThreeStarsInSouth,
+    AbandonedBaby,
+    AdvanceBlock,
+    BeltHold,
+    Breakaway,
+    Counterattack,
+    DojiStar,
+    DragonflyDoji,
+    GravestoneDoji,
+    LongLeggedDoji,
+    RickshawMan,
+    EveningDojiStar,
+    MorningDojiStar,
+    GapSideBySideWhite,
+    HighWave,
+    Hikkake,
+    HikkakeModified,
+    HomingPigeon,
+    OnNeck,
+    InNeck,
+    Thrusting,
+    SeparatingLines,
+    Kicking,
+    KickingByLength,
+    LadderBottom,
+    MatHold,
+    MatchingLow,
+    LongLine,
+    ShortLine,
+    RisingThreeMethods,
+    FallingThreeMethods,
+    UpsideGapThreeMethods,
+    DownsideGapThreeMethods,
+    StalledPattern,
+    StickSandwich,
+    Takuri,
+    ClosingMarubozu,
+    OpeningMarubozu,
+    TasukiGap,
+    UniqueThreeRiver,
+    ConcealingBabySwallow,
+    # Chart patterns
+    CupAndHandle,
+    RectangleRange,
+    FlagPennant,
+    Wedge,
+    Triangle,
+    HeadAndShoulders,
+    TripleTopBottom,
+    DoubleTopBottom,
+    # Harmonic patterns
+    ThreeDrives,
+    Cypher,
+    Shark,
+    Crab,
+    Bat,
+    Butterfly,
+    Gartley,
+    Abcd,
+    # Fibonacci
+    FibTimeZones,
+    FibChannel,
+    FibArcs,
+    FibFan,
+    FibConfluence,
+    GoldenPocket,
+    AutoFib,
+    FibProjection,
+    FibExtension,
+    FibRetracement,
+    # Microstructure: order book
+    OrderFlowImbalance,
+    OrderBookImbalanceTop1,
+    OrderBookImbalanceTopN,
+    OrderBookImbalanceFull,
+    Microprice,
+    QuotedSpread,
+    DepthSlope,
+    # Microstructure: trade flow
+    RollMeasure,
+    AmihudIlliquidity,
+    Vpin,
+    SignedVolume,
+    CumulativeVolumeDelta,
+    TradeImbalance,
+    # Microstructure: price impact
+    EffectiveSpread,
+    RealizedSpread,
+    KylesLambda,
+    # Microstructure: footprint
+    Footprint,
+    # Derivatives
+    FundingRate,
+    FundingRateMean,
+    FundingRateZScore,
+    FundingBasis,
+    OpenInterestDelta,
+    OIPriceDivergence,
+    OIWeighted,
+    LongShortRatio,
+    TakerBuySellRatio,
+    LiquidationFeatures,
+    TermStructureBasis,
+    CalendarSpread,
+    # Market Breadth
+    TickIndex,
+    AbsoluteBreadthIndex,
+    CumulativeVolumeIndex,
+    BullishPercentIndex,
+    UpDownVolumeRatio,
+    PercentAboveMa,
+    HighLowIndex,
+    NewHighsNewLows,
+    BreadthThrust,
+    Trin,
+    McClellanSummationIndex,
+    McClellanOscillator,
+    AdVolumeLine,
+    AdvanceDeclineRatio,
+    AdvanceDecline,
    # Risk / Performance
    SharpeRatio,
    SortinoRatio,
@@ -258,9 +471,81 @@ from ._wickra import (
    TreynorRatio,
    InformationRatio,
    Alpha,
+    # Seasonality & Session
+    SessionVwap,
+    SessionHighLow,
+    SessionRange,
+    AverageDailyRange,
+    OvernightGap,
+    OvernightIntradayReturn,
+    TurnOfMonth,
+    SeasonalZScore,
+    TimeOfDayReturnProfile,
+    DayOfWeekProfile,
+    IntradayVolatilityProfile,
+    VolumeByTimeProfile,
 )

 __all__ = [
+    "ProjectionOscillator",
+    "VolatilityCone",
+    "VolatilityRatio",
+    "BipowerVariation",
+    "VolatilityOfVolatility",
+    "Garch11",
+    "EwmaVolatility",
+    "PpoHistogram",
+    "MacdHistogram",
+    "TsfOscillator",
+    "Qstick",
+    "GatorOscillator",
+    "KasePermissionStochastic",
+    "WAVE_PM",
+    "POLARIZED_FRACTAL_EFFICIENCY",
+    "TREND_STRENGTH_INDEX",
+    "TTM_TREND",
+    "QQE",
+    "IMI",
+    "ElderRay",
+    "DerivativeOscillator",
+    "RMI",
+    "StochasticCCI",
+    "DynamicMomentumIndex",
+    "RSX",
+    "FisherRSI",
+    "DisparityIndex",
+    "HoltWinters",
+    "GD",
+    "AdaptiveLaguerre",
+    "MedianMA",
+    "EHMA",
+    "GMA",
+    "SWMA",
+    "Expectancy",
+    "WinRate",
+    "RegimeLabel",
+    "JumpIndicator",
+    "TrendLabel",
+    "HighLowRange",
+    "WickRatio",
+    "BodySizePct",
+    "CloseVsOpen",
+    "RollingQuantile",
+    "RollingPercentileRank",
+    "RollingIqr",
+    "RealizedVolatility",
+    "LogReturn",
+    "TSF",
+    "LINEARREG_INTERCEPT",
+    "ROCR100",
+    "ROCR",
+    "ROCP",
+    "AVGPRICE",
+    "MIDPOINT",
+    "MIDPRICE",
+    "DX",
+    "MINUS_DI",
+    "PLUS_DI",
    "__version__",
    # Trend
    "SMA",
@@ -284,13 +569,18 @@ __all__ = [
    "EVWMA",
    # Momentum
    "RSI",
+    "AnchoredRSI",
    "MACD",
+    "MACDFIX",
+    "MACDEXT",
    "Stochastic",
    "CCI",
    "ROC",
    "WilliamsR",
    "ADX",
    "ADXR",
+    "PLUS_DM",
+    "MINUS_DM",
    "MFI",
    "TRIX",
    "AwesomeOscillator",
@@ -334,6 +624,7 @@ __all__ = [
    "Keltner",
    "Donchian",
    "PSAR",
+    "SAREXT",
    "NATR",
    "StdDev",
    "UlcerIndex",
@@ -379,6 +670,16 @@ __all__ = [
    "MarketFacilitationIndex",
    "EaseOfMovement",
    # Statistics
+    "SpreadBollingerBands",
+    "KalmanHedgeRatio",
+    "GrangerCausality",
+    "VarianceRatio",
+    "BetaNeutralSpread",
+    "DistanceSsd",
+    "SpreadHurst",
+    "OuHalfLife",
+    "RollingCovariance",
+    "RollingCorrelation",
    "TypicalPrice",
    "MedianPrice",
    "WeightedClose",
@@ -399,6 +700,7 @@ __all__ = [
    "PearsonCorrelation",
    "Beta",
    "PairwiseBeta",
+    "SpreadAr1Coefficient",
    "PairSpreadZScore",
    "LeadLagCrossCorrelation",
    "Cointegration",
@@ -417,11 +719,18 @@ __all__ = [
    "EhlersStochastic",
    "EmpiricalModeDecomposition",
    "HilbertDominantCycle",
+    "HT_DCPHASE",
+    "HT_PHASOR",
+    "HT_TRENDMODE",
    "AdaptiveCycle",
    "SineWave",
    "MAMA",
    "FAMA",
    # Bands & Channels
+    "ProjectionBands",
+    "MedianChannel",
+    "BomarBands",
+    "QuartileBands",
    "MaEnvelope",
    "AccelerationBands",
    "StarcBands",
@@ -459,8 +768,14 @@ __all__ = [
    "HeikinAshi",
    # Market Profile
    "ValueArea",
+    "VolumeProfile",
+    "TpoProfile",
    "InitialBalance",
    "OpeningRange",
+    # Alt-Chart Bars
+    "RenkoBars",
+    "KagiBars",
+    "PointAndFigureBars",
    # Candlestick patterns
    "Doji",
    "Hammer",
@@ -477,6 +792,130 @@ __all__ = [
    "SpinningTop",
    "ThreeInside",
    "ThreeOutside",
+    "TwoCrows",
+    "UpsideGapTwoCrows",
+    "IdenticalThreeCrows",
+    "ThreeLineStrike",
+    "ThreeStarsInSouth",
+    "AbandonedBaby",
+    "AdvanceBlock",
+    "BeltHold",
+    "Breakaway",
+    "Counterattack",
+    "DojiStar",
+    "DragonflyDoji",
+    "GravestoneDoji",
+    "LongLeggedDoji",
+    "RickshawMan",
+    "EveningDojiStar",
+    "MorningDojiStar",
+    "GapSideBySideWhite",
+    "HighWave",
+    "Hikkake",
+    "HikkakeModified",
+    "HomingPigeon",
+    "OnNeck",
+    "InNeck",
+    "Thrusting",
+    "SeparatingLines",
+    "Kicking",
+    "KickingByLength",
+    "LadderBottom",
+    "MatHold",
+    "MatchingLow",
+    "LongLine",
+    "ShortLine",
+    "RisingThreeMethods",
+    "FallingThreeMethods",
+    "UpsideGapThreeMethods",
+    "DownsideGapThreeMethods",
+    "StalledPattern",
+    "StickSandwich",
+    "Takuri",
+    "ClosingMarubozu",
+    "OpeningMarubozu",
+    "TasukiGap",
+    "UniqueThreeRiver",
+    "ConcealingBabySwallow",
+    # Chart patterns
+    "CupAndHandle",
+    "RectangleRange",
+    "FlagPennant",
+    "Wedge",
+    "Triangle",
+    "HeadAndShoulders",
+    "TripleTopBottom",
+    "DoubleTopBottom",
+    # Harmonic patterns
+    "ThreeDrives",
+    "Cypher",
+    "Shark",
+    "Crab",
+    "Bat",
+    "Butterfly",
+    "Gartley",
+    "Abcd",
+    # Fibonacci
+    "FibTimeZones",
+    "FibChannel",
+    "FibArcs",
+    "FibFan",
+    "FibConfluence",
+    "GoldenPocket",
+    "AutoFib",
+    "FibProjection",
+    "FibExtension",
+    "FibRetracement",
+    # Microstructure: order book
+    "OrderFlowImbalance",
+    "OrderBookImbalanceTop1",
+    "OrderBookImbalanceTopN",
+    "OrderBookImbalanceFull",
+    "Microprice",
+    "QuotedSpread",
+    "DepthSlope",
+    # Microstructure: trade flow
+    "RollMeasure",
+    "AmihudIlliquidity",
+    "Vpin",
+    "SignedVolume",
+    "CumulativeVolumeDelta",
+    "TradeImbalance",
+    # Microstructure: price impact
+    "EffectiveSpread",
+    "RealizedSpread",
+    "KylesLambda",
+    # Microstructure: footprint
+    "Footprint",
+    # Derivatives
+    "FundingRate",
+    "FundingRateMean",
+    "FundingRateZScore",
+    "FundingBasis",
+    "OpenInterestDelta",
+    "OIPriceDivergence",
+    "OIWeighted",
+    "LongShortRatio",
+    "TakerBuySellRatio",
+    "LiquidationFeatures",
+    "TermStructureBasis",
+    "CalendarSpread",
+    # Market Breadth
+    "TickIndex",
+    "AbsoluteBreadthIndex",
+    "CumulativeVolumeIndex",
+    "BullishPercentIndex",
+    "UpDownVolumeRatio",
+    "PercentAboveMa",
+    "HighLowIndex",
+    "NewHighsNewLows",
+    "BreadthThrust",
+    "Trin",
+    "McClellanSummationIndex",
+    "McClellanOscillator",
+    "AdVolumeLine",
+    "AdvanceDeclineRatio",
+    "AdvanceDecline",
    # Risk / Performance
    "SharpeRatio",
    "SortinoRatio",
@@ -495,4 +934,17 @@ __all__ = [
    "TreynorRatio",
    "InformationRatio",
    "Alpha",
+    # Seasonality & Session
+    "SessionVwap",
+    "SessionHighLow",
+    "SessionRange",
+    "AverageDailyRange",
+    "OvernightGap",
+    "OvernightIntradayReturn",
+    "TurnOfMonth",
+    "SeasonalZScore",
+    "TimeOfDayReturnProfile",
+    "DayOfWeekProfile",
+    "IntradayVolatilityProfile",
+    "VolumeByTimeProfile",
 ]
@@ -166,3 +166,115 @@ def test_family_10_ehlers_rejects_invalid_parameters():
        ta.MAMA(0.05, 0.5)
    with pytest.raises(ValueError):
        ta.EmpiricalModeDecomposition(20, 0.0)
+
+
+def test_orderbook_topn_zero_levels_raises():
+    with pytest.raises(ValueError):
+        ta.OrderBookImbalanceTopN(0)
+
+
+def test_orderbook_unequal_price_size_lengths_raise():
+    # bid_px has 2 entries but bid_sz has 1 -> mismatched -> ValueError.
+    with pytest.raises(ValueError):
+        ta.OrderBookImbalanceTop1().update([100.0, 99.0], [1.0], [101.0], [1.0])
+    with pytest.raises(ValueError):
+        ta.Microprice().update([100.0], [1.0], [101.0, 102.0], [1.0])
+
+
+def test_orderbook_crossed_book_raises():
+    # best_bid (102) >= best_ask (101) is a crossed book -> rejected.
+    with pytest.raises(ValueError):
+        ta.QuotedSpread().update([102.0], [1.0], [101.0], [1.0])
+
+
+def test_orderbook_misordered_levels_raise():
+    # Bids must be strictly descending in price.
+    with pytest.raises(ValueError):
+        ta.OrderBookImbalanceFull().update([99.0, 100.0], [1.0, 1.0], [101.0], [1.0])
+
+
+def test_trade_imbalance_zero_window_raises():
+    with pytest.raises(ValueError):
+        ta.TradeImbalance(0)
+
+
+def test_trade_negative_size_raises():
+    with pytest.raises(ValueError):
+        ta.SignedVolume().update(100.0, -1.0, True)
+
+
+def test_trade_non_positive_price_raises():
+    with pytest.raises(ValueError):
+        ta.CumulativeVolumeDelta().update(0.0, 1.0, True)
+
+
+def test_trade_batch_unequal_lengths_raise():
+    with pytest.raises(ValueError):
+        ta.SignedVolume().batch([100.0, 100.0], [1.0], [True, False])
+
+
+def test_effective_spread_non_positive_mid_raises():
+    with pytest.raises(ValueError):
+        ta.EffectiveSpread().update(100.0, 1.0, True, 0.0)
+
+
+def test_effective_spread_batch_unequal_lengths_raise():
+    with pytest.raises(ValueError):
+        ta.EffectiveSpread().batch([100.0, 100.0], [1.0, 1.0], [True, False], [100.0])
+
+
+def test_realized_spread_zero_horizon_raises():
+    with pytest.raises(ValueError):
+        ta.RealizedSpread(0)
+
+
+def test_kyles_lambda_window_below_two_raises():
+    with pytest.raises(ValueError):
+        ta.KylesLambda(1)
+
+
+def test_footprint_non_positive_tick_raises():
+    with pytest.raises(ValueError):
+        ta.Footprint(0.0)
+    with pytest.raises(ValueError):
+        ta.Footprint(-1.0)
+
+
+def test_funding_rate_mean_zero_window_raises():
+    with pytest.raises(ValueError):
+        ta.FundingRateMean(0)
+
+
+def test_funding_rate_zscore_zero_window_raises():
+    with pytest.raises(ValueError):
+        ta.FundingRateZScore(0)
+
+
+def test_funding_basis_non_positive_index_raises():
+    with pytest.raises(ValueError):
+        ta.FundingBasis().update(100.0, 0.0)
+
+
+def test_funding_rate_non_finite_raises():
+    with pytest.raises(ValueError):
+        ta.FundingRate().update(float("nan"))
+
+
+def test_oi_price_divergence_zero_window_raises():
+    with pytest.raises(ValueError):
+        ta.OIPriceDivergence(0)
+
+
+def test_oi_weighted_non_positive_mark_raises():
+    with pytest.raises(ValueError):
+        ta.OIWeighted().update(0.0, 100.0)
+
+
+def test_term_structure_basis_non_positive_index_raises():
+    with pytest.raises(ValueError):
+        ta.TermStructureBasis().update(100.0, 0.0)
+
+
+def test_calendar_spread_non_positive_mark_raises():
+    with pytest.raises(ValueError):
+        ta.CalendarSpread().update(100.0, 0.0)
@@ -66,6 +66,14 @@ def test_rsi_wilder_textbook_first_value():
    assert math.isclose(out[14], 70.464, abs_tol=0.05)


+def test_anchored_rsi_cumulative_reference():
+    """Cumulative anchored RSI: 10 -> 11 (+1) -> 9 (-2) -> 12 (+3)."""
+    out = ta.AnchoredRSI().batch(np.array([10.0, 11.0, 9.0, 12.0]))
+    assert math.isclose(out[1], 100.0, abs_tol=1e-9)
+    assert math.isclose(out[2], 100.0 - 100.0 / 1.5, abs_tol=1e-6)
+    assert math.isclose(out[3], 100.0 - 100.0 / 3.0, abs_tol=1e-6)
+
+
 def test_inertia_constant_rvi_passes_through_linreg():
    # Every bar identical (open, high, low, close) = (10, 11, 9, 10.5):
    # RVI = (c-o) / (h-l) = 0.5 / 2 = 0.25 every bar. LinReg of a constant
@@ -823,3 +831,206 @@ def test_yang_zhang_zero_movement_yields_zero():
    ready = out[~np.isnan(out)]
    assert ready.size > 0
    np.testing.assert_allclose(ready, 0.0, atol=1e-12)
+
+
+def test_doji_default_is_directionless_flag():
+    # Default Doji is a direction-less detection flag: +1 on a doji, 0 else.
+    d = ta.Doji()
+    assert d.is_signed() is False
+    # body 0, range 2 -> doji.
+    assert d.update((10.0, 11.0, 9.0, 10.0, 1.0, 0)) == pytest.approx(1.0)
+    # body 2 == range -> not a doji.
+    assert d.update((10.0, 12.0, 10.0, 12.0, 1.0, 1)) == pytest.approx(0.0)
+
+
+def test_doji_signed_dragonfly_gravestone_neutral():
+    # Signed Doji classifies by body position within the range.
+    d = ta.Doji(signed=True)
+    assert d.is_signed() is True
+    # Dragonfly: body at the top, long lower shadow -> bullish +1.
+    assert d.update((10.0, 10.05, 6.0, 10.0, 1.0, 0)) == pytest.approx(1.0)
+    # Gravestone: body at the bottom, long upper shadow -> bearish -1.
+    assert d.update((10.0, 14.0, 9.95, 10.0, 1.0, 1)) == pytest.approx(-1.0)
+    # Long-legged: body centred, symmetric shadows -> neutral 0.
+    assert d.update((10.0, 12.0, 8.0, 10.0, 1.0, 2)) == pytest.approx(0.0)
+    # A large body is not a doji at all -> 0 regardless of position.
+    assert d.update((10.0, 12.0, 10.0, 12.0, 1.0, 3)) == pytest.approx(0.0)
+
+
+def test_orderbook_imbalance_reference_values():
+    # Top-1: (3 - 1) / (3 + 1) = 0.5.
+    assert ta.OrderBookImbalanceTop1().update([100.0], [3.0], [101.0], [1.0]) == pytest.approx(0.5)
+    # Top-2: bidDepth 3, askDepth 2 -> (3 - 2) / 5 = 0.2.
+    topn = ta.OrderBookImbalanceTopN(2)
+    assert topn.update([100.0, 99.0], [2.0, 1.0], [101.0, 102.0], [1.0, 1.0]) == pytest.approx(0.2)
+    # Full: bidDepth 1, askDepth 3 -> (1 - 3) / 4 = -0.5.
+    full = ta.OrderBookImbalanceFull()
+    assert full.update([100.0], [1.0], [101.0, 102.0], [2.0, 1.0]) == pytest.approx(-0.5)
+
+
+def test_microprice_reference_value():
+    # (100*3 + 101*1) / (1 + 3) = 401 / 4 = 100.25 — heavy ask pulls toward bid.
+    mp = ta.Microprice()
+    assert mp.update([100.0], [1.0], [101.0], [3.0]) == pytest.approx(100.25)
+
+
+def test_quoted_spread_reference_value():
+    # spread 1.0, mid 100.5 -> 1 / 100.5 * 10_000 ≈ 99.5025 bps.
+    qs = ta.QuotedSpread()
+    assert qs.update([100.0], [1.0], [101.0], [1.0]) == pytest.approx(99.50248756, abs=1e-6)
+
+
+def test_depth_slope_reference_value():
+    # Symmetric book, each side distances 1, 2 with cumulative sizes 1, 3.
+    # OLS slope of (1->1, 2->3) = 2; mean of two equal sides = 2.
+    ds = ta.DepthSlope()
+    out = ds.update([99.0, 98.0], [1.0, 2.0], [101.0, 102.0], [1.0, 2.0])
+    assert out == pytest.approx(2.0, abs=1e-9)
+    # A book with a single level per side has no slope -> 0.
+    assert ta.DepthSlope().update([100.0], [1.0], [101.0], [1.0]) == pytest.approx(0.0)
+
+
+def test_footprint_buckets_buy_and_sell_volume():
+    fp = ta.Footprint(1.0)
+    fp.update(100.2, 2.0, True)  # bucket 100 -> ask 2
+    fp.update(100.7, 3.0, False)  # bucket 101 -> bid 3
+    out = fp.update(100.1, 1.0, True)  # bucket 100 -> ask 3
+    # Columns are [price, bid_vol, ask_vol], rows sorted ascending by price.
+    assert out.shape == (2, 3)
+    assert list(out[0]) == [100.0, 0.0, 3.0]
+    assert list(out[1]) == [101.0, 3.0, 0.0]
+
+
+def test_signed_volume_reference_values():
+    assert ta.SignedVolume().update(100.0, 2.0, True) == pytest.approx(2.0)
+    assert ta.SignedVolume().update(100.0, 3.0, False) == pytest.approx(-3.0)
+
+
+def test_cumulative_volume_delta_reference_values():
+    cvd = ta.CumulativeVolumeDelta()
+    assert cvd.update(100.0, 5.0, True) == pytest.approx(5.0)
+    assert cvd.update(100.0, 2.0, False) == pytest.approx(3.0)
+    assert cvd.update(100.0, 4.0, False) == pytest.approx(-1.0)
+
+
+def test_trade_imbalance_reference_value():
+    ti = ta.TradeImbalance(2)
+    assert ti.update(100.0, 3.0, True) is None  # warming up
+    # Window full: buyVol 3, sellVol 1 -> (3 - 1) / 4 = 0.5.
+    assert ti.update(100.0, 1.0, False) == pytest.approx(0.5)
+
+
+def test_effective_spread_reference_values():
+    # Buy at 100.05 vs mid 100.0: 2 * (100.05 - 100) / 100 * 10000 = 10 bps.
+    assert ta.EffectiveSpread().update(100.05, 1.0, True, 100.0) == pytest.approx(10.0)
+    # Sell at 99.95 vs mid 100.0: 2 * -1 * (99.95 - 100) / 100 * 10000 = 10 bps.
+    assert ta.EffectiveSpread().update(99.95, 1.0, False, 100.0) == pytest.approx(10.0)
+    # A buy filled below the mid is price improvement -> negative.
+    assert ta.EffectiveSpread().update(99.95, 1.0, True, 100.0) < 0.0
+
+
+def test_realized_spread_reference_value():
+    rs = ta.RealizedSpread(1)
+    assert rs.update(100.10, 1.0, True, 100.0) is None  # buffered
+    # Resolved against mid 100.20 one trade later:
+    # 2 * (+1) * (100.10 - 100.20) / 100.0 * 10000 = -20 bps (adverse selection).
+    assert rs.update(99.90, 1.0, False, 100.20) == pytest.approx(-20.0)
+
+
+def test_kyles_lambda_recovers_constant_impact():
+    # Build a tape where each trade moves the mid by exactly 0.5 per unit of
+    # signed volume -> the rolling OLS slope is 0.5.
+    impact = 0.5
+    mid = 100.0
+    price, size, is_buy, mids = [], [], [], []
+    for i in range(20):
+        buy = i % 2 == 0
+        sz = 1.0 + (i % 3)
+        signed = sz if buy else -sz
+        mid += impact * signed
+        price.append(mid)
+        size.append(sz)
+        is_buy.append(buy)
+        mids.append(mid)
+    out = ta.KylesLambda(6).batch(price, size, is_buy, mids)
+    assert out[-1] == pytest.approx(0.5, abs=1e-9)
+
+
+def test_funding_rate_reference_values():
+    assert ta.FundingRate().update(0.0001) == pytest.approx(0.0001)
+    assert ta.FundingRate().update(-0.0003) == pytest.approx(-0.0003)
+
+
+def test_funding_rate_mean_reference_value():
+    frm = ta.FundingRateMean(2)
+    assert frm.update(0.001) is None  # warming up
+    # Window [0.001, 0.003] -> mean 0.002.
+    assert frm.update(0.003) == pytest.approx(0.002)
+
+
+def test_funding_rate_zscore_reference_value():
+    z = ta.FundingRateZScore(2)
+    assert z.update(0.001) is None  # warming up
+    # Window [0.001, 0.003]: mean 0.002, population stddev 0.001 -> +1.
+    assert z.update(0.003) == pytest.approx(1.0, abs=1e-9)
+
+
+def test_funding_basis_reference_value():
+    # mark 100.5 vs index 100.0 -> (100.5 - 100.0) / 100.0 = 0.005.
+    assert ta.FundingBasis().update(100.5, 100.0) == pytest.approx(0.005)
+    # A discount reads negative.
+    assert ta.FundingBasis().update(99.5, 100.0) == pytest.approx(-0.005)
+
+
+def test_open_interest_delta_reference_value():
+    oid = ta.OpenInterestDelta()
+    assert oid.update(1000.0) is None  # seeds the previous OI
+    assert oid.update(1250.0) == pytest.approx(250.0)
+    assert oid.update(1100.0) == pytest.approx(-150.0)
+
+
+def test_oi_price_divergence_reference_value():
+    div = ta.OIPriceDivergence(1)
+    assert div.update(1000.0, 100.0) is None  # warming up
+    # OI +10% while price flat -> divergence +0.1.
+    assert div.update(1100.0, 100.0) == pytest.approx(0.1)
+
+
+def test_oi_weighted_reference_value():
+    oiw = ta.OIWeighted()
+    assert oiw.update(100.0, 10.0) == pytest.approx(100.0)
+    # (100·10 + 110·30) / 40 = 107.5.
+    assert oiw.update(110.0, 30.0) == pytest.approx(107.5)
+
+
+def test_long_short_ratio_reference_value():
+    # 600 longs vs 400 shorts -> 1.5.
+    assert ta.LongShortRatio().update(600.0, 400.0) == pytest.approx(1.5)
+    # No short side -> 0.0.
+    assert ta.LongShortRatio().update(600.0, 0.0) == pytest.approx(0.0)
+
+
+def test_taker_buy_sell_ratio_reference_value():
+    # 60 taker buys vs 40 taker sells -> 1.5.
+    assert ta.TakerBuySellRatio().update(60.0, 40.0) == pytest.approx(1.5)
+    # No taker sell volume -> 0.0.
+    assert ta.TakerBuySellRatio().update(60.0, 0.0) == pytest.approx(0.0)
+
+
+def test_liquidation_features_reference_value():
+    # 30 long vs 10 short: (long, short, net, total, imbalance).
+    out = ta.LiquidationFeatures().update(30.0, 10.0)
+    assert out == pytest.approx((30.0, 10.0, 20.0, 40.0, 0.5))
+
+
+def test_term_structure_basis_reference_value():
+    # futures 102 vs index 100 -> 0.02 (contango).
+    assert ta.TermStructureBasis().update(102.0, 100.0) == pytest.approx(0.02)
+    # Backwardation reads negative.
+    assert ta.TermStructureBasis().update(98.0, 100.0) == pytest.approx(-0.02)
+
+
+def test_calendar_spread_reference_value():
+    # futures 101 vs perpetual mark 100 -> 0.01.
+    assert ta.CalendarSpread().update(101.0, 100.0) == pytest.approx(0.01)
+    assert ta.CalendarSpread().update(99.0, 100.0) == pytest.approx(-0.01)
@@ -12,6 +12,7 @@ SCALAR_INDICATORS = [
    (ta.EMA, (14,)),
    (ta.WMA, (14,)),
    (ta.RSI, (14,)),
+    (ta.AnchoredRSI, ()),
    (ta.MACD, ()),
    (ta.BollingerBands, ()),
 ]
@@ -42,6 +43,7 @@ def test_reset_returns_to_initial_state(cls, args):
        (ta.EMA, (14,), 14),
        (ta.WMA, (14,), 14),
        (ta.RSI, (14,), 15),
+        (ta.AnchoredRSI, (), 2),
        (ta.BollingerBands, (20, 2.0), 20),
    ],
 )
@@ -129,3 +131,92 @@ def test_ehlers_indicators_lifecycle():
        assert ind.is_ready()
        ind.reset()
        assert not ind.is_ready()
+
+
+def test_orderbook_lifecycle():
+    snapshot = ([100.0], [1.0], [101.0], [1.0])
+    for ind in [
+        ta.OrderBookImbalanceTop1(),
+        ta.OrderBookImbalanceTopN(3),
+        ta.OrderBookImbalanceFull(),
+        ta.Microprice(),
+        ta.QuotedSpread(),
+        ta.DepthSlope(),
+    ]:
+        assert ind.warmup_period() == 1
+        assert not ind.is_ready()
+        ind.update(*snapshot)
+        assert ind.is_ready()
+        ind.reset()
+        assert not ind.is_ready()
+
+
+def test_orderbook_topn_repr():
+    assert repr(ta.OrderBookImbalanceTopN(5)) == "OrderBookImbalanceTopN(levels=5)"
+
+
+def test_tradeflow_lifecycle():
+    for ind in [ta.SignedVolume(), ta.CumulativeVolumeDelta()]:
+        assert ind.warmup_period() == 1
+        assert not ind.is_ready()
+        ind.update(100.0, 1.0, True)
+        assert ind.is_ready()
+        ind.reset()
+        assert not ind.is_ready()
+
+
+def test_trade_imbalance_lifecycle_and_repr():
+    ti = ta.TradeImbalance(3)
+    assert ti.warmup_period() == 3
+    assert not ti.is_ready()
+    for _ in range(3):
+        ti.update(100.0, 1.0, True)
+    assert ti.is_ready()
+    ti.reset()
+    assert not ti.is_ready()
+    assert repr(ta.TradeImbalance(4)) == "TradeImbalance(window=4)"
+
+
+def test_effective_spread_lifecycle():
+    es = ta.EffectiveSpread()
+    assert es.warmup_period() == 1
+    assert not es.is_ready()
+    es.update(100.05, 1.0, True, 100.0)
+    assert es.is_ready()
+    es.reset()
+    assert not es.is_ready()
+
+
+def test_realized_spread_lifecycle_and_repr():
+    rs = ta.RealizedSpread(3)
+    assert rs.warmup_period() == 4
+    assert not rs.is_ready()
+    for _ in range(4):
+        rs.update(100.0, 1.0, True, 100.0)
+    assert rs.is_ready()
+    rs.reset()
+    assert not rs.is_ready()
+    assert repr(ta.RealizedSpread(5)) == "RealizedSpread(horizon=5)"
+
+
+def test_kyles_lambda_lifecycle_and_repr():
+    kl = ta.KylesLambda(3)
+    assert kl.warmup_period() == 4
+    assert not kl.is_ready()
+    for i in range(4):
+        kl.update(100.0 + i, 1.0 + (i % 2), i % 2 == 0, 100.0 + i)
+    assert kl.is_ready()
+    kl.reset()
+    assert not kl.is_ready()
+    assert repr(ta.KylesLambda(7)) == "KylesLambda(window=7)"
+
+
+def test_footprint_lifecycle_and_repr():
+    fp = ta.Footprint(0.5)
+    assert fp.warmup_period() == 1
+    assert not fp.is_ready()
+    fp.update(100.0, 1.0, True)
+    assert fp.is_ready()
+    fp.reset()
+    assert not fp.is_ready()
+    assert repr(ta.Footprint(0.25)) == "Footprint(tick_size=0.25)"
@@ -0,0 +1,132 @@
+"""Streaming-vs-batch equivalence and reference values for the Seasonality &
+Session family.
+
+These indicators read the full candle (including ``timestamp``), so they have a
+dedicated test rather than joining the timestamp-less parametrize harness in
+``test_new_indicators.py``.
+"""
+
+import numpy as np
+import pytest
+
+import wickra as ta
+
+HOUR_MS = 3_600_000
+
+
+@pytest.fixture(scope="module")
+def candle_columns():
+    """240 hourly candles (10 days) with valid OHLCV and epoch-ms timestamps."""
+    n = 240
+    t = np.arange(n, dtype=np.float64)
+    close = 100.0 + np.sin(t * 0.3) * 5.0 + np.cos(t * 0.1) * 3.0
+    open_ = close + np.sin(t * 0.5) * 0.5
+    high = np.maximum(open_, close) + 1.0
+    low = np.minimum(open_, close) - 1.0
+    volume = 1000.0 + (t % 24) * 50.0
+    timestamp = (np.arange(n, dtype=np.int64)) * HOUR_MS
+    return open_, high, low, close, volume, timestamp
+
+
+def _candles(cols):
+    open_, high, low, close, volume, timestamp = cols
+    return [
+        (open_[i], high[i], low[i], close[i], volume[i], int(timestamp[i]))
+        for i in range(len(close))
+    ]
+
+
+def _check_scalar(make, cols):
+    candles = _candles(cols)
+    a, b = make(), make()
+    stream = np.array(
+        [np.nan if (v := a.update(c)) is None else v for c in candles],
+        dtype=np.float64,
+    )
+    batch = np.asarray(b.batch(*cols))
+    np.testing.assert_allclose(stream, batch, equal_nan=True, rtol=1e-9, atol=1e-9)
+
+
+def _check_matrix(make, k, cols):
+    candles = _candles(cols)
+    a, b = make(), make()
+    rows = []
+    for c in candles:
+        out = a.update(c)
+        rows.append(np.full(k, np.nan) if out is None else np.asarray(out, dtype=float))
+    stream = np.vstack(rows)
+    batch = np.asarray(b.batch(*cols))
+    assert batch.shape == (len(candles), k)
+    np.testing.assert_allclose(stream, batch, equal_nan=True, rtol=1e-9, atol=1e-9)
+
+
+SCALAR = [
+    lambda: ta.SessionVwap(0),
+    lambda: ta.OvernightGap(0),
+    lambda: ta.SeasonalZScore(0),
+    lambda: ta.AverageDailyRange(3, 0),
+    lambda: ta.TurnOfMonth(3, 1, 0),
+]
+
+MATRIX = [
+    (lambda: ta.SessionHighLow(0), 2),
+    (lambda: ta.SessionRange(0), 3),
+    (lambda: ta.OvernightIntradayReturn(0), 2),
+    (lambda: ta.TimeOfDayReturnProfile(24, 0), 24),
+    (lambda: ta.IntradayVolatilityProfile(12, 0), 12),
+    (lambda: ta.VolumeByTimeProfile(24, 0), 24),
+    (lambda: ta.DayOfWeekProfile(0), 7),
+]
+
+
+@pytest.mark.parametrize("make", SCALAR)
+def test_scalar_streaming_equals_batch(make, candle_columns):
+    _check_scalar(make, candle_columns)
+
+
+@pytest.mark.parametrize("make,k", MATRIX)
+def test_matrix_streaming_equals_batch(make, k, candle_columns):
+    _check_matrix(make, k, candle_columns)
+
+
+def test_session_vwap_reference():
+    vwap = ta.SessionVwap(0)
+    # typical = close for a flat candle; volume-weighted within the day.
+    v1 = vwap.update((100.0, 100.0, 100.0, 100.0, 10.0, 0))
+    assert v1 == pytest.approx(100.0)
+    v2 = vwap.update((110.0, 110.0, 110.0, 110.0, 30.0, HOUR_MS))
+    assert v2 == pytest.approx(107.5)
+    # New day re-anchors.
+    v3 = vwap.update((200.0, 200.0, 200.0, 200.0, 5.0, 24 * HOUR_MS))
+    assert v3 == pytest.approx(200.0)
+
+
+def test_overnight_gap_reference():
+    gap = ta.OvernightGap(0)
+    assert gap.update((99.0, 101.0, 98.0, 100.0, 1.0, 0)) is None
+    g = gap.update((105.0, 106.0, 104.0, 105.5, 1.0, 24 * HOUR_MS))
+    assert g == pytest.approx(0.05)
+
+
+def test_session_high_low_reference():
+    shl = ta.SessionHighLow(0)
+    shl.update((100.0, 105.0, 99.0, 101.0, 1.0, 0))
+    out = shl.update((101.0, 108.0, 100.0, 107.0, 1.0, HOUR_MS))
+    assert out == (108.0, 99.0)
+
+
+def test_volume_by_time_profile_reference():
+    prof = ta.VolumeByTimeProfile(24, 0)
+    out = prof.update((100.0, 100.0, 100.0, 100.0, 500.0, HOUR_MS))  # 01:00 -> bucket 1
+    assert out[1] == pytest.approx(500.0)
+    assert out[0] == pytest.approx(0.0)
+
+
+def test_rejects_zero_buckets():
+    with pytest.raises(ValueError):
+        ta.TimeOfDayReturnProfile(0, 0)
+
+
+def test_average_daily_range_rejects_zero_period():
+    with pytest.raises(ValueError):
+        ta.AverageDailyRange(0, 0)
@@ -97,3 +97,73 @@ def test_ehlers_super_smoother_batch_shape(sine_prices):
 def test_mama_batch_shape(sine_prices):
    out = ta.MAMA().batch(sine_prices)
    assert out.shape == (sine_prices.size, 2)
+
+
+def test_orderbook_indicators_construct_and_emit():
+    # All five order-book indicators accept a four-array snapshot and emit a float.
+    snapshot = ([100.0, 99.0], [2.0, 1.0], [101.0, 102.0], [1.0, 1.0])
+    indicators = [
+        ta.OrderBookImbalanceTop1(),
+        ta.OrderBookImbalanceTopN(2),
+        ta.OrderBookImbalanceFull(),
+        ta.Microprice(),
+        ta.QuotedSpread(),
+        ta.DepthSlope(),
+    ]
+    for ind in indicators:
+        out = ind.update(*snapshot)
+        assert isinstance(out, float)
+
+
+def test_orderbook_batch_returns_one_value_per_snapshot():
+    snapshots = [([100.0], [3.0], [101.0], [1.0])] * 5
+    out = ta.OrderBookImbalanceTop1().batch(snapshots)
+    assert out.shape == (5,)
+    assert out.dtype == np.float64
+
+
+def test_tradeflow_indicators_construct_and_emit():
+    # SignedVolume and CVD emit from the first trade; TradeImbalance(1) too.
+    assert isinstance(ta.SignedVolume().update(100.0, 2.0, True), float)
+    assert isinstance(ta.CumulativeVolumeDelta().update(100.0, 2.0, True), float)
+    assert isinstance(ta.TradeImbalance(1).update(100.0, 2.0, True), float)
+
+
+def test_tradeflow_batch_returns_one_value_per_trade():
+    price = np.full(6, 100.0)
+    size = np.array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0])
+    is_buy = [True, False, True, False, True, False]
+    out = ta.CumulativeVolumeDelta().batch(price, size, is_buy)
+    assert out.shape == (6,)
+    assert out.dtype == np.float64
+
+
+def test_price_impact_indicators_construct_and_emit():
+    # Price-impact indicators take a trade paired with the prevailing mid.
+    assert isinstance(ta.EffectiveSpread().update(100.05, 1.0, True, 100.0), float)
+    # RealizedSpread buffers until its horizon elapses.
+    assert ta.RealizedSpread(1).update(100.05, 1.0, True, 100.0) is None
+
+
+def test_price_impact_batch_returns_one_value_per_trade():
+    price = np.array([100.05, 99.95, 100.10, 99.90])
+    size = np.array([1.0, 2.0, 1.0, 2.0])
+    is_buy = [True, False, True, False]
+    mid = np.full(4, 100.0)
+    for ind in (ta.EffectiveSpread(), ta.RealizedSpread(2), ta.KylesLambda(2)):
+        out = ind.batch(price, size, is_buy, mid)
+        assert out.shape == (4,)
+        assert out.dtype == np.float64
+
+
+def test_footprint_constructs_and_emits():
+    out = ta.Footprint(1.0).update(100.2, 2.0, True)
+    assert out.shape == (1, 3)
+    assert out.dtype == np.float64
+
+
+def test_footprint_batch_returns_list_of_arrays():
+    res = ta.Footprint(1.0).batch([100.2, 100.7], [2.0, 3.0], [True, False])
+    assert isinstance(res, list)
+    assert len(res) == 2
+    assert res[-1].shape[1] == 3
@@ -201,3 +201,50 @@ def test_opening_range_streaming_matches_batch(ohlc_series):
        rows.append([math.nan, math.nan, math.nan] if out is None else list(out))
    streamed = np.array(rows, dtype=np.float64)
    assert _equal_with_nan(batch, streamed)
+
+
+def test_orderbook_streaming_matches_batch():
+    snaps = [
+        (
+            [100.0, 99.0],
+            [1.0 + (i % 5), 1.0],
+            [101.0, 102.0],
+            [1.0 + ((i + 1) % 3), 1.0],
+        )
+        for i in range(30)
+    ]
+    batch = ta.Microprice().batch(snaps)
+    streamer = ta.Microprice()
+    streamed = np.array([streamer.update(*snap) for snap in snaps], dtype=np.float64)
+    assert _equal_with_nan(batch, streamed)
+
+
+def test_tradeflow_streaming_matches_batch():
+    n = 30
+    price = np.full(n, 100.0)
+    size = np.array([1.0 + (i % 4) for i in range(n)], dtype=np.float64)
+    is_buy = [i % 3 != 0 for i in range(n)]
+    batch = ta.CumulativeVolumeDelta().batch(price, size, is_buy)
+    streamer = ta.CumulativeVolumeDelta()
+    streamed = np.array(
+        [streamer.update(price[i], size[i], is_buy[i]) for i in range(n)],
+        dtype=np.float64,
+    )
+    assert _equal_with_nan(batch, streamed)
+
+
+def test_price_impact_streaming_matches_batch():
+    n = 30
+    mid = np.array([100.0 + 0.25 * math.sin(i * 0.5) for i in range(n)], dtype=np.float64)
+    is_buy = [i % 3 != 0 for i in range(n)]
+    price = np.array(
+        [mid[i] + (0.03 if is_buy[i] else -0.03) for i in range(n)], dtype=np.float64
+    )
+    size = np.array([1.0 + (i % 4) for i in range(n)], dtype=np.float64)
+    batch = ta.EffectiveSpread().batch(price, size, is_buy, mid)
+    streamer = ta.EffectiveSpread()
+    streamed = np.array(
+        [streamer.update(price[i], size[i], is_buy[i], mid[i]) for i in range(n)],
+        dtype=np.float64,
+    )
+    assert _equal_with_nan(batch, streamed)
@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![npm](https://img.shields.io/npm/v/wickra-wasm.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra-wasm)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)

 **Streaming-first technical indicators in the browser. `npm install
 wickra-wasm` — pure WebAssembly, runs anywhere a modern JS engine does.**
@@ -66,7 +66,5 @@ risk. The library is provided **as is**, without warranty of any kind.

 ## License

-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.
@@ -1,4 +1,4 @@
 # Proper nouns that appear in indicator documentation. They are real names,
 # not code identifiers, so `clippy::doc_markdown` must not demand backticks.
 # `..` keeps clippy's built-in default identifier list in addition to these.
-doc-valid-idents = ["LeBeau", ".."]
+doc-valid-idents = ["LeBeau", "McClellan", ".."]
@@ -0,0 +1,22 @@
+[package]
+name = "wickra-bench"
+version.workspace = true
+edition.workspace = true
+license.workspace = true
+publish = false
+description = "Internal cross-library benchmark harness (not published)."
+
+[lints]
+workspace = true
+
+[dev-dependencies]
+wickra = { path = "../wickra" }
+wickra-data = { path = "../wickra-data" }
+criterion = { workspace = true }
+kand = "0.2.2"
+ta = "0.5.0"
+yata = "0.7.0"
+
+[[bench]]
+name = "cross_lib"
+harness = false
@@ -0,0 +1,695 @@
+//! Cross-library Criterion benchmark: Wickra vs `kand` vs `ta` (ta-rs) vs `yata`.
+//!
+//! All four are pure-Rust technical-analysis crates, so this is a like-for-like
+//! Rust-vs-Rust comparison with no language-binding overhead. It feeds the exact
+//! same BTCUSDT 1-minute candle series used by `crates/wickra/benches/indicators.rs`.
+//!
+//! Two arenas, kept honest:
+//!
+//! * **Streaming** (`*/stream`): one value fed at a time. Wickra (`Indicator::update`),
+//!   ta-rs (`Next::next`) and yata (`Method::next`) carry their own state; `kand`
+//!   exposes stateless `*_inc` helpers, so the per-tick state is threaded manually
+//!   here, seeded from `kand`'s own batch output (the seed is computed outside the
+//!   timed closure). yata only appears for SMA/EMA — its RSI/MACD/Bollinger/ATR are
+//!   exposed through a heavier signal-oriented indicator API, not a raw-value method,
+//!   so they are intentionally left out rather than compared unfairly.
+//! * **Batch** (`*/batch`): the whole series at once. Only Wickra (`BatchExt::batch`)
+//!   and `kand` (TA-Lib-style fill-the-output-slice functions) have a real batch API;
+//!   ta-rs and yata are streaming-only and are deliberately absent from this arena.
+//!
+//! Run: `cargo bench -p wickra-bench`
+
+// Each indicator's benchmark group spells out every library arm explicitly, which
+// runs a few groups over the 100-line lint threshold; that verbosity is the point.
+#![allow(clippy::too_many_lines)]
+
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+use std::hint::black_box;
+use wickra::{Atr, BatchExt, BollingerBands, Candle, Ema, Indicator, MacdIndicator, Rsi, Sma};
+use wickra_data::csv::CandleReader;
+use yata::prelude::Method;
+
+const SIZES: &[usize] = &[1_000, 10_000, 50_000];
+
+const SMA_PERIOD: usize = 20;
+const EMA_PERIOD: usize = 20;
+const RSI_PERIOD: usize = 14;
+const ATR_PERIOD: usize = 14;
+const BB_PERIOD: usize = 20;
+const BB_DEV: f64 = 2.0;
+const MACD_FAST: usize = 12;
+const MACD_SLOW: usize = 26;
+const MACD_SIGNAL: usize = 9;
+
+fn load_candles() -> Vec<Candle> {
+    let path = concat!(
+        env!("CARGO_MANIFEST_DIR"),
+        "/../../examples/data/btcusdt-1m.csv"
+    );
+    CandleReader::open(path)
+        .expect("dataset present")
+        .read_all()
+        .expect("valid OHLCV rows")
+}
+
+/// Mean of the first `period` samples — the warmup seed for `kand`'s SMA/EMA `*_inc`.
+fn window_mean(series: &[f64], period: usize) -> f64 {
+    series[..period].iter().sum::<f64>() / period as f64
+}
+
+fn sma_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("sma_20");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Sma::new(SMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Sma::new(SMA_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let seed = window_mean(series, SMA_PERIOD);
+                bencher.iter(|| {
+                    let mut prev = seed;
+                    for idx in SMA_PERIOD..series.len() {
+                        prev = kand::ohlcv::sma::sma_inc(
+                            prev,
+                            series[idx],
+                            series[idx - SMA_PERIOD],
+                            SMA_PERIOD,
+                        )
+                        .unwrap();
+                        black_box(prev);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut out = vec![0.0; series.len()];
+                    kand::ohlcv::sma::sma(series, SMA_PERIOD, &mut out).unwrap();
+                    black_box(&out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::SimpleMovingAverage::new(SMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("yata/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = yata::methods::SMA::new(SMA_PERIOD as u8, &series[0]).unwrap();
+                    for price in series {
+                        black_box(ind.next(price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn ema_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("ema_20");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Ema::new(EMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Ema::new(EMA_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let seed = window_mean(series, EMA_PERIOD);
+                bencher.iter(|| {
+                    let mut prev = seed;
+                    for &price in &series[EMA_PERIOD..] {
+                        prev = kand::ohlcv::ema::ema_inc(price, prev, EMA_PERIOD, None).unwrap();
+                        black_box(prev);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut out = vec![0.0; series.len()];
+                    kand::ohlcv::ema::ema(series, EMA_PERIOD, None, &mut out).unwrap();
+                    black_box(&out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind =
+                        ta::indicators::ExponentialMovingAverage::new(EMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("yata/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = yata::methods::EMA::new(EMA_PERIOD as u8, &series[0]).unwrap();
+                    for price in series {
+                        black_box(ind.next(price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn rsi_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("rsi_14");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Rsi::new(RSI_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Rsi::new(RSI_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Wilder seed: simple average of the first `period` gains and losses.
+                let mut gain = 0.0;
+                let mut loss = 0.0;
+                for idx in 1..=RSI_PERIOD {
+                    let delta = series[idx] - series[idx - 1];
+                    if delta > 0.0 {
+                        gain += delta;
+                    } else {
+                        loss -= delta;
+                    }
+                }
+                let seed_gain = gain / RSI_PERIOD as f64;
+                let seed_loss = loss / RSI_PERIOD as f64;
+                bencher.iter(|| {
+                    let mut avg_gain = seed_gain;
+                    let mut avg_loss = seed_loss;
+                    let mut prev_price = series[RSI_PERIOD];
+                    for &price in &series[RSI_PERIOD + 1..] {
+                        let (rsi, next_gain, next_loss) = kand::ohlcv::rsi::rsi_inc(
+                            price, prev_price, avg_gain, avg_loss, RSI_PERIOD,
+                        )
+                        .unwrap();
+                        avg_gain = next_gain;
+                        avg_loss = next_loss;
+                        prev_price = price;
+                        black_box(rsi);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut rsi = vec![0.0; series.len()];
+                    let mut avg_gain = vec![0.0; series.len()];
+                    let mut avg_loss = vec![0.0; series.len()];
+                    kand::ohlcv::rsi::rsi(
+                        series,
+                        RSI_PERIOD,
+                        &mut rsi,
+                        &mut avg_gain,
+                        &mut avg_loss,
+                    )
+                    .unwrap();
+                    black_box(&rsi);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::RelativeStrengthIndex::new(RSI_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn macd_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("macd_12_26_9");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = MacdIndicator::classic();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = MacdIndicator::classic();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Seed the fast/slow/signal EMAs from kand's own warmed-up batch state.
+                let lookback =
+                    kand::ohlcv::macd::lookback(MACD_FAST, MACD_SLOW, MACD_SIGNAL).unwrap();
+                let mut macd_line = vec![0.0; series.len()];
+                let mut signal_line = vec![0.0; series.len()];
+                let mut histogram = vec![0.0; series.len()];
+                let mut fast_ema = vec![0.0; series.len()];
+                let mut slow_ema = vec![0.0; series.len()];
+                kand::ohlcv::macd::macd(
+                    series,
+                    MACD_FAST,
+                    MACD_SLOW,
+                    MACD_SIGNAL,
+                    &mut macd_line,
+                    &mut signal_line,
+                    &mut histogram,
+                    &mut fast_ema,
+                    &mut slow_ema,
+                )
+                .unwrap();
+                let seed_fast = fast_ema[lookback];
+                let seed_slow = slow_ema[lookback];
+                let seed_signal = signal_line[lookback];
+                bencher.iter(|| {
+                    // macd_inc returns (macd, signal, hist) but not the new EMAs, so the
+                    // fast/slow/signal state is threaded with kand's own ema_inc primitive.
+                    let mut prev_fast = seed_fast;
+                    let mut prev_slow = seed_slow;
+                    let mut prev_signal = seed_signal;
+                    for &price in &series[lookback + 1..] {
+                        let fast =
+                            kand::ohlcv::ema::ema_inc(price, prev_fast, MACD_FAST, None).unwrap();
+                        let slow =
+                            kand::ohlcv::ema::ema_inc(price, prev_slow, MACD_SLOW, None).unwrap();
+                        let macd = fast - slow;
+                        let signal =
+                            kand::ohlcv::ema::ema_inc(macd, prev_signal, MACD_SIGNAL, None)
+                                .unwrap();
+                        prev_fast = fast;
+                        prev_slow = slow;
+                        prev_signal = signal;
+                        black_box((macd, signal, macd - signal));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut macd_line = vec![0.0; series.len()];
+                    let mut signal_line = vec![0.0; series.len()];
+                    let mut histogram = vec![0.0; series.len()];
+                    let mut fast_ema = vec![0.0; series.len()];
+                    let mut slow_ema = vec![0.0; series.len()];
+                    kand::ohlcv::macd::macd(
+                        series,
+                        MACD_FAST,
+                        MACD_SLOW,
+                        MACD_SIGNAL,
+                        &mut macd_line,
+                        &mut signal_line,
+                        &mut histogram,
+                        &mut fast_ema,
+                        &mut slow_ema,
+                    )
+                    .unwrap();
+                    black_box(&macd_line);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::MovingAverageConvergenceDivergence::new(
+                        MACD_FAST,
+                        MACD_SLOW,
+                        MACD_SIGNAL,
+                    )
+                    .unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn bbands_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("bollinger_20_2");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Seed running sma/sum/sum_sq from kand's batch state at the warmup edge.
+                let mut upper = vec![0.0; series.len()];
+                let mut middle = vec![0.0; series.len()];
+                let mut lower = vec![0.0; series.len()];
+                let mut sma = vec![0.0; series.len()];
+                let mut variance = vec![0.0; series.len()];
+                let mut sum = vec![0.0; series.len()];
+                let mut sum_sq = vec![0.0; series.len()];
+                kand::ohlcv::bbands::bbands(
+                    series,
+                    BB_PERIOD,
+                    BB_DEV,
+                    BB_DEV,
+                    &mut upper,
+                    &mut middle,
+                    &mut lower,
+                    &mut sma,
+                    &mut variance,
+                    &mut sum,
+                    &mut sum_sq,
+                )
+                .unwrap();
+                let seed_sma = sma[BB_PERIOD - 1];
+                let seed_sum = sum[BB_PERIOD - 1];
+                let seed_sum_sq = sum_sq[BB_PERIOD - 1];
+                bencher.iter(|| {
+                    let mut prev_sma = seed_sma;
+                    let mut prev_sum = seed_sum;
+                    let mut prev_sum_sq = seed_sum_sq;
+                    for idx in BB_PERIOD..series.len() {
+                        let result = kand::ohlcv::bbands::bbands_inc(
+                            series[idx],
+                            prev_sma,
+                            prev_sum,
+                            prev_sum_sq,
+                            series[idx - BB_PERIOD],
+                            BB_PERIOD,
+                            BB_DEV,
+                            BB_DEV,
+                        )
+                        .unwrap();
+                        prev_sma = result.1;
+                        prev_sum = result.4;
+                        prev_sum_sq = result.5;
+                        black_box((result.0, result.1, result.2));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut upper = vec![0.0; series.len()];
+                    let mut middle = vec![0.0; series.len()];
+                    let mut lower = vec![0.0; series.len()];
+                    let mut sma = vec![0.0; series.len()];
+                    let mut variance = vec![0.0; series.len()];
+                    let mut sum = vec![0.0; series.len()];
+                    let mut sum_sq = vec![0.0; series.len()];
+                    kand::ohlcv::bbands::bbands(
+                        series,
+                        BB_PERIOD,
+                        BB_DEV,
+                        BB_DEV,
+                        &mut upper,
+                        &mut middle,
+                        &mut lower,
+                        &mut sma,
+                        &mut variance,
+                        &mut sum,
+                        &mut sum_sq,
+                    )
+                    .unwrap();
+                    black_box(&upper);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn atr_group(crit: &mut Criterion, candles: &[Candle]) {
+    let mut group = crit.benchmark_group("atr_14");
+    for &len in SIZES {
+        let len = len.min(candles.len());
+        let series: &[Candle] = &candles[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Atr::new(ATR_PERIOD).unwrap();
+                    for &candle in series {
+                        black_box(ind.update(candle));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Atr::new(ATR_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let high: Vec<f64> = series.iter().map(|candle| candle.high).collect();
+                let low: Vec<f64> = series.iter().map(|candle| candle.low).collect();
+                let close: Vec<f64> = series.iter().map(|candle| candle.close).collect();
+                // Seed prev_atr from kand's batch ATR at the first valid index (= period).
+                let mut atr_out = vec![0.0; series.len()];
+                kand::ohlcv::atr::atr(&high, &low, &close, ATR_PERIOD, &mut atr_out).unwrap();
+                let seed_atr = atr_out[ATR_PERIOD];
+                bencher.iter(|| {
+                    let mut prev_atr = seed_atr;
+                    for idx in ATR_PERIOD + 1..series.len() {
+                        prev_atr = kand::ohlcv::atr::atr_inc(
+                            high[idx],
+                            low[idx],
+                            close[idx - 1],
+                            prev_atr,
+                            ATR_PERIOD,
+                        )
+                        .unwrap();
+                        black_box(prev_atr);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                let high: Vec<f64> = series.iter().map(|candle| candle.high).collect();
+                let low: Vec<f64> = series.iter().map(|candle| candle.low).collect();
+                let close: Vec<f64> = series.iter().map(|candle| candle.close).collect();
+                bencher.iter(|| {
+                    let mut atr_out = vec![0.0; series.len()];
+                    kand::ohlcv::atr::atr(&high, &low, &close, ATR_PERIOD, &mut atr_out).unwrap();
+                    black_box(&atr_out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                let items: Vec<ta::DataItem> = series
+                    .iter()
+                    .map(|candle| {
+                        ta::DataItem::builder()
+                            .open(candle.open)
+                            .high(candle.high)
+                            .low(candle.low)
+                            .close(candle.close)
+                            .volume(candle.volume)
+                            .build()
+                            .unwrap()
+                    })
+                    .collect();
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::AverageTrueRange::new(ATR_PERIOD).unwrap();
+                    for item in &items {
+                        black_box(ta::Next::next(&mut ind, item));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn benches(crit: &mut Criterion) {
+    let candles = load_candles();
+    let closes: Vec<f64> = candles.iter().map(|candle| candle.close).collect();
+    sma_group(crit, &closes);
+    ema_group(crit, &closes);
+    rsi_group(crit, &closes);
+    macd_group(crit, &closes);
+    bbands_group(crit, &closes);
+    atr_group(crit, &candles);
+}
+
+criterion_group!(name = cross_lib; config = Criterion::default(); targets = benches);
+criterion_main!(cross_lib);
@@ -0,0 +1,6 @@
+//! Internal cross-library benchmark harness for Wickra.
+//!
+//! This crate is `publish = false`. It exists only to host the Criterion
+//! benchmark in `benches/cross_lib.rs`, which compares Wickra against the
+//! Rust technical-analysis crates `kand`, `ta` (ta-rs) and `yata` on an
+//! identical candle series. It deliberately carries no library code.
@@ -0,0 +1,203 @@
+//! Pure calendar arithmetic for the timestamp-driven seasonality indicators.
+//!
+//! Every indicator in the *Seasonality & Session* family keys off the wall-clock
+//! fields of [`Candle::timestamp`](crate::Candle) (epoch milliseconds), shifted
+//! by a caller-supplied `utc_offset_minutes` so the buckets line up with the
+//! relevant exchange session rather than UTC. This module turns an epoch
+//! millisecond instant into its civil fields using Howard Hinnant's
+//! branch-light `civil_from_days` algorithm (the same one libc++ ships).
+//!
+//! All arithmetic is floor-based (`div_euclid`/`rem_euclid`) so instants before
+//! the Unix epoch decompose correctly without a dedicated negative-input branch.
+
+/// Civil (wall-clock) decomposition of an epoch-millisecond instant.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub(crate) struct CivilTime {
+    /// Proleptic Gregorian year (can be negative for instants before year 1).
+    pub(crate) year: i64,
+    /// Month of year, `1..=12`.
+    pub(crate) month: u32,
+    /// Day of month, `1..=31`.
+    pub(crate) day: u32,
+    /// Hour of day, `0..=23`.
+    pub(crate) hour: u32,
+    /// Minute of hour, `0..=59`.
+    pub(crate) minute: u32,
+    /// Day of week with Monday as `0` through Sunday as `6`.
+    pub(crate) weekday: u32,
+}
+
+impl CivilTime {
+    /// Minute of day, `0..=1439`.
+    pub(crate) const fn minute_of_day(&self) -> u32 {
+        self.hour * 60 + self.minute
+    }
+}
+
+/// Decompose an epoch-millisecond instant into local civil fields.
+///
+/// `utc_offset_minutes` shifts the instant before decomposition: `0` yields
+/// UTC, `-300` U.S. Eastern standard time, `60` Central European time, etc.
+pub(crate) fn civil_from_timestamp(millis: i64, utc_offset_minutes: i32) -> CivilTime {
+    let local_secs = millis.div_euclid(1000) + i64::from(utc_offset_minutes) * 60;
+    let days = local_secs.div_euclid(86_400);
+    let secs_of_day = local_secs.rem_euclid(86_400);
+    let hour = (secs_of_day / 3600) as u32;
+    let minute = ((secs_of_day % 3600) / 60) as u32;
+    let (year, month, day) = civil_from_days(days);
+    // 1970-01-01 was a Thursday; Monday-based weekday is `(z + 3) mod 7`.
+    let weekday = (days + 3).rem_euclid(7) as u32;
+    CivilTime {
+        year,
+        month,
+        day,
+        hour,
+        minute,
+        weekday,
+    }
+}
+
+/// Gregorian `(year, month, day)` for a day count `z` relative to 1970-01-01.
+///
+/// Howard Hinnant, "chrono-Compatible Low-Level Date Algorithms".
+fn civil_from_days(z: i64) -> (i64, u32, u32) {
+    let z = z + 719_468;
+    let era = if z >= 0 { z } else { z - 146_096 } / 146_097;
+    let doe = z - era * 146_097; // [0, 146096]
+    let yoe = (doe - doe / 1460 + doe / 36_524 - doe / 146_096) / 365; // [0, 399]
+    let year = yoe + era * 400;
+    let doy = doe - (365 * yoe + yoe / 4 - yoe / 100); // [0, 365]
+    let mp = (5 * doy + 2) / 153; // [0, 11]
+    let day = (doy - (153 * mp + 2) / 5 + 1) as u32; // [1, 31]
+    let month = if mp < 10 { mp + 3 } else { mp - 9 } as u32; // [1, 12]
+    (if month <= 2 { year + 1 } else { year }, month, day)
+}
+
+/// Whether `year` is a Gregorian leap year.
+pub(crate) const fn is_leap(year: i64) -> bool {
+    (year % 4 == 0 && year % 100 != 0) || year % 400 == 0
+}
+
+/// Number of days in `month` (`1..=12`) of `year`.
+pub(crate) const fn days_in_month(year: i64, month: u32) -> u32 {
+    match month {
+        1 | 3 | 5 | 7 | 8 | 10 | 12 => 31,
+        4 | 6 | 9 | 11 => 30,
+        _ => {
+            if is_leap(year) {
+                29
+            } else {
+                28
+            }
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn epoch_zero_is_thursday_midnight() {
+        let t = civil_from_timestamp(0, 0);
+        assert_eq!(
+            t,
+            CivilTime {
+                year: 1970,
+                month: 1,
+                day: 1,
+                hour: 0,
+                minute: 0,
+                weekday: 3, // Thursday
+            }
+        );
+        assert_eq!(t.minute_of_day(), 0);
+    }
+
+    #[test]
+    fn known_utc_instant_mid_year() {
+        // 2021-06-15 13:45:00 UTC = 1623764700 s.
+        let t = civil_from_timestamp(1_623_764_700_000, 0);
+        assert_eq!(t.year, 2021);
+        assert_eq!(t.month, 6);
+        assert_eq!(t.day, 15);
+        assert_eq!(t.hour, 13);
+        assert_eq!(t.minute, 45);
+        assert_eq!(t.weekday, 1); // Tuesday
+        assert_eq!(t.minute_of_day(), 13 * 60 + 45);
+    }
+
+    #[test]
+    fn new_year_2021_is_friday() {
+        // 2021-01-01 00:00:00 UTC = 1609459200 s — exercises the m<=2 year bump.
+        let t = civil_from_timestamp(1_609_459_200_000, 0);
+        assert_eq!((t.year, t.month, t.day), (2021, 1, 1));
+        assert_eq!(t.weekday, 4); // Friday
+    }
+
+    #[test]
+    fn positive_offset_rolls_to_next_day() {
+        // 2021-01-01 23:30 UTC shifted +60 min -> 2021-01-02 00:30 local.
+        let base = 1_609_459_200_000 + (23 * 3600 + 30 * 60) * 1000;
+        let t = civil_from_timestamp(base, 60);
+        assert_eq!((t.year, t.month, t.day), (2021, 1, 2));
+        assert_eq!((t.hour, t.minute), (0, 30));
+        assert_eq!(t.weekday, 5); // Saturday
+    }
+
+    #[test]
+    fn negative_offset_rolls_to_previous_day() {
+        // 2021-01-01 00:30 UTC shifted -60 min -> 2020-12-31 23:30 local.
+        let base = 1_609_459_200_000 + 30 * 60 * 1000;
+        let t = civil_from_timestamp(base, -60);
+        assert_eq!((t.year, t.month, t.day), (2020, 12, 31));
+        assert_eq!((t.hour, t.minute), (23, 30));
+        assert_eq!(t.weekday, 3); // Thursday
+    }
+
+    #[test]
+    fn sub_epoch_millis_floor_correctly() {
+        // -1 ms -> 1969-12-31 23:59:59.999, a Wednesday.
+        let t = civil_from_timestamp(-1, 0);
+        assert_eq!((t.year, t.month, t.day), (1969, 12, 31));
+        assert_eq!((t.hour, t.minute), (23, 59));
+        assert_eq!(t.weekday, 2); // Wednesday
+    }
+
+    #[test]
+    fn far_negative_day_count_hits_pre_era_branch() {
+        // A day count below -719468 drives `z + 719468` negative, exercising the
+        // `z - 146096` era branch in civil_from_days (year < 1).
+        let (year, month, day) = civil_from_days(-1_000_000);
+        // -1_000_000 days before 1970-01-01 is 0768-02-04 BCE (proleptic
+        // Gregorian, astronomical year numbering where year 0 exists).
+        assert_eq!((year, month, day), (-768, 2, 4));
+    }
+
+    #[test]
+    fn leap_year_rules() {
+        assert!(is_leap(2000));
+        assert!(!is_leap(1900));
+        assert!(is_leap(2024));
+        assert!(!is_leap(2023));
+    }
+
+    #[test]
+    fn days_in_month_all_cases() {
+        assert_eq!(days_in_month(2023, 1), 31);
+        assert_eq!(days_in_month(2023, 4), 30);
+        assert_eq!(days_in_month(2023, 2), 28);
+        assert_eq!(days_in_month(2024, 2), 29);
+        assert_eq!(days_in_month(2023, 12), 31);
+        assert_eq!(days_in_month(2023, 11), 30);
+    }
+
+    #[test]
+    fn leap_day_decodes() {
+        // 2024-02-29 12:00 UTC.
+        let secs = 1_709_208_000; // 2024-02-29T12:00:00Z
+        let t = civil_from_timestamp(secs * 1000, 0);
+        assert_eq!((t.year, t.month, t.day), (2024, 2, 29));
+        assert_eq!(t.hour, 12);
+    }
+}
@@ -0,0 +1,387 @@
+//! Cross-section value type: a market-breadth snapshot across a whole universe.
+//!
+//! A [`CrossSection`] is a single tick that carries the per-symbol state of
+//! *every* symbol in a universe at one point in time. It is the non-OHLCV input
+//! consumed by the market-breadth indicator family (advance/decline, `McClellan`,
+//! the TRIN / Arms index, the high-low index, ...), each of which aggregates the
+//! whole cross-section into a single breadth reading. This is the same
+//! one-rich-type-per-family pattern as [`DerivativesTick`] and [`OrderBook`].
+//!
+//! Each [`Member`] precomputes the per-symbol signals the breadth indicators
+//! need — a signed price `change` (whose sign classifies the symbol as
+//! advancing, declining or unchanged), the period `volume`, the
+//! `new_high` / `new_low` extreme flags, and the `above_ma` / `on_buy_signal`
+//! state flags — so the indicators stay stateless per tick and never have to
+//! track per-symbol history.
+//!
+//! [`DerivativesTick`]: crate::DerivativesTick
+//! [`OrderBook`]: crate::OrderBook
+
+use crate::error::{Error, Result};
+
+/// One symbol's contribution to a [`CrossSection`] tick.
+///
+/// Field invariants enforced by [`CrossSection::new`] when the member is placed
+/// into a tick:
+///
+/// - `change` is finite (its sign classifies the symbol — positive is
+///   advancing, negative is declining, zero is unchanged).
+/// - `volume` is finite and non-negative.
+///
+/// `new_high` / `new_low` are caller-supplied flags marking whether the symbol
+/// printed a new period extreme; `above_ma` / `on_buy_signal` are caller-supplied
+/// per-symbol state signals (whether the symbol trades above its reference moving
+/// average, and whether it is on a point-and-figure buy signal). None of the four
+/// flags carries a numeric invariant.
+#[non_exhaustive]
+#[derive(Debug, Clone, Copy, PartialEq)]
+#[allow(
+    clippy::struct_excessive_bools,
+    reason = "the four flags are independent per-symbol breadth signals, not a state machine"
+)]
+pub struct Member {
+    /// Price change versus the previous close. Sign classifies the symbol:
+    /// positive is advancing, negative is declining, zero is unchanged.
+    pub change: f64,
+    /// Period volume for the symbol (finite, non-negative).
+    pub volume: f64,
+    /// Whether the symbol printed a new period high.
+    pub new_high: bool,
+    /// Whether the symbol printed a new period low.
+    pub new_low: bool,
+    /// Whether the symbol is trading above its reference moving average
+    /// (consumed by the `% Above Moving Average` breadth indicator).
+    pub above_ma: bool,
+    /// Whether the symbol is on a point-and-figure buy signal
+    /// (consumed by the `Bullish Percent Index` breadth indicator).
+    pub on_buy_signal: bool,
+}
+
+impl Member {
+    /// Assemble a cross-section member from its core signals, leaving the
+    /// extended per-symbol state flags (`above_ma`, `on_buy_signal`) cleared.
+    ///
+    /// The field invariants documented on [`Member`] are validated centrally by
+    /// [`CrossSection::new`] when the member is placed into a tick; this
+    /// constructor only assembles the value so the `#[non_exhaustive]` struct can
+    /// be built from outside the crate.
+    #[must_use]
+    pub const fn new(change: f64, volume: f64, new_high: bool, new_low: bool) -> Self {
+        Self {
+            change,
+            volume,
+            new_high,
+            new_low,
+            above_ma: false,
+            on_buy_signal: false,
+        }
+    }
+
+    /// Assemble a cross-section member including the extended per-symbol state
+    /// signals `above_ma` and `on_buy_signal`.
+    ///
+    /// Use this constructor for the breadth indicators that read per-symbol
+    /// state (`% Above Moving Average`, `Bullish Percent Index`); [`new`](Member::new)
+    /// is the shorthand that leaves both flags `false`.
+    #[must_use]
+    #[allow(
+        clippy::fn_params_excessive_bools,
+        reason = "mirrors the four independent per-symbol flag fields of Member"
+    )]
+    pub const fn with_signals(
+        change: f64,
+        volume: f64,
+        new_high: bool,
+        new_low: bool,
+        above_ma: bool,
+        on_buy_signal: bool,
+    ) -> Self {
+        Self {
+            change,
+            volume,
+            new_high,
+            new_low,
+            above_ma,
+            on_buy_signal,
+        }
+    }
+}
+
+/// A market-breadth cross-section: the per-symbol state of an entire universe at
+/// a single point in time.
+///
+/// Invariants enforced by [`new`](CrossSection::new):
+///
+/// - `members` is non-empty (a breadth reading needs at least one symbol).
+/// - every member's `change` is finite, and `volume` is finite and non-negative.
+///
+/// `timestamp` is a caller-defined epoch / resolution and is not validated.
+#[non_exhaustive]
+#[derive(Debug, Clone, PartialEq)]
+pub struct CrossSection {
+    /// Per-symbol members of the universe for this tick.
+    pub members: Vec<Member>,
+    /// Tick timestamp (caller-defined epoch / resolution).
+    pub timestamp: i64,
+}
+
+impl CrossSection {
+    /// Construct a cross-section, validating every member invariant.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidCrossSection`] if `members` is empty, if any
+    /// member has a non-finite `change`, or if any member has a `volume` that is
+    /// not a finite non-negative number.
+    pub fn new(members: Vec<Member>, timestamp: i64) -> Result<Self> {
+        if members.is_empty() {
+            return Err(Error::InvalidCrossSection {
+                message: "cross-section must contain at least one member",
+            });
+        }
+        for member in &members {
+            if !member.change.is_finite() {
+                return Err(Error::InvalidCrossSection {
+                    message: "member change must be finite",
+                });
+            }
+            if !member.volume.is_finite() || member.volume < 0.0 {
+                return Err(Error::InvalidCrossSection {
+                    message: "member volume must be finite and non-negative",
+                });
+            }
+        }
+        Ok(Self { members, timestamp })
+    }
+
+    /// Construct a cross-section without validation. The caller asserts that
+    /// every invariant documented on [`CrossSection`] holds.
+    #[must_use]
+    pub const fn new_unchecked(members: Vec<Member>, timestamp: i64) -> Self {
+        Self { members, timestamp }
+    }
+
+    /// Number of advancing symbols (those with a strictly positive `change`).
+    #[must_use]
+    pub fn advancers(&self) -> usize {
+        self.members.iter().filter(|m| m.change > 0.0).count()
+    }
+
+    /// Number of declining symbols (those with a strictly negative `change`).
+    #[must_use]
+    pub fn decliners(&self) -> usize {
+        self.members.iter().filter(|m| m.change < 0.0).count()
+    }
+
+    /// Total volume traded by advancing symbols (those with positive `change`).
+    #[must_use]
+    pub fn advancing_volume(&self) -> f64 {
+        self.members
+            .iter()
+            .filter(|m| m.change > 0.0)
+            .map(|m| m.volume)
+            .sum()
+    }
+
+    /// Total volume traded by declining symbols (those with negative `change`).
+    #[must_use]
+    pub fn declining_volume(&self) -> f64 {
+        self.members
+            .iter()
+            .filter(|m| m.change < 0.0)
+            .map(|m| m.volume)
+            .sum()
+    }
+
+    /// Total volume traded across the whole universe.
+    #[must_use]
+    pub fn total_volume(&self) -> f64 {
+        self.members.iter().map(|m| m.volume).sum()
+    }
+
+    /// Number of symbols that printed a new period high.
+    #[must_use]
+    pub fn new_highs(&self) -> usize {
+        self.members.iter().filter(|m| m.new_high).count()
+    }
+
+    /// Number of symbols that printed a new period low.
+    #[must_use]
+    pub fn new_lows(&self) -> usize {
+        self.members.iter().filter(|m| m.new_low).count()
+    }
+
+    /// Number of symbols trading above their reference moving average.
+    #[must_use]
+    pub fn above_ma_count(&self) -> usize {
+        self.members.iter().filter(|m| m.above_ma).count()
+    }
+
+    /// Number of symbols on a point-and-figure buy signal.
+    #[must_use]
+    pub fn on_buy_signal_count(&self) -> usize {
+        self.members.iter().filter(|m| m.on_buy_signal).count()
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn members() -> Vec<Member> {
+        vec![
+            Member::new(1.5, 100.0, true, false),
+            Member::new(-0.5, 50.0, false, true),
+            Member::new(0.0, 0.0, false, false),
+        ]
+    }
+
+    #[test]
+    fn new_accepts_valid() {
+        let cs = CrossSection::new(members(), 42).unwrap();
+        assert_eq!(cs.members.len(), 3);
+        assert_eq!(cs.timestamp, 42);
+        assert_eq!(cs.members[0].change, 1.5);
+        assert_eq!(cs.members[0].volume, 100.0);
+        assert!(cs.members[0].new_high);
+        assert!(cs.members[1].new_low);
+    }
+
+    #[test]
+    fn member_new_assembles_fields() {
+        let m = Member::new(2.0, 10.0, true, false);
+        assert_eq!(m.change, 2.0);
+        assert_eq!(m.volume, 10.0);
+        assert!(m.new_high);
+        assert!(!m.new_low);
+    }
+
+    #[test]
+    fn new_rejects_empty() {
+        assert!(matches!(
+            CrossSection::new(Vec::new(), 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_change() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(f64::NAN, 10.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(f64::INFINITY, 10.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_negative_volume() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(1.0, -1.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_volume() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(1.0, f64::NAN, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_unchecked_skips_validation() {
+        let cs = CrossSection::new_unchecked(vec![Member::new(f64::NAN, -1.0, false, false)], 7);
+        assert_eq!(cs.members.len(), 1);
+        assert_eq!(cs.timestamp, 7);
+    }
+
+    #[test]
+    fn advancers_and_decliners_count_by_sign() {
+        let cs = CrossSection::new(members(), 0).unwrap();
+        assert_eq!(cs.advancers(), 1);
+        assert_eq!(cs.decliners(), 1);
+    }
+
+    #[test]
+    fn unchanged_members_count_as_neither() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(0.0, 1.0, false, false),
+                Member::new(0.0, 1.0, false, false),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.advancers(), 0);
+        assert_eq!(cs.decliners(), 0);
+    }
+
+    #[test]
+    fn new_leaves_extended_flags_cleared() {
+        let m = Member::new(1.0, 10.0, true, false);
+        assert!(!m.above_ma);
+        assert!(!m.on_buy_signal);
+    }
+
+    #[test]
+    fn with_signals_assembles_all_fields() {
+        let m = Member::with_signals(2.0, 10.0, true, false, true, true);
+        assert_eq!(m.change, 2.0);
+        assert_eq!(m.volume, 10.0);
+        assert!(m.new_high);
+        assert!(!m.new_low);
+        assert!(m.above_ma);
+        assert!(m.on_buy_signal);
+    }
+
+    #[test]
+    fn volume_helpers_bucket_by_change_sign() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(1.5, 100.0, false, false), // advancing
+                Member::new(2.0, 40.0, false, false),  // advancing
+                Member::new(-0.5, 50.0, false, false), // declining
+                Member::new(0.0, 7.0, false, false),   // unchanged
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.advancing_volume(), 140.0);
+        assert_eq!(cs.declining_volume(), 50.0);
+        assert_eq!(cs.total_volume(), 197.0);
+    }
+
+    #[test]
+    fn high_low_helpers_count_flags() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(1.0, 1.0, true, false),
+                Member::new(1.0, 1.0, true, false),
+                Member::new(-1.0, 1.0, false, true),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.new_highs(), 2);
+        assert_eq!(cs.new_lows(), 1);
+    }
+
+    #[test]
+    fn state_helpers_count_extended_flags() {
+        let cs = CrossSection::new(
+            vec![
+                Member::with_signals(1.0, 1.0, false, false, true, true),
+                Member::with_signals(1.0, 1.0, false, false, true, false),
+                Member::with_signals(-1.0, 1.0, false, false, false, true),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.above_ma_count(), 2);
+        assert_eq!(cs.on_buy_signal_count(), 2);
+    }
+}
@@ -0,0 +1,321 @@
+//! Derivatives value type: the perpetual / futures tick.
+//!
+//! [`DerivativesTick`] is the non-OHLCV input consumed by the derivatives /
+//! perpetual-futures indicator family. A single tick bundles the funding,
+//! price, open-interest, positioning, taker-flow and liquidation fields a
+//! perp/futures venue publishes per update; each indicator reads only the
+//! subset it needs (the same one-rich-type-per-family pattern as [`Trade`] /
+//! [`OrderBook`] in [`crate::microstructure`]).
+//!
+//! [`Trade`]: crate::microstructure::Trade
+//! [`OrderBook`]: crate::microstructure::OrderBook
+
+use crate::error::{Error, Result};
+
+/// A single derivatives / perpetual-futures market tick.
+///
+/// Field invariants enforced by [`new`](DerivativesTick::new):
+///
+/// - `funding_rate` is finite and **may be negative** (a negative funding rate
+///   means shorts pay longs).
+/// - `mark_price`, `index_price` and `futures_price` are finite and strictly
+///   positive.
+/// - `open_interest`, `long_size`, `short_size`, `taker_buy_volume`,
+///   `taker_sell_volume`, `long_liquidation` and `short_liquidation` are finite
+///   and non-negative.
+///
+/// `timestamp` is a caller-defined epoch / resolution and is not validated.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct DerivativesTick {
+    /// Current funding rate for the interval (finite; may be negative).
+    pub funding_rate: f64,
+    /// Perpetual mark price (finite, strictly positive).
+    pub mark_price: f64,
+    /// Spot / index price the perpetual tracks (finite, strictly positive).
+    pub index_price: f64,
+    /// Dated (e.g. quarterly) futures mark price (finite, strictly positive).
+    pub futures_price: f64,
+    /// Open interest — outstanding contracts / notional (finite, non-negative).
+    pub open_interest: f64,
+    /// Aggregate long size / long account count (finite, non-negative).
+    pub long_size: f64,
+    /// Aggregate short size / short account count (finite, non-negative).
+    pub short_size: f64,
+    /// Taker buy (ask-lifting) volume (finite, non-negative).
+    pub taker_buy_volume: f64,
+    /// Taker sell (bid-hitting) volume (finite, non-negative).
+    pub taker_sell_volume: f64,
+    /// Long-side liquidation notional (finite, non-negative).
+    pub long_liquidation: f64,
+    /// Short-side liquidation notional (finite, non-negative).
+    pub short_liquidation: f64,
+    /// Tick timestamp (caller-defined epoch / resolution).
+    pub timestamp: i64,
+}
+
+impl DerivativesTick {
+    /// Construct a derivatives tick, validating every field invariant.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidDerivatives`] if `funding_rate` is not finite;
+    /// any of `mark_price`, `index_price`, `futures_price` is not a finite
+    /// positive number; or any of the six size / volume / liquidation fields is
+    /// not a finite non-negative number.
+    #[allow(clippy::too_many_arguments)]
+    pub fn new(
+        funding_rate: f64,
+        mark_price: f64,
+        index_price: f64,
+        futures_price: f64,
+        open_interest: f64,
+        long_size: f64,
+        short_size: f64,
+        taker_buy_volume: f64,
+        taker_sell_volume: f64,
+        long_liquidation: f64,
+        short_liquidation: f64,
+        timestamp: i64,
+    ) -> Result<Self> {
+        if !funding_rate.is_finite() {
+            return Err(Error::InvalidDerivatives {
+                message: "funding_rate must be finite",
+            });
+        }
+        for price in [mark_price, index_price, futures_price] {
+            if !price.is_finite() || price <= 0.0 {
+                return Err(Error::InvalidDerivatives {
+                    message:
+                        "mark_price, index_price and futures_price must be finite and positive",
+                });
+            }
+        }
+        for amount in [
+            open_interest,
+            long_size,
+            short_size,
+            taker_buy_volume,
+            taker_sell_volume,
+            long_liquidation,
+            short_liquidation,
+        ] {
+            if !amount.is_finite() || amount < 0.0 {
+                return Err(Error::InvalidDerivatives {
+                    message: "open interest, sizes, volumes and liquidations must be finite and non-negative",
+                });
+            }
+        }
+        Ok(Self {
+            funding_rate,
+            mark_price,
+            index_price,
+            futures_price,
+            open_interest,
+            long_size,
+            short_size,
+            taker_buy_volume,
+            taker_sell_volume,
+            long_liquidation,
+            short_liquidation,
+            timestamp,
+        })
+    }
+
+    /// Construct a derivatives tick without validation. The caller asserts that
+    /// every field invariant documented on [`DerivativesTick`] holds.
+    #[allow(clippy::too_many_arguments)]
+    #[must_use]
+    pub const fn new_unchecked(
+        funding_rate: f64,
+        mark_price: f64,
+        index_price: f64,
+        futures_price: f64,
+        open_interest: f64,
+        long_size: f64,
+        short_size: f64,
+        taker_buy_volume: f64,
+        taker_sell_volume: f64,
+        long_liquidation: f64,
+        short_liquidation: f64,
+        timestamp: i64,
+    ) -> Self {
+        Self {
+            funding_rate,
+            mark_price,
+            index_price,
+            futures_price,
+            open_interest,
+            long_size,
+            short_size,
+            taker_buy_volume,
+            taker_sell_volume,
+            long_liquidation,
+            short_liquidation,
+            timestamp,
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    /// A fully valid tick used as a baseline; individual tests override one
+    /// field to exercise a single reject branch.
+    fn valid() -> DerivativesTick {
+        DerivativesTick::new(
+            0.0001, 100.0, 99.5, 100.5, 1_000.0, 600.0, 400.0, 50.0, 40.0, 5.0, 3.0, 42,
+        )
+        .unwrap()
+    }
+
+    #[test]
+    fn new_accepts_valid() {
+        let tick = valid();
+        assert_eq!(tick.funding_rate, 0.0001);
+        assert_eq!(tick.mark_price, 100.0);
+        assert_eq!(tick.index_price, 99.5);
+        assert_eq!(tick.futures_price, 100.5);
+        assert_eq!(tick.open_interest, 1_000.0);
+        assert_eq!(tick.long_size, 600.0);
+        assert_eq!(tick.short_size, 400.0);
+        assert_eq!(tick.taker_buy_volume, 50.0);
+        assert_eq!(tick.taker_sell_volume, 40.0);
+        assert_eq!(tick.long_liquidation, 5.0);
+        assert_eq!(tick.short_liquidation, 3.0);
+        assert_eq!(tick.timestamp, 42);
+    }
+
+    #[test]
+    fn new_accepts_negative_funding_and_zero_amounts() {
+        let tick = DerivativesTick::new(
+            -0.0005, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
+        )
+        .unwrap();
+        assert_eq!(tick.funding_rate, -0.0005);
+        assert_eq!(tick.open_interest, 0.0);
+    }
+
+    #[test]
+    fn new_rejects_non_finite_funding() {
+        assert!(matches!(
+            DerivativesTick::new(
+                f64::NAN,
+                100.0,
+                100.0,
+                100.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0
+            ),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+        assert!(matches!(
+            DerivativesTick::new(
+                f64::INFINITY,
+                100.0,
+                100.0,
+                100.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0
+            ),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_positive_mark() {
+        assert!(matches!(
+            DerivativesTick::new(0.0, 0.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_positive_index() {
+        assert!(matches!(
+            DerivativesTick::new(0.0, 100.0, -1.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_futures() {
+        assert!(matches!(
+            DerivativesTick::new(
+                0.0,
+                100.0,
+                100.0,
+                f64::NAN,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0
+            ),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_negative_open_interest() {
+        assert!(matches!(
+            DerivativesTick::new(0.0, 100.0, 100.0, 100.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_size() {
+        assert!(matches!(
+            DerivativesTick::new(
+                0.0,
+                100.0,
+                100.0,
+                100.0,
+                0.0,
+                f64::INFINITY,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+                0
+            ),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_negative_liquidation() {
+        assert!(matches!(
+            DerivativesTick::new(0.0, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.0, 0),
+            Err(Error::InvalidDerivatives { .. })
+        ));
+    }
+
+    #[test]
+    fn new_unchecked_preserves_fields() {
+        let tick = DerivativesTick::new_unchecked(
+            -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0, -9.0, -10.0, -11.0, 7,
+        );
+        assert_eq!(tick.funding_rate, -1.0);
+        assert_eq!(tick.mark_price, -2.0);
+        assert_eq!(tick.short_liquidation, -11.0);
+        assert_eq!(tick.timestamp, 7);
+    }
+}
@@ -31,6 +31,42 @@ pub enum Error {
    /// A multiplier or factor must be strictly positive.
    #[error("multiplier must be greater than zero")]
    NonPositiveMultiplier,
+
+    /// An order-book snapshot whose levels do not satisfy the book invariants
+    /// (e.g. a crossed book, non-finite price, negative size, or mis-sorted
+    /// levels) was provided. Order books are a microstructure input distinct
+    /// from candles and ticks, so they surface as their own variant.
+    #[error("invalid order book: {message}")]
+    InvalidOrderBook { message: &'static str },
+
+    /// A trade whose components do not satisfy the trade invariants (e.g.
+    /// non-finite price or negative size) was provided.
+    #[error("invalid trade: {message}")]
+    InvalidTrade { message: &'static str },
+
+    /// A derivatives tick whose components do not satisfy the tick invariants
+    /// (e.g. a non-positive price, a non-finite funding rate, or a negative
+    /// size/volume/liquidation) was provided. Derivatives ticks (funding /
+    /// open-interest / liquidation feeds) are a perpetual-futures input
+    /// distinct from candles, order books and trades, so they surface as their
+    /// own variant.
+    #[error("invalid derivatives tick: {message}")]
+    InvalidDerivatives { message: &'static str },
+
+    /// A market-breadth cross-section whose members do not satisfy the
+    /// cross-section invariants (an empty universe, a non-finite change, or a
+    /// negative / non-finite volume) was provided. A cross-section is a
+    /// breadth input distinct from candles, ticks, order books and trades, so
+    /// it surfaces as its own variant.
+    #[error("invalid cross-section: {message}")]
+    InvalidCrossSection { message: &'static str },
+
+    /// A real-valued configuration parameter was outside its admissible range
+    /// (e.g. a non-positive standard-deviation multiplier, or a Kalman filter
+    /// covariance that is not strictly positive). This is the floating-point
+    /// analogue of [`Error::InvalidPeriod`], which only covers integer windows.
+    #[error("invalid parameter: {message}")]
+    InvalidParameter { message: &'static str },
 }

 /// Convenience alias for `Result<T, wickra_core::Error>`.
@@ -0,0 +1,247 @@
+//! Abandoned Baby candlestick pattern.
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Abandoned Baby — a strong 3-bar reversal where a doji is "abandoned" by price
+/// gaps on both sides, isolating it from the candles before and after.
+///
+/// ```text
+/// tol           = tolerance * max(|bar2.open|, |bar2.close|)
+/// bar2 doji                                   (|bar2.close − bar2.open| <= tol)
+///
+/// bullish  (+1.0): bar1 red, bar2 gaps fully below bar1 (bar2.high < bar1.low),
+///                  bar3 green and gaps fully above bar2 (bar3.low > bar2.high)
+/// bearish  (−1.0): bar1 green, bar2 gaps fully above bar1 (bar2.low > bar1.high),
+///                  bar3 red and gaps fully below bar2 (bar3.high < bar2.low)
+/// ```
+///
+/// Output is `0.0` otherwise. The first two bars always return `0.0` because the
+/// three-bar window is not yet filled. `tolerance` defaults to `0.001` (10 bps
+/// relative) and bounds how flat the middle candle must be to count as a doji; it
+/// must lie in `[0, 1)`. Pattern-shape check only — no trend filter is applied;
+/// combine with a trend indicator for actionable signals.
+///
+/// # Signed ±1 encoding
+///
+/// This detector emits the uniform candlestick sign convention shared across the
+/// pattern family — `+1.0` bullish, `−1.0` bearish, `0.0` no pattern — so it
+/// drops straight into a machine-learning feature matrix where the bullish and
+/// bearish variants occupy a single dimension.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AbandonedBaby, Candle, Indicator};
+///
+/// let mut indicator = AbandonedBaby::new();
+/// indicator.update(Candle::new(20.0, 20.1, 14.9, 15.0, 1.0, 0).unwrap());
+/// indicator.update(Candle::new(13.0, 13.1, 12.9, 13.0, 1.0, 1).unwrap());
+/// let out = indicator
+///     .update(Candle::new(16.0, 18.1, 15.9, 18.0, 1.0, 2).unwrap());
+/// assert_eq!(out, Some(1.0));
+/// ```
+#[derive(Debug, Clone)]
+pub struct AbandonedBaby {
+    tolerance: f64,
+    prev: Option<Candle>,
+    prev_prev: Option<Candle>,
+    has_emitted: bool,
+}
+
+impl Default for AbandonedBaby {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl AbandonedBaby {
+    /// Construct a detector with the default relative doji tolerance (1e-3).
+    pub const fn new() -> Self {
+        Self {
+            tolerance: 0.001,
+            prev: None,
+            prev_prev: None,
+            has_emitted: false,
+        }
+    }
+
+    /// Construct a detector with a custom relative doji tolerance.
+    ///
+    /// `tolerance` must lie in `[0, 1)`.
+    pub fn with_tolerance(tolerance: f64) -> Result<Self> {
+        if !(0.0..1.0).contains(&tolerance) {
+            return Err(Error::InvalidPeriod {
+                message: "abandoned baby tolerance must lie in [0, 1)",
+            });
+        }
+        Ok(Self {
+            tolerance,
+            prev: None,
+            prev_prev: None,
+            has_emitted: false,
+        })
+    }
+
+    /// Configured relative doji tolerance.
+    pub fn tolerance(&self) -> f64 {
+        self.tolerance
+    }
+}
+
+impl Indicator for AbandonedBaby {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let pp = self.prev_prev;
+        let p = self.prev;
+        self.prev_prev = self.prev;
+        self.prev = Some(candle);
+        let (Some(bar1), Some(bar2)) = (pp, p) else {
+            return Some(0.0);
+        };
+        let tol = self.tolerance * bar2.open.abs().max(bar2.close.abs());
+        let bar2_is_doji = (bar2.close - bar2.open).abs() <= tol;
+        if !bar2_is_doji {
+            return Some(0.0);
+        }
+        // Bullish: red bar1, doji gaps below, green bar3 gaps above.
+        if bar1.close < bar1.open
+            && bar2.high < bar1.low
+            && candle.close > candle.open
+            && candle.low > bar2.high
+        {
+            return Some(1.0);
+        }
+        // Bearish: green bar1, doji gaps above, red bar3 gaps below.
+        if bar1.close > bar1.open
+            && bar2.low > bar1.high
+            && candle.close < candle.open
+            && candle.high < bar2.low
+        {
+            return Some(-1.0);
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        self.prev_prev = None;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AbandonedBaby"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn rejects_invalid_tolerance() {
+        assert!(AbandonedBaby::with_tolerance(-0.01).is_err());
+        assert!(AbandonedBaby::with_tolerance(1.0).is_err());
+    }
+
+    #[test]
+    fn accepts_valid_tolerance() {
+        let t = AbandonedBaby::with_tolerance(0.0).unwrap();
+        assert!((t.tolerance() - 0.0).abs() < 1e-12);
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = AbandonedBaby::default();
+        assert_eq!(t.name(), "AbandonedBaby");
+        assert_eq!(t.warmup_period(), 3);
+        assert!(!t.is_ready());
+        assert!((t.tolerance() - 0.001).abs() < 1e-12);
+    }
+
+    #[test]
+    fn bullish_abandoned_baby_is_plus_one() {
+        let mut t = AbandonedBaby::new();
+        assert_eq!(t.update(c(20.0, 20.1, 14.9, 15.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(13.0, 13.1, 12.9, 13.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(16.0, 18.1, 15.9, 18.0, 2)), Some(1.0));
+    }
+
+    #[test]
+    fn bearish_abandoned_baby_is_minus_one() {
+        let mut t = AbandonedBaby::new();
+        assert_eq!(t.update(c(15.0, 20.1, 14.9, 20.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(22.0, 22.1, 21.9, 22.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(19.0, 19.1, 16.9, 17.0, 2)), Some(-1.0));
+    }
+
+    #[test]
+    fn middle_not_doji_yields_zero() {
+        let mut t = AbandonedBaby::new();
+        t.update(c(20.0, 20.1, 14.9, 15.0, 0));
+        // Middle bar has a wide body -> not a doji.
+        assert_eq!(t.update(c(13.0, 14.0, 11.0, 11.5, 1)), Some(0.0));
+        assert_eq!(t.update(c(16.0, 18.1, 15.9, 18.0, 2)), Some(0.0));
+    }
+
+    #[test]
+    fn no_gap_yields_zero() {
+        let mut t = AbandonedBaby::new();
+        t.update(c(20.0, 20.1, 14.9, 15.0, 0));
+        // Doji overlaps bar1's range -> no gap.
+        assert_eq!(t.update(c(15.0, 15.1, 14.9, 15.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(16.0, 18.1, 15.9, 18.0, 2)), Some(0.0));
+    }
+
+    #[test]
+    fn first_two_bars_return_zero() {
+        let mut t = AbandonedBaby::new();
+        assert_eq!(t.update(c(20.0, 20.1, 14.9, 15.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(13.0, 13.1, 12.9, 13.0, 1)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + (i as f64 * 0.3).sin() * 5.0;
+                c(base, base + 1.0, base - 1.0, base + 0.5, i)
+            })
+            .collect();
+        let mut a = AbandonedBaby::new();
+        let mut b = AbandonedBaby::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = AbandonedBaby::new();
+        t.update(c(20.0, 20.1, 14.9, 15.0, 0));
+        t.update(c(13.0, 13.1, 12.9, 13.0, 1));
+        t.update(c(16.0, 18.1, 15.9, 18.0, 2));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.update(c(20.0, 20.1, 14.9, 15.0, 0)), Some(0.0));
+    }
+}
@@ -0,0 +1,154 @@
+//! AB=CD harmonic pattern.
+
+use crate::indicators::pattern_swing::{approx_equal, ratios_in, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// AB=CD — the simplest four-point harmonic pattern: an A→B leg, a B→C
+/// retracement, and a C→D leg that mirrors A→B in length:
+///
+/// ```text
+/// BC / AB ∈ [0.382, 0.886]   (C retraces AB)
+/// CD / BC ∈ [1.13, 2.618]    (D extends BC)
+/// AB ≈ CD (within 10%)        (the two legs are equal — the defining symmetry)
+/// ```
+///
+/// Read from the last four confirmed pivots `A-B-C-D`. Output is `+1.0`
+/// (bullish, D a swing low), `-1.0` (bearish, D a swing high), or `0.0`; never
+/// `None`. See `crates/wickra-core/src/indicators/abcd.rs`.
+#[derive(Debug, Clone)]
+pub struct Abcd {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Abcd {
+    /// Construct a new AB=CD detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 4),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Abcd {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Abcd {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 4 {
+            return Some(0.0);
+        }
+        let len = pivots.len();
+        let pa = pivots[len - 4];
+        let pb = pivots[len - 3];
+        let pc = pivots[len - 2];
+        let pd = pivots[len - 1];
+        let ab = (pb.price - pa.price).abs();
+        let bc = (pc.price - pb.price).abs();
+        let cd = (pd.price - pc.price).abs();
+        let ratios_ok = ratios_in(&[(bc / ab, 0.382, 0.886), (cd / bc, 1.13, 2.618)]);
+        let legs_equal = approx_equal(ab, cd, 0.10);
+        if ratios_ok && legs_equal {
+            return Some(if pd.direction < 0.0 { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        5
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Abcd"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Abcd::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Abcd::new();
+        assert_eq!(indicator.name(), "Abcd");
+        assert_eq!(indicator.warmup_period(), 5);
+        assert!(!indicator.is_ready());
+        assert!(!Abcd::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_abcd_is_plus_one() {
+        // AB = 40 down, BC = 24.7 up (0.618), CD = 40 down → AB = CD.
+        let out = run(&[140.0, 100.0, 124.7, 84.7]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_abcd_is_minus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 115.3, 155.3]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn unequal_legs_do_not_trigger() {
+        // CD (82) far longer than AB (40) → not an AB=CD.
+        let out = run(&[150.0, 100.0, 140.0, 118.0, 200.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Abcd::new();
+        for c in candles_for_pivots(&[140.0, 100.0, 124.7]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[140.0, 100.0, 124.7, 84.7]);
+        let mut a = Abcd::new();
+        let mut b = Abcd::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,144 @@
+//! Absolute Breadth Index — the magnitude of net advancing-minus-declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Absolute Breadth Index (ABI) — the absolute value of net advancing issues,
+/// `|advancers - decliners|`.
+///
+/// The ABI ignores the *direction* of breadth and measures only its *magnitude*:
+/// a high reading means the universe moved decisively one way or the other (high
+/// internal activity / volatility), while a low reading means advances and
+/// declines were nearly balanced (a quiet, directionless market). It is sometimes
+/// called a "market thermometer" because elevated readings often cluster around
+/// turning points.
+///
+/// `Input = CrossSection`, `Output = f64`, `warmup_period == 1`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AbsoluteBreadthIndex, CrossSection, Indicator, Member};
+///
+/// let mut abi = AbsoluteBreadthIndex::new();
+/// // 2 advancers, 5 decliners -> |2 - 5| = 3.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(abi.update(tick), Some(3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AbsoluteBreadthIndex {
+    has_emitted: bool,
+}
+
+impl AbsoluteBreadthIndex {
+    /// Construct a new Absolute Breadth Index indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AbsoluteBreadthIndex {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancers() as f64 - section.decliners() as f64;
+        self.has_emitted = true;
+        Some(net.abs())
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AbsoluteBreadthIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.name(), "AbsoluteBreadthIndex");
+        assert_eq!(abi.warmup_period(), 1);
+        assert!(!abi.is_ready());
+    }
+
+    #[test]
+    fn magnitude_ignores_direction() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.update(section(2, 5)), Some(3.0));
+        // Same magnitude with the direction reversed.
+        let mut abi2 = AbsoluteBreadthIndex::new();
+        assert_eq!(abi2.update(section(5, 2)), Some(3.0));
+    }
+
+    #[test]
+    fn balanced_universe_yields_zero() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.update(section(3, 3)), Some(0.0));
+        assert!(abi.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        abi.update(section(2, 5));
+        assert!(abi.is_ready());
+        abi.reset();
+        assert!(!abi.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(2, 5), section(5, 2), section(3, 3)];
+        let mut a = AbsoluteBreadthIndex::new();
+        let mut b = AbsoluteBreadthIndex::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,157 @@
+//! Advance/Decline Volume Line — cumulative net advancing-minus-declining volume.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Volume Line (AD Volume Line) — the running cumulative sum of
+/// net advancing volume across a universe.
+///
+/// On each [`CrossSection`] tick the net is `advancing volume - declining volume`,
+/// where advancing volume is the total volume of symbols with a positive change
+/// and declining volume the total volume of symbols with a negative change. The
+/// line accumulates this net over time, so a rising line means volume is flowing
+/// into advancing issues (healthy participation) while a falling line warns that
+/// declining issues are carrying the volume — the volume-weighted analogue of the
+/// plain Advance/Decline Line.
+///
+/// `Input = CrossSection`, `Output = f64`, `warmup_period == 1` (defined from the
+/// first tick).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdVolumeLine, CrossSection, Indicator, Member};
+///
+/// let mut adv = AdVolumeLine::new();
+/// // advancing volume 150, declining volume 50 -> net +100.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 150.0, false, false),
+///         Member::new(-1.0, 50.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(adv.update(tick), Some(100.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdVolumeLine {
+    line: f64,
+    has_emitted: bool,
+}
+
+impl AdVolumeLine {
+    /// Construct a new Advance/Decline Volume Line indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            line: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for AdVolumeLine {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancing_volume() - section.declining_volume();
+        self.line += net;
+        self.has_emitted = true;
+        Some(self.line)
+    }
+
+    fn reset(&mut self) {
+        self.line = 0.0;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdVolumeLine"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn tick(items: &[(f64, f64)]) -> CrossSection {
+        CrossSection::new(
+            items
+                .iter()
+                .map(|&(change, volume)| Member::new(change, volume, false, false))
+                .collect(),
+            0,
+        )
+        .unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let adv = AdVolumeLine::new();
+        assert_eq!(adv.name(), "AdVolumeLine");
+        assert_eq!(adv.warmup_period(), 1);
+        assert!(!adv.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_net_volume() {
+        let mut adv = AdVolumeLine::new();
+        assert_eq!(adv.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(100.0));
+        assert!(adv.is_ready());
+    }
+
+    #[test]
+    fn line_accumulates_across_ticks() {
+        let mut adv = AdVolumeLine::new();
+        assert_eq!(adv.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(100.0));
+        assert_eq!(adv.update(tick(&[(1.0, 60.0), (-1.0, 60.0)])), Some(100.0));
+        assert_eq!(adv.update(tick(&[(1.0, 30.0)])), Some(130.0));
+    }
+
+    #[test]
+    fn unchanged_volume_is_ignored() {
+        let mut adv = AdVolumeLine::new();
+        // Unchanged symbols (zero change) contribute to neither bucket.
+        assert_eq!(adv.update(tick(&[(0.0, 1000.0), (1.0, 10.0)])), Some(10.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adv = AdVolumeLine::new();
+        adv.update(tick(&[(1.0, 100.0)]));
+        assert!(adv.is_ready());
+        adv.reset();
+        assert!(!adv.is_ready());
+        assert_eq!(adv.update(tick(&[(1.0, 20.0)])), Some(20.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![
+            tick(&[(1.0, 150.0), (-1.0, 50.0)]),
+            tick(&[(1.0, 60.0), (-1.0, 60.0)]),
+            tick(&[(1.0, 30.0)]),
+        ];
+        let mut a = AdVolumeLine::new();
+        let mut b = AdVolumeLine::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,344 @@
+//! Ehlers' Adaptive Laguerre Filter.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// John Ehlers' Adaptive Laguerre Filter — a four-stage Laguerre polynomial
+/// smoother whose damping factor `gamma` is recomputed every bar from how well
+/// the filter is currently tracking price.
+///
+/// The Laguerre cascade is the same one used by [`LaguerreRsi`](crate::LaguerreRsi),
+/// but instead of a fixed `gamma` the filter adapts: it measures the recent
+/// absolute error `|price − filter|`, normalises those errors across a window of
+/// `period` bars to `[0, 1]`, and takes their **median** as `gamma`. When price
+/// is tracking smoothly the errors are small and uniform (low `gamma`, fast
+/// response); when price jumps, the spread of errors widens and `gamma` rises,
+/// slowing the filter to reject the noise.
+///
+/// ```text
+/// diff_t  = |price_t − filter_{t-1}|
+/// over the last `period` diffs:
+///   HH = max(diff),  LL = min(diff)
+///   norm_i = (diff_i − LL) / (HH − LL)      (0 if HH == LL)
+///   gamma  = median(norm)
+/// alpha   = 1 − gamma
+/// L0_t = alpha·price_t + gamma·L0_{t-1}
+/// L1_t = −gamma·L0_t + L0_{t-1} + gamma·L1_{t-1}
+/// L2_t = −gamma·L1_t + L1_{t-1} + gamma·L2_{t-1}
+/// L3_t = −gamma·L2_t + L2_{t-1} + gamma·L3_{t-1}
+/// filter_t = (L0_t + 2·L1_t + 2·L2_t + L3_t) / 6
+/// ```
+///
+/// The output is a smoothed price on the same scale as the input. The first
+/// emission lands once the error window holds `period` values.
+///
+/// Reference: John F. Ehlers, *"Adaptive Laguerre Filter"*, Technical Analysis
+/// of Stocks & Commodities, 2007.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, AdaptiveLaguerreFilter};
+///
+/// let mut indicator = AdaptiveLaguerreFilter::new(13).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + f64::from(i));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct AdaptiveLaguerreFilter {
+    period: usize,
+    l0: f64,
+    l1: f64,
+    l2: f64,
+    l3: f64,
+    /// Previous filter output, or `None` before the first bar.
+    filter: Option<f64>,
+    /// The last `period` absolute errors `|price − filter|`.
+    diffs: VecDeque<f64>,
+}
+
+impl AdaptiveLaguerreFilter {
+    /// Construct a new adaptive Laguerre filter with the given error-window
+    /// length.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            l0: 0.0,
+            l1: 0.0,
+            l2: 0.0,
+            l3: 0.0,
+            filter: None,
+            diffs: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured error-window length.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if the error window is full.
+    pub fn value(&self) -> Option<f64> {
+        if self.diffs.len() == self.period {
+            self.filter
+        } else {
+            None
+        }
+    }
+
+    /// Median of the normalised errors currently in the window. Returns `0.0`
+    /// when every error is equal (e.g. during a constant warmup), which makes
+    /// the filter maximally fast.
+    fn adaptive_gamma(&self) -> f64 {
+        let mut hh = f64::MIN;
+        let mut ll = f64::MAX;
+        for &d in &self.diffs {
+            if d > hh {
+                hh = d;
+            }
+            if d < ll {
+                ll = d;
+            }
+        }
+        let range = hh - ll;
+        if range <= 0.0 {
+            return 0.0;
+        }
+        let mut norm: Vec<f64> = self.diffs.iter().map(|&d| (d - ll) / range).collect();
+        // `total_cmp` never panics — under pathological (e.g. overflowing) fuzz
+        // inputs a normalised error can be non-finite; a total order keeps the
+        // sort sound where `partial_cmp` would return `None`.
+        norm.sort_by(f64::total_cmp);
+        let mid = norm.len() / 2;
+        if norm.len() % 2 == 1 {
+            norm[mid]
+        } else {
+            f64::midpoint(norm[mid - 1], norm[mid])
+        }
+    }
+}
+
+impl Indicator for AdaptiveLaguerreFilter {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, price: f64) -> Option<f64> {
+        if !price.is_finite() {
+            return self.value();
+        }
+        // Absolute tracking error against the previous filter (0 on the first
+        // bar, where there is no prior filter value).
+        let diff = self.filter.map_or(0.0, |f| (price - f).abs());
+        if self.diffs.len() == self.period {
+            self.diffs.pop_front();
+        }
+        self.diffs.push_back(diff);
+
+        let gamma = self.adaptive_gamma();
+        let alpha = 1.0 - gamma;
+
+        let l0 = alpha * price + gamma * self.l0;
+        let l1 = -gamma * l0 + self.l0 + gamma * self.l1;
+        let l2 = -gamma * l1 + self.l1 + gamma * self.l2;
+        let l3 = -gamma * l2 + self.l2 + gamma * self.l3;
+        self.l0 = l0;
+        self.l1 = l1;
+        self.l2 = l2;
+        self.l3 = l3;
+
+        let filter = (l0 + 2.0 * l1 + 2.0 * l2 + l3) / 6.0;
+        self.filter = Some(filter);
+        self.value()
+    }
+
+    fn reset(&mut self) {
+        self.l0 = 0.0;
+        self.l1 = 0.0;
+        self.l2 = 0.0;
+        self.l3 = 0.0;
+        self.filter = None;
+        self.diffs.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.diffs.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "AdaptiveLaguerre"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    /// Independent reference: replays the exact recurrence from scratch.
+    fn naive(prices: &[f64], period: usize) -> Vec<Option<f64>> {
+        let (mut l0, mut l1, mut l2, mut l3) = (0.0_f64, 0.0_f64, 0.0_f64, 0.0_f64);
+        let mut filter: Option<f64> = None;
+        let mut diffs: Vec<f64> = Vec::new();
+        let mut out = Vec::with_capacity(prices.len());
+        for &price in prices {
+            let diff = filter.map_or(0.0, |f: f64| (price - f).abs());
+            diffs.push(diff);
+            if diffs.len() > period {
+                diffs.remove(0);
+            }
+            let hh = diffs.iter().copied().fold(f64::MIN, f64::max);
+            let ll = diffs.iter().copied().fold(f64::MAX, f64::min);
+            let range = hh - ll;
+            let gamma = if range <= 0.0 {
+                0.0
+            } else {
+                let mut norm: Vec<f64> = diffs.iter().map(|&d| (d - ll) / range).collect();
+                norm.sort_by(|a, b| a.partial_cmp(b).unwrap());
+                let mid = norm.len() / 2;
+                if norm.len() % 2 == 1 {
+                    norm[mid]
+                } else {
+                    f64::midpoint(norm[mid - 1], norm[mid])
+                }
+            };
+            let alpha = 1.0 - gamma;
+            let n0 = alpha * price + gamma * l0;
+            let n1 = -gamma * n0 + l0 + gamma * l1;
+            let n2 = -gamma * n1 + l1 + gamma * l2;
+            let n3 = -gamma * n2 + l2 + gamma * l3;
+            l0 = n0;
+            l1 = n1;
+            l2 = n2;
+            l3 = n3;
+            let f = (n0 + 2.0 * n1 + 2.0 * n2 + n3) / 6.0;
+            filter = Some(f);
+            out.push(if diffs.len() == period { Some(f) } else { None });
+        }
+        out
+    }
+
+    #[test]
+    fn new_rejects_zero_period() {
+        assert!(matches!(
+            AdaptiveLaguerreFilter::new(0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    /// Cover the const accessor `period` and the Indicator-impl `warmup_period`
+    /// + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let alf = AdaptiveLaguerreFilter::new(13).unwrap();
+        assert_eq!(alf.period(), 13);
+        assert_eq!(alf.warmup_period(), 13);
+        assert_eq!(alf.name(), "AdaptiveLaguerre");
+    }
+
+    #[test]
+    fn warmup_returns_none_until_window_full() {
+        let mut alf = AdaptiveLaguerreFilter::new(3).unwrap();
+        assert_eq!(alf.update(10.0), None);
+        assert_eq!(alf.update(11.0), None);
+        assert!(alf.update(12.0).is_some());
+    }
+
+    #[test]
+    fn constant_series_converges_to_constant() {
+        // Errors are all zero -> gamma 0 -> the 4-stage delay line fills with
+        // the constant and the filter settles on it.
+        let mut alf = AdaptiveLaguerreFilter::new(5).unwrap();
+        let out = alf.batch(&[42.0_f64; 40]);
+        let last = out.iter().rev().flatten().next().unwrap();
+        assert_relative_eq!(*last, 42.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn converged_output_stays_within_price_range() {
+        // Once the Laguerre cascade has filled (it cold-starts from zero, so the
+        // first few post-warmup values ramp up toward price), the filter is a
+        // convex blend of recent prices and must stay inside the data range.
+        let prices: Vec<f64> = (0..120)
+            .map(|i| 50.0 + (f64::from(i) * 0.4).sin() * 10.0)
+            .collect();
+        let lo = prices.iter().copied().fold(f64::MAX, f64::min);
+        let hi = prices.iter().copied().fold(f64::MIN, f64::max);
+        let period = 8;
+        let mut alf = AdaptiveLaguerreFilter::new(period).unwrap();
+        for (i, v) in alf.batch(&prices).into_iter().enumerate() {
+            // Skip the cold-start transient (a few multiples of the window).
+            if i < 4 * period {
+                continue;
+            }
+            let v = v.expect("filter is ready well past warmup");
+            assert!(
+                v >= lo - 1e-6 && v <= hi + 1e-6,
+                "filter out of range at {i}"
+            );
+        }
+    }
+
+    #[test]
+    fn matches_naive_recurrence() {
+        let prices: Vec<f64> = (0..80)
+            .map(|i| 100.0 + (f64::from(i) * 0.5).sin() * 8.0 + f64::from(i) * 0.1)
+            .collect();
+        let mut alf = AdaptiveLaguerreFilter::new(10).unwrap();
+        let got = alf.batch(&prices);
+        let want = naive(&prices, 10);
+        for (i, (g, w)) in got.iter().zip(want.iter()).enumerate() {
+            assert_eq!(g.is_some(), w.is_some(), "readiness mismatch at {i}");
+            if let (Some(a), Some(b)) = (g, w) {
+                assert_relative_eq!(*a, *b, epsilon = 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut alf = AdaptiveLaguerreFilter::new(5).unwrap();
+        alf.batch(&(1..=40).map(f64::from).collect::<Vec<_>>());
+        assert!(alf.is_ready());
+        alf.reset();
+        assert!(!alf.is_ready());
+        assert_eq!(alf.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=50).map(|i| f64::from(i) * 0.7).collect();
+        let mut a = AdaptiveLaguerreFilter::new(7).unwrap();
+        let mut b = AdaptiveLaguerreFilter::new(7).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut alf = AdaptiveLaguerreFilter::new(3).unwrap();
+        alf.update(10.0);
+        alf.update(11.0);
+        let ready = alf.update(12.0).expect("ready after three inputs");
+        assert_eq!(alf.update(f64::NAN), Some(ready));
+        assert_eq!(alf.update(f64::INFINITY), Some(ready));
+    }
+}
@@ -0,0 +1,192 @@
+//! Advance Block candlestick pattern.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Advance Block — a 3-bar bearish warning: three green candles still pushing to
+/// higher closes, but visibly running out of steam — each real body shrinks while
+/// the upper shadows lengthen, hinting the advance is about to stall.
+///
+/// ```text
+/// all three green & higher closes
+/// each opens inside the prior body
+/// shrinking bodies   (body3 < body2 < body1)
+/// upper shadow of bar3 >= upper shadow of bar2 and bar3 has an upper shadow
+/// ```
+///
+/// Output is `−1.0` when the pattern completes and `0.0` otherwise. Advance Block
+/// is a single-direction (bearish-only) warning, so it never emits `+1.0`. The
+/// first two bars always return `0.0` because the three-bar window is not yet
+/// filled. Pattern-shape check only — no trend filter is applied; combine with a
+/// trend indicator for actionable signals.
+///
+/// # Signed ±1 encoding
+///
+/// This detector emits the uniform candlestick sign convention shared across the
+/// pattern family — `−1.0` bearish, `0.0` no pattern — so it drops straight into
+/// a machine-learning feature matrix as a single dimension.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdvanceBlock, Candle, Indicator};
+///
+/// let mut indicator = AdvanceBlock::new();
+/// indicator.update(Candle::new(10.0, 13.1, 9.9, 13.0, 1.0, 0).unwrap());
+/// indicator.update(Candle::new(12.0, 14.3, 11.9, 14.0, 1.0, 1).unwrap());
+/// let out = indicator
+///     .update(Candle::new(13.5, 15.0, 13.4, 14.5, 1.0, 2).unwrap());
+/// assert_eq!(out, Some(-1.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdvanceBlock {
+    prev: Option<Candle>,
+    prev_prev: Option<Candle>,
+    has_emitted: bool,
+}
+
+impl AdvanceBlock {
+    /// Construct a new Advance Block detector.
+    pub const fn new() -> Self {
+        Self {
+            prev: None,
+            prev_prev: None,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for AdvanceBlock {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let pp = self.prev_prev;
+        let p = self.prev;
+        self.prev_prev = self.prev;
+        self.prev = Some(candle);
+        let (Some(bar1), Some(bar2)) = (pp, p) else {
+            return Some(0.0);
+        };
+        let body1 = bar1.close - bar1.open;
+        let body2 = bar2.close - bar2.open;
+        let body3 = candle.close - candle.open;
+        let upper2 = bar2.high - bar2.close;
+        let upper3 = candle.high - candle.close;
+        if bar1.close > bar1.open
+            && bar2.close > bar2.open
+            && candle.close > candle.open
+            && bar2.close > bar1.close
+            && candle.close > bar2.close
+            && bar2.open >= bar1.open
+            && bar2.open <= bar1.close
+            && candle.open >= bar2.open
+            && candle.open <= bar2.close
+            && body2 < body1
+            && body3 < body2
+            && upper3 >= upper2
+            && upper3 > 0.0
+        {
+            return Some(-1.0);
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        self.prev_prev = None;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdvanceBlock"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = AdvanceBlock::new();
+        assert_eq!(t.name(), "AdvanceBlock");
+        assert_eq!(t.warmup_period(), 3);
+        assert!(!t.is_ready());
+    }
+
+    #[test]
+    fn advance_block_is_minus_one() {
+        let mut t = AdvanceBlock::new();
+        assert_eq!(t.update(c(10.0, 13.1, 9.9, 13.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(12.0, 14.3, 11.9, 14.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(13.5, 15.0, 13.4, 14.5, 2)), Some(-1.0));
+    }
+
+    #[test]
+    fn strong_advance_yields_zero() {
+        let mut t = AdvanceBlock::new();
+        // Bodies grow instead of shrinking -> a strong advance, not blocked.
+        assert_eq!(t.update(c(10.0, 11.1, 9.9, 11.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(10.5, 12.6, 10.4, 12.5, 1)), Some(0.0));
+        assert_eq!(t.update(c(11.5, 14.1, 11.4, 14.0, 2)), Some(0.0));
+    }
+
+    #[test]
+    fn no_upper_shadow_growth_yields_zero() {
+        let mut t = AdvanceBlock::new();
+        t.update(c(10.0, 13.1, 9.9, 13.0, 0));
+        t.update(c(12.0, 14.3, 11.9, 14.0, 1));
+        // bar3 shrinking body but no upper shadow -> not blocked.
+        assert_eq!(t.update(c(13.5, 14.5, 13.4, 14.5, 2)), Some(0.0));
+    }
+
+    #[test]
+    fn first_two_bars_return_zero() {
+        let mut t = AdvanceBlock::new();
+        assert_eq!(t.update(c(10.0, 13.1, 9.9, 13.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(12.0, 14.3, 11.9, 14.0, 1)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + i as f64;
+                c(base, base + 2.0, base - 0.2, base + 1.5, i)
+            })
+            .collect();
+        let mut a = AdvanceBlock::new();
+        let mut b = AdvanceBlock::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = AdvanceBlock::new();
+        t.update(c(10.0, 13.1, 9.9, 13.0, 0));
+        t.update(c(12.0, 14.3, 11.9, 14.0, 1));
+        t.update(c(13.5, 15.0, 13.4, 14.5, 2));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.update(c(10.0, 13.1, 9.9, 13.0, 0)), Some(0.0));
+    }
+}
@@ -0,0 +1,168 @@
+//! Advance/Decline Line — cumulative net advancing-minus-declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Line (A/D Line) — the running cumulative sum of net advancing
+/// issues across a universe.
+///
+/// On each [`CrossSection`] tick the net breadth is `advancers - decliners`:
+/// the number of symbols with a positive price change minus the number with a
+/// negative change (unchanged symbols are ignored). The line accumulates this
+/// net value over time, so a rising line means advancers have persistently
+/// outnumbered decliners — broad participation — while a falling line warns that
+/// a rally is being carried by fewer and fewer names (a breadth divergence when
+/// the index itself is still rising).
+///
+/// `Input = CrossSection`, `Output = f64`. The line is defined from the very
+/// first tick, so `warmup_period == 1` and the indicator is ready after one
+/// update.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdvanceDecline, CrossSection, Indicator, Member};
+///
+/// let mut ad = AdvanceDecline::new();
+/// // 3 advancers, 1 decliner -> net +2.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(0.5, 10.0, false, false),
+///         Member::new(2.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(ad.update(tick), Some(2.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdvanceDecline {
+    line: f64,
+    has_emitted: bool,
+}
+
+impl AdvanceDecline {
+    /// Construct a new Advance/Decline Line indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            line: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for AdvanceDecline {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancers() as f64 - section.decliners() as f64;
+        self.line += net;
+        self.has_emitted = true;
+        Some(self.line)
+    }
+
+    fn reset(&mut self) {
+        self.line = 0.0;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdvanceDecline"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    /// Build a cross-section with `up` advancers, `down` decliners and `flat`
+    /// unchanged symbols.
+    fn section(up: usize, down: usize, flat: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        for _ in 0..flat {
+            members.push(Member::new(0.0, 10.0, false, false));
+        }
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ad = AdvanceDecline::new();
+        assert_eq!(ad.name(), "AdvanceDecline");
+        assert_eq!(ad.warmup_period(), 1);
+        assert!(!ad.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_net_breadth() {
+        let mut ad = AdvanceDecline::new();
+        assert_eq!(ad.update(section(3, 1, 0)), Some(2.0));
+        assert!(ad.is_ready());
+    }
+
+    #[test]
+    fn line_accumulates_across_ticks() {
+        let mut ad = AdvanceDecline::new();
+        assert_eq!(ad.update(section(3, 1, 0)), Some(2.0)); // +2 -> 2
+        assert_eq!(ad.update(section(1, 4, 0)), Some(-1.0)); // -3 -> -1
+        assert_eq!(ad.update(section(2, 0, 0)), Some(1.0)); // +2 -> 1
+    }
+
+    #[test]
+    fn unchanged_symbols_are_ignored() {
+        let mut ad = AdvanceDecline::new();
+        // 2 up, 2 down, 5 unchanged -> net 0, line stays flat.
+        assert_eq!(ad.update(section(2, 2, 5)), Some(0.0));
+        assert_eq!(ad.update(section(2, 2, 5)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ad = AdvanceDecline::new();
+        ad.update(section(5, 0, 0));
+        assert!(ad.is_ready());
+        ad.reset();
+        assert!(!ad.is_ready());
+        // Line restarts from zero, not from the pre-reset value.
+        assert_eq!(ad.update(section(1, 0, 0)), Some(1.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![
+            section(3, 1, 2),
+            section(1, 4, 0),
+            section(2, 2, 1),
+            section(5, 0, 3),
+        ];
+        let mut a = AdvanceDecline::new();
+        let mut b = AdvanceDecline::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,151 @@
+//! Advance/Decline Ratio — advancing issues divided by declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Ratio (ADR) — the number of advancing symbols divided by the
+/// number of declining symbols across a universe.
+///
+/// On each [`CrossSection`] tick the ratio is `advancers / decliners`: a reading
+/// above one means advancing issues outnumber declining ones (broad strength),
+/// while a reading below one signals broad weakness. Because it is a ratio rather
+/// than a difference, the ADR is comparable across universes of different sizes.
+///
+/// When a tick has no declining symbols the denominator is floored to one, so the
+/// ratio degrades gracefully to the advancer count instead of dividing by zero.
+///
+/// `Input = CrossSection`, `Output = f64`. The ratio is defined from the first
+/// tick, so `warmup_period == 1` and the indicator is ready after one update.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdvanceDeclineRatio, CrossSection, Indicator, Member};
+///
+/// let mut adr = AdvanceDeclineRatio::new();
+/// // 3 advancers, 1 decliner -> ratio 3.0.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(0.5, 10.0, false, false),
+///         Member::new(2.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(adr.update(tick), Some(3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdvanceDeclineRatio {
+    has_emitted: bool,
+}
+
+impl AdvanceDeclineRatio {
+    /// Construct a new Advance/Decline Ratio indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AdvanceDeclineRatio {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let advancers = section.advancers() as f64;
+        let decliners = section.decliners().max(1) as f64;
+        self.has_emitted = true;
+        Some(advancers / decliners)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdvanceDeclineRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        // A non-empty unchanged member guarantees a valid universe when both
+        // counts are zero.
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.name(), "AdvanceDeclineRatio");
+        assert_eq!(adr.warmup_period(), 1);
+        assert!(!adr.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_ratio() {
+        let mut adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.update(section(3, 1)), Some(3.0));
+        assert!(adr.is_ready());
+    }
+
+    #[test]
+    fn zero_decliners_floors_denominator() {
+        let mut adr = AdvanceDeclineRatio::new();
+        // 4 advancers, 0 decliners -> 4 / max(0, 1) = 4.0.
+        assert_eq!(adr.update(section(4, 0)), Some(4.0));
+    }
+
+    #[test]
+    fn no_advancers_yields_zero() {
+        let mut adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.update(section(0, 5)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adr = AdvanceDeclineRatio::new();
+        adr.update(section(3, 1));
+        assert!(adr.is_ready());
+        adr.reset();
+        assert!(!adr.is_ready());
+        assert_eq!(adr.update(section(2, 1)), Some(2.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(3, 1), section(4, 0), section(0, 5), section(2, 2)];
+        let mut a = AdvanceDeclineRatio::new();
+        let mut b = AdvanceDeclineRatio::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -91,7 +91,7 @@ impl Adx {
    }
 }

-fn directional_movement(prev: &Candle, current: &Candle) -> (f64, f64) {
+pub(crate) fn directional_movement(prev: &Candle, current: &Candle) -> (f64, f64) {
    let up = current.high - prev.high;
    let down = prev.low - current.low;
    let plus_dm = if up > down && up > 0.0 { up } else { 0.0 };
@@ -0,0 +1,239 @@
+//! Amihud Illiquidity — average price impact per unit traded value.
+
+use std::collections::VecDeque;
+
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+use crate::{Error, Result};
+
+/// Amihud Illiquidity — the average absolute log return per unit of traded
+/// value over the last `period` trades (Amihud, 2002).
+///
+/// ```text
+/// rₜ      = ln(priceₜ / priceₜ₋₁)
+/// ILLIQₜ  = |rₜ| / (priceₜ · sizeₜ)        (return per dollar of volume)
+/// Amihud  = mean of ILLIQ over the last `period` trades
+/// ```
+///
+/// Amihud's measure captures how much the price moves for a given amount of
+/// traded value: a **high** reading means small volume already shifts the price
+/// a lot (an illiquid, easily-moved market), a **low** reading means it takes
+/// large volume to move the price (a deep, liquid market). It is the workhorse
+/// cross-sectional liquidity proxy in market-microstructure research.
+///
+/// `Input = Trade`. Trades with zero size carry no traded value and are skipped
+/// (the ratio is undefined); the last value is returned and state is untouched.
+/// The first valid trade only seeds the reference price.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Side, Trade, AmihudIlliquidity};
+///
+/// let mut amihud = AmihudIlliquidity::new(20).unwrap();
+/// assert_eq!(amihud.update(Trade::new(100.0, 5.0, Side::Buy, 0).unwrap()), None);
+/// ```
+#[derive(Debug, Clone)]
+pub struct AmihudIlliquidity {
+    period: usize,
+    prev_price: Option<f64>,
+    window: VecDeque<f64>,
+    sum: f64,
+    last: Option<f64>,
+}
+
+impl AmihudIlliquidity {
+    /// Construct a new Amihud Illiquidity over the given trade window.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            prev_price: None,
+            window: VecDeque::with_capacity(period),
+            sum: 0.0,
+            last: None,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for AmihudIlliquidity {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        // A zero-size trade has no traded value: the ratio is undefined, so the
+        // trade is skipped without touching the reference price.
+        if trade.size == 0.0 {
+            return self.last;
+        }
+        let Some(prev) = self.prev_price else {
+            self.prev_price = Some(trade.price);
+            return None;
+        };
+        self.prev_price = Some(trade.price);
+        // `prev` and `trade.price` are both finite and strictly positive
+        // (enforced by `Trade::new`), so the log return is well-defined and the
+        // traded value is strictly positive.
+        let ret = (trade.price / prev).ln().abs();
+        let illiq = ret / (trade.price * trade.size);
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("window is non-empty");
+            self.sum -= old;
+        }
+        self.window.push_back(illiq);
+        self.sum += illiq;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let value = self.sum / self.period as f64;
+        self.last = Some(value);
+        Some(value)
+    }
+
+    fn reset(&mut self) {
+        self.prev_price = None;
+        self.window.clear();
+        self.sum = 0.0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "AmihudIlliquidity"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn trade(price: f64, size: f64) -> Trade {
+        Trade::new(price, size, Side::Buy, 0).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(AmihudIlliquidity::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let a = AmihudIlliquidity::new(20).unwrap();
+        assert_eq!(a.period(), 20);
+        assert_eq!(a.warmup_period(), 21);
+        assert_eq!(a.name(), "AmihudIlliquidity");
+        assert!(!a.is_ready());
+    }
+
+    #[test]
+    fn known_value() {
+        // period 1. Seed at 100, then 101 with size 10:
+        // |ln(101/100)| / (101 * 10).
+        let mut a = AmihudIlliquidity::new(1).unwrap();
+        assert_eq!(a.update(trade(100.0, 10.0)), None);
+        let out = a.update(trade(101.0, 10.0)).unwrap();
+        let expected = (101.0_f64 / 100.0).ln().abs() / (101.0 * 10.0);
+        assert_relative_eq!(out, expected, epsilon = 1e-15);
+    }
+
+    #[test]
+    fn higher_for_thinner_volume() {
+        // Same price move on smaller volume => larger illiquidity reading.
+        let thin = {
+            let mut a = AmihudIlliquidity::new(1).unwrap();
+            a.update(trade(100.0, 1.0));
+            a.update(trade(101.0, 1.0)).unwrap()
+        };
+        let thick = {
+            let mut a = AmihudIlliquidity::new(1).unwrap();
+            a.update(trade(100.0, 1000.0));
+            a.update(trade(101.0, 1000.0)).unwrap()
+        };
+        assert!(thin > thick, "thin {thin} should exceed thick {thick}");
+    }
+
+    #[test]
+    fn flat_price_is_zero() {
+        let mut a = AmihudIlliquidity::new(5).unwrap();
+        for v in a.batch(&[trade(100.0, 3.0); 20]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-15);
+        }
+    }
+
+    #[test]
+    fn skips_zero_size_trades() {
+        let mut a = AmihudIlliquidity::new(1).unwrap();
+        a.update(trade(100.0, 10.0));
+        let baseline = a.update(trade(101.0, 10.0)).unwrap();
+        // A zero-size trade is ignored; the previous reference price is kept.
+        assert_eq!(a.update(trade(200.0, 0.0)), Some(baseline));
+        // The next real trade still references price 101, not 200.
+        let mut control = a.clone();
+        let after = a.update(trade(102.0, 10.0)).unwrap();
+        assert_eq!(control.update(trade(102.0, 10.0)).unwrap(), after);
+    }
+
+    #[test]
+    fn output_is_non_negative() {
+        let mut a = AmihudIlliquidity::new(10).unwrap();
+        let trades: Vec<Trade> = (0..100)
+            .map(|i| {
+                trade(
+                    100.0 + (f64::from(i) * 0.3).sin() * 5.0,
+                    1.0 + f64::from(i % 7),
+                )
+            })
+            .collect();
+        for v in a.batch(&trades).into_iter().flatten() {
+            assert!(v >= 0.0, "illiquidity must be non-negative, got {v}");
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut a = AmihudIlliquidity::new(5).unwrap();
+        for i in 0..20 {
+            a.update(trade(100.0 + f64::from(i), 2.0));
+        }
+        assert!(a.is_ready());
+        a.reset();
+        assert!(!a.is_ready());
+        assert_eq!(a.update(trade(100.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..80)
+            .map(|i| {
+                trade(
+                    100.0 + (f64::from(i) * 0.25).sin() * 4.0,
+                    1.0 + f64::from(i % 5),
+                )
+            })
+            .collect();
+        let batch = AmihudIlliquidity::new(14).unwrap().batch(&trades);
+        let mut b = AmihudIlliquidity::new(14).unwrap();
+        let streamed: Vec<_> = trades.iter().map(|t| b.update(*t)).collect();
+        assert_eq!(batch, streamed);
+    }
+}
@@ -0,0 +1,284 @@
+//! Anchored Relative Strength Index.
+
+use crate::traits::Indicator;
+
+/// Anchored RSI — a cumulative Relative Strength Index whose averaging begins at
+/// a user-chosen anchor bar rather than over a fixed Wilder period.
+///
+/// Where [`crate::Rsi`] uses Wilder's `period`-length smoothing, Anchored RSI
+/// accumulates *every* up- and down-move since the anchor with equal weight, so
+/// it answers "what is the RSI of the entire move since the anchor point?". The
+/// running relative strength is `Σ gains / Σ losses` over all bars in the
+/// current anchor window (the bar count cancels, so this equals
+/// `avg_gain / avg_loss`):
+///
+/// ```text
+/// RSI_t = 100 - 100 / (1 + Σ_{i ≥ anchor} gain_i / Σ_{i ≥ anchor} loss_i)
+/// ```
+///
+/// As with [`crate::AnchoredVwap`], the anchor is chosen at runtime:
+/// [`AnchoredRsi::set_anchor`] re-anchors at the **next** bar that arrives,
+/// clearing the running sums. Because RSI needs a price *change*, the first bar
+/// of a fresh anchor window only seeds the previous close and emits `None`; the
+/// first value follows on the second bar (warmup period 2).
+///
+/// Saturation follows the standard convention: a window with no losses yet (and
+/// at least one gain) reads 100, no gains yet reads 0, and a perfectly flat
+/// window reads the neutral 50. Non-finite inputs are ignored, leaving the last
+/// value unchanged.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AnchoredRsi, Indicator};
+///
+/// let mut indicator = AnchoredRsi::new();
+/// let mut last = None;
+/// for i in 0..80 {
+///     let price = 100.0 + (f64::from(i) * 0.5).sin() * 5.0;
+///     // Re-anchor at bar 40 (e.g. a major swing low).
+///     if i == 40 {
+///         indicator.set_anchor();
+///     }
+///     last = indicator.update(price);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AnchoredRsi {
+    prev_close: Option<f64>,
+    sum_gain: f64,
+    sum_loss: f64,
+    last_value: Option<f64>,
+    pending_anchor: bool,
+}
+
+impl AnchoredRsi {
+    /// Construct a fresh Anchored RSI. The first bar to arrive is the anchor.
+    pub const fn new() -> Self {
+        Self {
+            prev_close: None,
+            sum_gain: 0.0,
+            sum_loss: 0.0,
+            last_value: None,
+            pending_anchor: false,
+        }
+    }
+
+    /// Mark a re-anchor: the **next** [`Indicator::update`] call clears the
+    /// running sums and previous close before folding in its own bar, starting
+    /// a fresh anchored window.
+    pub fn set_anchor(&mut self) {
+        self.pending_anchor = true;
+    }
+
+    /// Current anchored RSI value if at least one price change has been
+    /// observed in the current anchor window.
+    pub const fn value(&self) -> Option<f64> {
+        self.last_value
+    }
+
+    fn rsi_from_sums(sum_gain: f64, sum_loss: f64) -> f64 {
+        if sum_loss == 0.0 {
+            if sum_gain == 0.0 {
+                // No movement at all -> RSI undefined; standard convention returns 50.
+                50.0
+            } else {
+                100.0
+            }
+        } else {
+            let rs = sum_gain / sum_loss;
+            100.0 - 100.0 / (1.0 + rs)
+        }
+    }
+}
+
+impl Indicator for AnchoredRsi {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        if !input.is_finite() {
+            return self.last_value;
+        }
+
+        if self.pending_anchor {
+            self.prev_close = None;
+            self.sum_gain = 0.0;
+            self.sum_loss = 0.0;
+            self.last_value = None;
+            self.pending_anchor = false;
+        }
+
+        let Some(prev) = self.prev_close else {
+            self.prev_close = Some(input);
+            return None;
+        };
+        self.prev_close = Some(input);
+
+        let diff = input - prev;
+        if diff > 0.0 {
+            self.sum_gain += diff;
+        } else if diff < 0.0 {
+            self.sum_loss -= diff;
+        }
+
+        let value = Self::rsi_from_sums(self.sum_gain, self.sum_loss);
+        self.last_value = Some(value);
+        Some(value)
+    }
+
+    fn reset(&mut self) {
+        self.prev_close = None;
+        self.sum_gain = 0.0;
+        self.sum_loss = 0.0;
+        self.last_value = None;
+        self.pending_anchor = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last_value.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "AnchoredRSI"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = AnchoredRsi::new();
+        assert_eq!(indicator.name(), "AnchoredRSI");
+        assert_eq!(indicator.warmup_period(), 2);
+        assert_eq!(indicator.value(), None);
+        assert!(!indicator.is_ready());
+    }
+
+    #[test]
+    fn first_bar_seeds_and_returns_none() {
+        let mut indicator = AnchoredRsi::new();
+        assert_eq!(indicator.update(100.0), None);
+        assert!(!indicator.is_ready());
+        // Second bar produces the first value.
+        assert!(indicator.update(101.0).is_some());
+        assert!(indicator.is_ready());
+    }
+
+    #[test]
+    fn pure_uptrend_saturates_at_100() {
+        let mut indicator = AnchoredRsi::new();
+        let out = indicator.batch(&[10.0, 11.0, 12.0, 13.0]);
+        assert_relative_eq!(out[3].unwrap(), 100.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn pure_downtrend_saturates_at_0() {
+        let mut indicator = AnchoredRsi::new();
+        let out = indicator.batch(&[13.0, 12.0, 11.0, 10.0]);
+        assert_relative_eq!(out[3].unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn flat_window_reads_50() {
+        let mut indicator = AnchoredRsi::new();
+        let out = indicator.batch(&[42.0, 42.0, 42.0]);
+        assert_relative_eq!(out[2].unwrap(), 50.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn cumulative_reference_values() {
+        // prices 10 -> 11 (+1) -> 9 (-2) -> 12 (+3)
+        // after bar2: sum_gain=1, sum_loss=2 -> rs=0.5 -> 100 - 100/1.5 = 33.3333
+        // after bar3: sum_gain=4, sum_loss=2 -> rs=2.0 -> 100 - 100/3   = 66.6667
+        let mut indicator = AnchoredRsi::new();
+        let out = indicator.batch(&[10.0, 11.0, 9.0, 12.0]);
+        assert_relative_eq!(out[1].unwrap(), 100.0, epsilon = 1e-9);
+        assert_relative_eq!(out[2].unwrap(), 33.333_333_333, epsilon = 1e-6);
+        assert_relative_eq!(out[3].unwrap(), 66.666_666_666, epsilon = 1e-6);
+    }
+
+    #[test]
+    fn set_anchor_clears_old_window() {
+        // Downtrend, then re-anchor and pump an uptrend: the new window must
+        // read 100, not the blended value.
+        let mut indicator = AnchoredRsi::new();
+        indicator.batch(&[20.0, 19.0, 18.0, 17.0]);
+        assert_relative_eq!(indicator.value().unwrap(), 0.0, epsilon = 1e-12);
+        indicator.set_anchor();
+        // First bar after anchor re-seeds (None), second bar emits.
+        assert_eq!(indicator.update(50.0), None);
+        let after = indicator.update(51.0).unwrap();
+        assert_relative_eq!(after, 100.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn set_anchor_before_first_bar_acts_as_normal_start() {
+        let mut indicator = AnchoredRsi::new();
+        indicator.set_anchor();
+        assert_eq!(indicator.update(10.0), None);
+        assert_relative_eq!(indicator.update(11.0).unwrap(), 100.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut indicator = AnchoredRsi::new();
+        indicator.batch(&[10.0, 11.0, 12.0]);
+        let before = indicator.value();
+        assert!(before.is_some());
+        assert_eq!(indicator.update(f64::NAN), before);
+        assert_eq!(indicator.update(f64::INFINITY), before);
+        assert_eq!(indicator.value(), before);
+    }
+
+    #[test]
+    fn non_finite_before_any_bar_returns_none() {
+        let mut indicator = AnchoredRsi::new();
+        assert_eq!(indicator.update(f64::NAN), None);
+        assert!(!indicator.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = AnchoredRsi::new();
+        indicator.batch(&[10.0, 11.0, 12.0]);
+        assert!(indicator.is_ready());
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        assert_eq!(indicator.value(), None);
+        assert_eq!(indicator.update(50.0), None);
+    }
+
+    #[test]
+    fn stays_in_0_100_range() {
+        let prices: Vec<f64> = (0..200)
+            .map(|i| 100.0 + (f64::from(i) * 0.7).sin() * 10.0)
+            .collect();
+        let mut indicator = AnchoredRsi::new();
+        for value in indicator.batch(&prices).into_iter().flatten() {
+            assert!((0.0..=100.0).contains(&value), "RSI out of range: {value}");
+        }
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=40)
+            .map(|i| (f64::from(i) * 0.3).sin() * 5.0 + f64::from(i))
+            .collect();
+        let mut a = AnchoredRsi::new();
+        let mut b = AnchoredRsi::new();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -28,9 +28,17 @@ use crate::traits::Indicator;
 #[derive(Debug, Clone)]
 pub struct Atr {
    period: usize,
+    /// `period - 1` as `f64`, precomputed for the Wilder smoothing step.
+    n_minus_1: f64,
+    /// `1 / period`, precomputed so the per-tick smoothing multiplies instead of
+    /// divides.
+    inv_period: f64,
    prev_close: Option<f64>,
    seed_buf: Vec<f64>,
-    avg: Option<f64>,
+    /// Smoothed ATR, valid once `seeded` is set. Bare `f64` + flag rather than
+    /// `Option<f64>` so the hot recurrence avoids an enum-tag read per tick.
+    avg: f64,
+    seeded: bool,
 }

 impl Atr {
@@ -45,9 +53,12 @@ impl Atr {
        }
        Ok(Self {
            period,
+            n_minus_1: (period - 1) as f64,
+            inv_period: 1.0 / period as f64,
            prev_close: None,
            seed_buf: Vec::with_capacity(period),
-            avg: None,
+            avg: 0.0,
+            seeded: false,
        })
    }

@@ -58,7 +69,11 @@ impl Atr {

    /// Current value if available.
    pub const fn value(&self) -> Option<f64> {
-        self.avg
+        if self.seeded {
+            Some(self.avg)
+        } else {
+            None
+        }
    }
 }

@@ -70,17 +85,18 @@ impl Indicator for Atr {
        let tr = candle.true_range(self.prev_close);
        self.prev_close = Some(candle.close);

-        if let Some(avg) = self.avg {
-            let n = self.period as f64;
-            let new_avg = avg.mul_add(n - 1.0, tr) / n;
-            self.avg = Some(new_avg);
+        if self.seeded {
+            // Wilder smoothing with the reciprocal hoisted out of the hot path.
+            let new_avg = self.avg.mul_add(self.n_minus_1, tr) * self.inv_period;
+            self.avg = new_avg;
            return Some(new_avg);
        }

        self.seed_buf.push(tr);
        if self.seed_buf.len() == self.period {
            let seed = self.seed_buf.iter().copied().sum::<f64>() / self.period as f64;
-            self.avg = Some(seed);
+            self.avg = seed;
+            self.seeded = true;
            return Some(seed);
        }
        None
@@ -89,7 +105,8 @@ impl Indicator for Atr {
    fn reset(&mut self) {
        self.prev_close = None;
        self.seed_buf.clear();
-        self.avg = None;
+        self.avg = 0.0;
+        self.seeded = false;
    }

    fn warmup_period(&self) -> usize {
@@ -97,7 +114,7 @@ impl Indicator for Atr {
    }

    fn is_ready(&self) -> bool {
-        self.avg.is_some()
+        self.seeded
    }

    fn name(&self) -> &'static str {
@@ -0,0 +1,176 @@
+//! Auto-Fibonacci — retracement of the most significant recent swing leg.
+
+use crate::indicators::pattern_swing::{SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// How many recent pivots to consider when picking the dominant leg.
+const PIVOT_HISTORY: usize = 6;
+
+/// The seven canonical retracement ratios, in ascending order.
+const RATIOS: [f64; 7] = [0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0];
+
+/// Auto-Fibonacci retracement levels for the dominant recent swing leg.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct AutoFibOutput {
+    /// 0.0% — the dominant leg's end.
+    pub level_0: f64,
+    /// 23.6% retracement.
+    pub level_236: f64,
+    /// 38.2% retracement.
+    pub level_382: f64,
+    /// 50% retracement.
+    pub level_500: f64,
+    /// 61.8% retracement.
+    pub level_618: f64,
+    /// 78.6% retracement.
+    pub level_786: f64,
+    /// 100% — the dominant leg's start.
+    pub level_1000: f64,
+}
+
+/// Auto-Fibonacci (`AutoFib`).
+///
+/// Like [`crate::indicators::FibRetracement`], but instead of always using the
+/// immediate last leg it scans the last six confirmed pivots and anchors the
+/// retracement on the single largest-magnitude leg among them — the dominant
+/// swing the market is most likely respecting.
+///
+/// Parameter-free; construction is infallible. Returns `None` until two pivots
+/// have confirmed.
+///
+/// See `crates/wickra-core/src/indicators/auto_fib.rs`.
+#[derive(Debug, Clone)]
+pub struct AutoFib {
+    swing: SwingTracker,
+}
+
+impl AutoFib {
+    /// Construct a new Auto-Fibonacci tracker.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, PIVOT_HISTORY),
+        }
+    }
+
+    fn levels(&self) -> Option<AutoFibOutput> {
+        let dominant = self.swing.pivots().windows(2).max_by(|x, y| {
+            (x[0].price - x[1].price)
+                .abs()
+                .total_cmp(&(y[0].price - y[1].price).abs())
+        })?;
+        let (start, end) = (dominant[0].price, dominant[1].price);
+        let level = |r: f64| end + r * (start - end);
+        Some(AutoFibOutput {
+            level_0: level(RATIOS[0]),
+            level_236: level(RATIOS[1]),
+            level_382: level(RATIOS[2]),
+            level_500: level(RATIOS[3]),
+            level_618: level(RATIOS[4]),
+            level_786: level(RATIOS[5]),
+            level_1000: level(RATIOS[6]),
+        })
+    }
+}
+
+impl Default for AutoFib {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for AutoFib {
+    type Input = Candle;
+    type Output = AutoFibOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<AutoFibOutput> {
+        self.swing.update(candle);
+        self.levels()
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.swing.pivots().len() >= 2
+    }
+
+    fn name(&self) -> &'static str {
+        "AutoFib"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = AutoFib::new();
+        assert_eq!(indicator.name(), "AutoFib");
+        assert_eq!(indicator.warmup_period(), 2);
+        assert!(!indicator.is_ready());
+        assert!(!AutoFib::default().is_ready());
+    }
+
+    #[test]
+    fn no_output_before_two_pivots() {
+        let mut indicator = AutoFib::new();
+        let outputs: Vec<_> = candles_for_pivots(&[120.0])
+            .into_iter()
+            .map(|c| indicator.update(c))
+            .collect();
+        assert!(outputs.iter().all(Option::is_none));
+    }
+
+    #[test]
+    fn anchors_on_the_largest_leg() {
+        // Pivots: 130 -> 120 (small, 10) -> 220 (large, 100) -> 200 (small, 20).
+        // The dominant leg is 120 -> 220; its retracement spans [120, 220].
+        let mut indicator = AutoFib::new();
+        let mut last = None;
+        for candle in candles_for_pivots(&[130.0, 120.0, 220.0, 200.0]) {
+            last = indicator.update(candle);
+        }
+        let v = last.unwrap();
+        assert!(indicator.is_ready());
+        // Largest leg 120 -> 220: 0% on 220 (end), 100% on 120 (start).
+        assert_relative_eq!(v.level_0, 220.0);
+        assert_relative_eq!(v.level_1000, 120.0);
+        assert_relative_eq!(v.level_500, 170.0);
+        assert_relative_eq!(v.level_618, 220.0 + 0.618 * (120.0 - 220.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = AutoFib::new();
+        for candle in candles_for_pivots(&[200.0, 100.0]) {
+            let _ = indicator.update(candle);
+        }
+        assert!(indicator.is_ready());
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert!(indicator.update(c).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[130.0, 120.0, 220.0, 200.0]);
+        let mut a = AutoFib::new();
+        let mut b = AutoFib::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,231 @@
+//! Average Daily Range (ADR) — the mean high-minus-low range of the last `period`
+//! completed calendar-day sessions.
+
+use std::collections::VecDeque;
+
+use crate::calendar::civil_from_timestamp;
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Average Daily Range over the last `period` completed sessions.
+///
+/// The indicator tracks the running high / low of the current session (the
+/// wall-clock day of [`Candle::timestamp`](crate::Candle) shifted by
+/// `utc_offset_minutes`). When a new day begins, the just-finished session's
+/// range (`high - low`) joins a rolling window of the last `period` completed
+/// days, and the reported value is their mean. The current, still-forming day is
+/// excluded until it closes. No value is produced until the first session
+/// completes.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, AverageDailyRange};
+///
+/// let hour = 3_600_000;
+/// let mut adr = AverageDailyRange::new(2, 0).unwrap();
+/// // Day 1 range 10 (high 110, low 100) — still forming, so None.
+/// assert!(adr.update(Candle::new(105.0, 110.0, 100.0, 108.0, 1.0, 0).unwrap()).is_none());
+/// // First bar of day 2 closes day 1: ADR = 10.
+/// let v = adr.update(Candle::new(108.0, 112.0, 106.0, 109.0, 1.0, 24 * hour).unwrap()).unwrap();
+/// assert!((v - 10.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct AverageDailyRange {
+    period: usize,
+    utc_offset_minutes: i32,
+    day_key: Option<(i64, u32, u32)>,
+    cur_high: f64,
+    cur_low: f64,
+    completed: VecDeque<f64>,
+    sum: f64,
+}
+
+impl AverageDailyRange {
+    /// Construct an ADR indicator over `period` completed days.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize, utc_offset_minutes: i32) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            utc_offset_minutes,
+            day_key: None,
+            cur_high: f64::NEG_INFINITY,
+            cur_low: f64::INFINITY,
+            completed: VecDeque::with_capacity(period),
+            sum: 0.0,
+        })
+    }
+
+    /// Configured `(period, utc_offset_minutes)`.
+    pub const fn params(&self) -> (usize, i32) {
+        (self.period, self.utc_offset_minutes)
+    }
+
+    /// Most recent ADR if at least one session has completed.
+    pub fn value(&self) -> Option<f64> {
+        if self.completed.is_empty() {
+            None
+        } else {
+            Some(self.sum / self.completed.len() as f64)
+        }
+    }
+}
+
+impl Indicator for AverageDailyRange {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let civil = civil_from_timestamp(candle.timestamp, self.utc_offset_minutes);
+        let key = (civil.year, civil.month, civil.day);
+        match self.day_key {
+            Some(prev) if prev == key => {
+                if candle.high > self.cur_high {
+                    self.cur_high = candle.high;
+                }
+                if candle.low < self.cur_low {
+                    self.cur_low = candle.low;
+                }
+            }
+            Some(_) => {
+                let range = self.cur_high - self.cur_low;
+                self.completed.push_back(range);
+                self.sum += range;
+                if self.completed.len() > self.period {
+                    self.sum -= self
+                        .completed
+                        .pop_front()
+                        .expect("len > period implies a front element");
+                }
+                self.day_key = Some(key);
+                self.cur_high = candle.high;
+                self.cur_low = candle.low;
+            }
+            None => {
+                self.day_key = Some(key);
+                self.cur_high = candle.high;
+                self.cur_low = candle.low;
+            }
+        }
+        self.value()
+    }
+
+    fn reset(&mut self) {
+        self.day_key = None;
+        self.cur_high = f64::NEG_INFINITY;
+        self.cur_low = f64::INFINITY;
+        self.completed.clear();
+        self.sum = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        !self.completed.is_empty()
+    }
+
+    fn name(&self) -> &'static str {
+        "AverageDailyRange"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    const HOUR: i64 = 3_600_000;
+    const DAY: i64 = 24 * HOUR;
+
+    fn c(high: f64, low: f64, ts: i64) -> Candle {
+        let mid = f64::midpoint(high, low);
+        Candle::new(mid, high, low, mid, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(
+            AverageDailyRange::new(0, 0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    #[test]
+    fn metadata_and_accessors() {
+        let adr = AverageDailyRange::new(5, -60).unwrap();
+        assert_eq!(adr.params(), (5, -60));
+        assert_eq!(adr.name(), "AverageDailyRange");
+        assert_eq!(adr.warmup_period(), 5);
+        assert!(!adr.is_ready());
+        assert!(adr.value().is_none());
+    }
+
+    #[test]
+    fn averages_completed_day_ranges() {
+        let mut adr = AverageDailyRange::new(3, 0).unwrap();
+        // Day 1: range 10.
+        assert!(adr.update(c(110.0, 100.0, 0)).is_none());
+        assert!(adr.update(c(108.0, 104.0, HOUR)).is_none());
+        // Day 2 opens -> day 1 (range 10) completes.
+        let v = adr.update(c(120.0, 110.0, DAY)).unwrap();
+        assert_relative_eq!(v, 10.0);
+        assert!(adr.is_ready());
+        // Day 3 opens -> day 2 (range 10) completes: mean of [10, 10] = 10.
+        let v = adr.update(c(130.0, 100.0, 2 * DAY)).unwrap();
+        assert_relative_eq!(v, 10.0);
+    }
+
+    #[test]
+    fn rolls_off_oldest_day_beyond_period() {
+        let mut adr = AverageDailyRange::new(2, 0).unwrap();
+        adr.update(c(110.0, 100.0, 0)); // day 1 range 10
+        let v = adr.update(c(125.0, 110.0, DAY)).unwrap(); // close day 1 -> [10]
+        assert_relative_eq!(v, 10.0);
+        // Close day 2 (range 125-110=15) -> window [10, 15], mean 12.5.
+        let v = adr.update(c(130.0, 110.0, 2 * DAY)).unwrap();
+        assert_relative_eq!(v, 12.5);
+        // Close day 3 (range 130-110=20) -> window [15, 20], oldest (10) rolled off.
+        let v = adr.update(c(140.0, 138.0, 3 * DAY)).unwrap();
+        assert_relative_eq!(v, 17.5);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adr = AverageDailyRange::new(2, 0).unwrap();
+        adr.update(c(110.0, 100.0, 0));
+        adr.update(c(120.0, 110.0, DAY));
+        adr.reset();
+        assert!(!adr.is_ready());
+        assert!(adr.value().is_none());
+        assert!(adr.update(c(50.0, 40.0, 2 * DAY)).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..60)
+            .map(|i| {
+                c(
+                    110.0 + f64::from(i % 5),
+                    100.0 - f64::from(i % 3),
+                    i64::from(i) * 6 * HOUR,
+                )
+            })
+            .collect();
+        let mut a = AverageDailyRange::new(4, 0).unwrap();
+        let mut b = AverageDailyRange::new(4, 0).unwrap();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,92 @@
+//! Average Price (AVGPRICE).
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Average Price (`AVGPRICE`) — the bar's `(open + high + low + close) / 4`.
+///
+/// A per-bar price aggregate that, unlike [`TypicalPrice`](crate::TypicalPrice)
+/// and [`WeightedClose`](crate::WeightedClose), folds in the open as well as the
+/// high, low and close. As a stateless transform it emits a value from the very
+/// first candle.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, AvgPrice};
+///
+/// let mut indicator = AvgPrice::new();
+/// let mut last = None;
+/// for i in 0..80 {
+///     let base = 100.0 + f64::from(i);
+///     let candle =
+///         Candle::new(base, base + 2.0, base - 2.0, base + 1.0, 10.0, i64::from(i)).unwrap();
+///     last = indicator.update(candle);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AvgPrice {
+    has_emitted: bool,
+}
+
+impl AvgPrice {
+    /// Construct a new Average Price transform.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AvgPrice {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        Some(candle.avg_price())
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AVGPRICE"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn averages_the_four_prices() {
+        // (open + high + low + close) / 4 = (10 + 14 + 6 + 12) / 4 = 10.5.
+        let candle = Candle::new(10.0, 14.0, 6.0, 12.0, 1.0, 0).unwrap();
+        let mut ap = AvgPrice::new();
+        assert!(!ap.is_ready());
+        assert_relative_eq!(ap.update(candle).unwrap(), 10.5, epsilon = 1e-12);
+        assert!(ap.is_ready());
+    }
+
+    #[test]
+    fn accessors_and_reset() {
+        let mut ap = AvgPrice::new();
+        assert_eq!(ap.name(), "AVGPRICE");
+        assert_eq!(ap.warmup_period(), 1);
+        let candle = Candle::new(10.0, 14.0, 6.0, 12.0, 1.0, 0).unwrap();
+        let _ = ap.update(candle);
+        assert!(ap.is_ready());
+        ap.reset();
+        assert!(!ap.is_ready());
+    }
+}
@@ -0,0 +1,154 @@
+//! Bat harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Bat — a 5-point (X-A-B-C-D) harmonic pattern with a shallow B and a deep
+/// `0.886` D completion:
+///
+/// ```text
+/// AB / XA ∈ [0.382, 0.50]
+/// BC / AB ∈ [0.382, 0.886]
+/// CD / BC ∈ [1.618, 2.618]
+/// AD / XA ∈ [0.84, 0.93]   (≈ 0.886 — the defining D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/bat.rs`.
+#[derive(Debug, Clone)]
+pub struct Bat {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Bat {
+    /// Construct a new Bat detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Bat {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Bat {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let cd = (p.d - p.c).abs();
+        let ad = (p.d - p.a).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.382, 0.50),
+            (bc / ab, 0.382, 0.886),
+            (cd / bc, 1.618, 2.618),
+            (ad / xa, 0.84, 0.93),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Bat"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Bat::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Bat::new();
+        assert_eq!(indicator.name(), "Bat");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Bat::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_bat_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 122.0, 137.0, 104.56]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_bat_is_minus_one() {
+        let out = run(&[150.0, 110.0, 128.0, 113.0, 145.44]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Bat::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 122.0, 137.0, 104.56]);
+        let mut a = Bat::new();
+        let mut b = Bat::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,211 @@
+//! Belt-hold candlestick pattern.
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Belt-hold — a single-bar reversal: a long candle that opens at one extreme of
+/// its range (an "opening marubozu") and runs the other way.
+///
+/// ```text
+/// range        = high − low
+/// bullish (+1.0): green, opens at the low  (open − low <= tol * range) & long body
+/// bearish (−1.0): red,   opens at the high (high − open <= tol * range) & long body
+/// long body    = |close − open| >= 0.5 * range
+/// ```
+///
+/// Output is `0.0` when the opening side carries a shadow, the body is short, or
+/// the range is degenerate. `shadow_tolerance` defaults to `0.05` (5 % of the bar
+/// range allowed on the opening side) and must lie in `[0, 1)`. Pattern-shape
+/// check only — no trend filter is applied; combine with a trend indicator for
+/// actionable signals.
+///
+/// # Signed ±1 encoding
+///
+/// This detector emits the uniform candlestick sign convention shared across the
+/// pattern family — `+1.0` bullish, `−1.0` bearish, `0.0` no pattern — so it
+/// drops straight into a machine-learning feature matrix where the bullish and
+/// bearish variants occupy a single dimension.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BeltHold, Candle, Indicator};
+///
+/// let mut indicator = BeltHold::new();
+/// // Bullish belt-hold: opens at the low, closes near the high.
+/// let candle = Candle::new(10.0, 12.0, 10.0, 11.5, 1.0, 0).unwrap();
+/// assert_eq!(indicator.update(candle), Some(1.0));
+/// ```
+#[derive(Debug, Clone)]
+pub struct BeltHold {
+    shadow_tolerance: f64,
+    has_emitted: bool,
+}
+
+impl Default for BeltHold {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl BeltHold {
+    /// Construct a Belt-hold detector with the default 5 % opening-shadow tolerance.
+    pub const fn new() -> Self {
+        Self {
+            shadow_tolerance: 0.05,
+            has_emitted: false,
+        }
+    }
+
+    /// Construct a Belt-hold detector with a custom opening-shadow tolerance.
+    ///
+    /// `shadow_tolerance` must lie in `[0, 1)`.
+    pub fn with_tolerance(shadow_tolerance: f64) -> Result<Self> {
+        if !(0.0..1.0).contains(&shadow_tolerance) {
+            return Err(Error::InvalidPeriod {
+                message: "belt-hold shadow tolerance must lie in [0, 1)",
+            });
+        }
+        Ok(Self {
+            shadow_tolerance,
+            has_emitted: false,
+        })
+    }
+
+    /// Configured opening-shadow tolerance.
+    pub fn shadow_tolerance(&self) -> f64 {
+        self.shadow_tolerance
+    }
+}
+
+impl Indicator for BeltHold {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let range = candle.high - candle.low;
+        if range <= 0.0 {
+            return Some(0.0);
+        }
+        let body = candle.close - candle.open;
+        if body.abs() < 0.5 * range {
+            return Some(0.0);
+        }
+        let tol = self.shadow_tolerance * range;
+        // Bullish: opens at the low (no lower shadow), green body.
+        if body > 0.0 && candle.open - candle.low <= tol {
+            return Some(1.0);
+        }
+        // Bearish: opens at the high (no upper shadow), red body.
+        if body < 0.0 && candle.high - candle.open <= tol {
+            return Some(-1.0);
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "BeltHold"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn rejects_invalid_tolerance() {
+        assert!(BeltHold::with_tolerance(-0.01).is_err());
+        assert!(BeltHold::with_tolerance(1.0).is_err());
+    }
+
+    #[test]
+    fn accepts_valid_tolerance() {
+        let t = BeltHold::with_tolerance(0.0).unwrap();
+        assert!((t.shadow_tolerance() - 0.0).abs() < 1e-12);
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = BeltHold::default();
+        assert_eq!(t.name(), "BeltHold");
+        assert_eq!(t.warmup_period(), 1);
+        assert!(!t.is_ready());
+        assert!((t.shadow_tolerance() - 0.05).abs() < 1e-12);
+    }
+
+    #[test]
+    fn bullish_belt_hold_is_plus_one() {
+        let mut t = BeltHold::new();
+        assert_eq!(t.update(c(10.0, 12.0, 10.0, 11.5, 0)), Some(1.0));
+    }
+
+    #[test]
+    fn bearish_belt_hold_is_minus_one() {
+        let mut t = BeltHold::new();
+        assert_eq!(t.update(c(12.0, 12.0, 10.0, 10.5, 0)), Some(-1.0));
+    }
+
+    #[test]
+    fn opening_shadow_yields_zero() {
+        let mut t = BeltHold::new();
+        // Opens 0.5 above the low -> lower shadow exceeds tolerance.
+        assert_eq!(t.update(c(10.5, 12.0, 10.0, 11.5, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn short_body_yields_zero() {
+        let mut t = BeltHold::new();
+        // Body 0.5 < half the range (1.0) -> not a long belt-hold.
+        assert_eq!(t.update(c(10.0, 12.0, 10.0, 10.5, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn zero_range_yields_zero() {
+        let mut t = BeltHold::new();
+        assert_eq!(t.update(c(10.0, 10.0, 10.0, 10.0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + i as f64;
+                c(base, base + 2.0, base, base + 1.8, i)
+            })
+            .collect();
+        let mut a = BeltHold::new();
+        let mut b = BeltHold::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = BeltHold::new();
+        t.update(c(10.0, 12.0, 10.0, 11.5, 0));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+    }
+}
@@ -0,0 +1,247 @@
+//! Beta-neutral spread: the rolling OLS regression residual of two series.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// The beta-neutral spread between two assets — the residual of a rolling
+/// ordinary-least-squares regression of `a` on `b`.
+///
+/// Each `update` takes one `(a, b)` price pair. Over the trailing window of
+/// `period` pairs the indicator fits the hedge ratio `β` (and intercept `α`) by
+/// OLS and reports the **current** residual:
+///
+/// ```text
+/// β = cov(a, b) / var(b)        α = ā − β · b̄
+/// spread = a_now − (α + β · b_now)
+/// ```
+///
+/// Subtracting `β · b` removes `a`'s exposure to `b`, so the spread is market-
+/// (beta-)neutral: it is what is left after the common factor is hedged out.
+/// Positive means `a` is rich relative to its hedge, negative means cheap — the
+/// raw signal a pairs trade fades. Where [`crate::PairSpreadZScore`] standardises
+/// this residual into a z-score and [`crate::Cointegration`] bundles it with an
+/// ADF test, this indicator returns the residual itself, in price units.
+///
+/// If `b` is flat over the window (`var(b) = 0`) there is no defined slope; the
+/// indicator falls back to `β = 0`, so the spread becomes `a_now − ā`.
+///
+/// Each `update` is `O(1)`: four running sums (`Σa`, `Σb`, `Σb²`, `Σab`) are
+/// maintained as the window slides.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BetaNeutralSpread, Indicator};
+///
+/// let mut s = BetaNeutralSpread::new(20).unwrap();
+/// let mut last = None;
+/// for t in 0..40 {
+///     let b = 100.0 + f64::from(t);
+///     // a = 2·b + 5 exactly ⇒ the regression explains a fully ⇒ spread ≈ 0.
+///     last = s.update((2.0 * b + 5.0, b));
+/// }
+/// assert!(last.unwrap().abs() < 1e-6);
+/// ```
+#[derive(Debug, Clone)]
+pub struct BetaNeutralSpread {
+    period: usize,
+    window: VecDeque<(f64, f64)>,
+    sum_a: f64,
+    sum_b: f64,
+    sum_bb: f64,
+    sum_ab: f64,
+}
+
+impl BetaNeutralSpread {
+    /// Construct a new beta-neutral spread.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` — a regression slope
+    /// needs at least two points.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "beta-neutral spread needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+            sum_a: 0.0,
+            sum_b: 0.0,
+            sum_bb: 0.0,
+            sum_ab: 0.0,
+        })
+    }
+
+    /// Configured look-back window.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for BetaNeutralSpread {
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        let (a, b) = input;
+        if self.window.len() == self.period {
+            let (oa, ob) = self.window.pop_front().expect("non-empty");
+            self.sum_a -= oa;
+            self.sum_b -= ob;
+            self.sum_bb -= ob * ob;
+            self.sum_ab -= oa * ob;
+        }
+        self.window.push_back((a, b));
+        self.sum_a += a;
+        self.sum_b += b;
+        self.sum_bb += b * b;
+        self.sum_ab += a * b;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let n = self.period as f64;
+        let mean_a = self.sum_a / n;
+        let mean_b = self.sum_b / n;
+        let var_b = (self.sum_bb / n - mean_b * mean_b).max(0.0);
+        let (beta, intercept) = if var_b == 0.0 {
+            (0.0, mean_a)
+        } else {
+            let cov = self.sum_ab / n - mean_a * mean_b;
+            let slope = cov / var_b;
+            (slope, mean_a - slope * mean_b)
+        };
+        Some(a - (intercept + beta * b))
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum_a = 0.0;
+        self.sum_b = 0.0;
+        self.sum_bb = 0.0;
+        self.sum_ab = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "BetaNeutralSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(BetaNeutralSpread::new(1).is_err());
+        assert!(BetaNeutralSpread::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let s = BetaNeutralSpread::new(20).unwrap();
+        assert_eq!(s.period(), 20);
+        assert_eq!(s.warmup_period(), 20);
+        assert_eq!(s.name(), "BetaNeutralSpread");
+        assert!(!s.is_ready());
+    }
+
+    #[test]
+    fn warmup_returns_none() {
+        let mut s = BetaNeutralSpread::new(3).unwrap();
+        assert_eq!(s.update((1.0, 1.0)), None);
+        assert_eq!(s.update((2.0, 2.0)), None);
+        assert!(s.update((3.0, 3.0)).is_some());
+        assert!(s.is_ready());
+    }
+
+    #[test]
+    fn perfect_linear_relationship_has_zero_spread() {
+        let pairs: Vec<(f64, f64)> = (0..40)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                (2.0 * b + 5.0, b)
+            })
+            .collect();
+        let last = BetaNeutralSpread::new(20)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-6);
+    }
+
+    #[test]
+    fn dislocation_produces_nonzero_spread() {
+        // a tracks 2·b, then the last bar jumps up ⇒ positive residual.
+        let mut pairs: Vec<(f64, f64)> = (0..19)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                (2.0 * b + 5.0, b)
+            })
+            .collect();
+        pairs.push((2.0 * 119.0 + 5.0 + 10.0, 119.0));
+        let last = BetaNeutralSpread::new(20)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last > 1.0, "spread {last}");
+    }
+
+    #[test]
+    fn flat_b_falls_back_to_demeaned_a() {
+        // b constant ⇒ β = 0 ⇒ spread = a − mean(a). Last window of a = 0..9,
+        // mean = 4.5, last a = 9 ⇒ spread = 4.5.
+        let pairs: Vec<(f64, f64)> = (0..10).map(|t| (f64::from(t), 7.0)).collect();
+        let last = BetaNeutralSpread::new(10)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 4.5, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut s = BetaNeutralSpread::new(4).unwrap();
+        s.batch(&[(1.0, 2.0), (2.0, 4.0), (3.0, 5.0), (4.0, 9.0), (5.0, 2.0)]);
+        assert!(s.is_ready());
+        s.reset();
+        assert!(!s.is_ready());
+        assert_eq!(s.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|t| {
+                let b = 30.0 + 0.7 * f64::from(t);
+                (1.8 * b + 2.0 + (f64::from(t) * 0.4).sin(), b)
+            })
+            .collect();
+        let batch = BetaNeutralSpread::new(20).unwrap().batch(&pairs);
+        let mut s = BetaNeutralSpread::new(20).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| s.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}
@@ -0,0 +1,281 @@
+//! Realized Bipower Variation — a jump-robust quadratic-variation estimator.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Realized Bipower Variation — the sum of *adjacent* absolute log-return
+/// products over the trailing `period` returns, scaled to estimate integrated
+/// variance.
+///
+/// ```text
+/// r_t = ln(price_t / price_{t−1})
+/// BV  = (π / 2) · Σ |r_t| · |r_{t−1}|   over the window
+/// ```
+///
+/// Bipower variation (Barndorff-Nielsen & Shephard 2004) estimates the same
+/// integrated variance as [`RealizedVolatility`](crate::RealizedVolatility)'s
+/// `Σ r²`, but by multiplying *neighbouring* absolute returns rather than
+/// squaring a single one. A price jump inflates exactly one return; because that
+/// return appears in a product with its (ordinary) neighbour rather than squared,
+/// its contribution stays bounded — so `BV` is **robust to jumps** while realized
+/// variance is not. The constant `π / 2 = μ₁⁻²` (with `μ₁ = E|Z| = √(2/π)` for a
+/// standard normal) debiases the product of two half-normal magnitudes back to a
+/// variance scale.
+///
+/// The output is on the **variance** scale (the jump-robust counterpart of
+/// realized *variance*, not volatility); take its square root for a volatility,
+/// and compare `RV − BV` to isolate the jump contribution. A window of `period`
+/// returns contributes `period − 1` adjacent products; each `update` is O(1) via
+/// a running sum.
+///
+/// Non-finite and non-positive prices are ignored (the log return would be
+/// undefined): the tick is dropped, state is left untouched, and the last value
+/// is returned.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BipowerVariation, Indicator};
+///
+/// let mut indicator = BipowerVariation::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + (f64::from(i) * 0.3).sin() * 5.0);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct BipowerVariation {
+    period: usize,
+    prev_price: Option<f64>,
+    /// Rolling window of the last `period` log returns.
+    window: VecDeque<f64>,
+    /// Running sum of adjacent absolute-return products inside the window.
+    sum_adjacent: f64,
+    last: Option<f64>,
+}
+
+impl BipowerVariation {
+    /// Construct a new bipower-variation indicator.
+    ///
+    /// `period` is the number of log returns in the rolling window; the estimate
+    /// uses the `period − 1` adjacent products between them.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`, or
+    /// [`Error::InvalidPeriod`] if `period == 1` (an adjacent product needs at
+    /// least two returns).
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "bipower variation period must be >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            prev_price: None,
+            window: VecDeque::with_capacity(period),
+            sum_adjacent: 0.0,
+            last: None,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+/// `μ₁⁻² = π / 2`, the debiasing constant for a product of half-normal returns.
+const MU1_INV_SQ: f64 = std::f64::consts::FRAC_PI_2;
+
+impl Indicator for BipowerVariation {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        // Non-finite / non-positive prices are skipped: `ln(input / prev)` is
+        // undefined, so the tick must not enter the return window.
+        if !input.is_finite() || input <= 0.0 {
+            return self.last;
+        }
+        let Some(prev) = self.prev_price else {
+            self.prev_price = Some(input);
+            return None;
+        };
+        self.prev_price = Some(input);
+        // `prev` came from `self.prev_price`, gated by the guard above, so it is
+        // finite and positive — the log return is always well-defined.
+        let r = (input / prev).ln();
+        // The incoming return forms a product with the current last return.
+        if let Some(&back) = self.window.back() {
+            self.sum_adjacent += back.abs() * r.abs();
+        }
+        self.window.push_back(r);
+        if self.window.len() > self.period {
+            let first = self.window.pop_front().expect("window is non-empty");
+            // The product between the dropped return and the new front leaves.
+            let second = *self.window.front().expect("window still has >= 1 element");
+            self.sum_adjacent -= first.abs() * second.abs();
+        }
+        if self.window.len() < self.period {
+            return None;
+        }
+        // Products are non-negative; the rolling subtraction can leave a tiny
+        // negative residual when returns are ~0, so clamp before scaling.
+        let bv = MU1_INV_SQ * self.sum_adjacent.max(0.0);
+        self.last = Some(bv);
+        Some(bv)
+    }
+
+    fn reset(&mut self) {
+        self.prev_price = None;
+        self.window.clear();
+        self.sum_adjacent = 0.0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // The first log return needs a previous price, then the window fills.
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "BipowerVariation"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BipowerVariation::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn rejects_period_one() {
+        assert!(matches!(
+            BipowerVariation::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bv = BipowerVariation::new(20).unwrap();
+        assert_eq!(bv.period(), 20);
+        assert_eq!(bv.warmup_period(), 21);
+        assert_eq!(bv.name(), "BipowerVariation");
+        assert!(!bv.is_ready());
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let out = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        for v in out.iter().take(5) {
+            assert!(v.is_none());
+        }
+        assert!(out[5].is_some());
+    }
+
+    #[test]
+    fn known_value() {
+        // period = 2: one adjacent product. r1 = ln(1.1), r2 = ln(0.9).
+        // BV = (π/2)·|r1|·|r2|.
+        let mut bv = BipowerVariation::new(2).unwrap();
+        let out = bv.batch(&[100.0, 110.0, 99.0]);
+        assert!(out[1].is_none());
+        let r1 = (110.0_f64 / 100.0).ln();
+        let r2 = (99.0_f64 / 110.0).ln();
+        let expected = std::f64::consts::FRAC_PI_2 * r1.abs() * r2.abs();
+        assert_relative_eq!(out[2].unwrap(), expected, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rolling_window_drops_oldest_product() {
+        // period = 2, four prices -> two emissions, each a single product.
+        let mut bv = BipowerVariation::new(2).unwrap();
+        let out = bv.batch(&[100.0, 110.0, 99.0, 105.0]);
+        let r2 = (99.0_f64 / 110.0).ln();
+        let r3 = (105.0_f64 / 99.0).ln();
+        let expected = std::f64::consts::FRAC_PI_2 * r2.abs() * r3.abs();
+        assert_relative_eq!(out[3].unwrap(), expected, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn constant_series_yields_zero() {
+        let mut bv = BipowerVariation::new(10).unwrap();
+        for v in bv.batch(&[100.0; 40]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn output_is_non_negative() {
+        let mut bv = BipowerVariation::new(20).unwrap();
+        let prices: Vec<f64> = (1..=200)
+            .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 12.0)
+            .collect();
+        for v in bv.batch(&prices).into_iter().flatten() {
+            assert!(v >= 0.0, "bipower variation must be non-negative, got {v}");
+        }
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let out = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let last = *out.last().unwrap();
+        assert!(last.is_some());
+        assert_eq!(bv.update(f64::NAN), last);
+        assert_eq!(bv.update(f64::INFINITY), last);
+    }
+
+    #[test]
+    fn skips_non_positive_prices() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let warmup = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let baseline = warmup.last().copied().flatten().expect("warmed up");
+        assert_eq!(bv.update(-5.0), Some(baseline));
+        assert_eq!(bv.update(0.0), Some(baseline));
+        // State untouched: a clone advanced by the same real tick agrees.
+        let mut control = bv.clone();
+        let after = bv.update(21.0).expect("ready");
+        assert_eq!(control.update(21.0).expect("ready"), after);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        assert!(bv.is_ready());
+        bv.reset();
+        assert!(!bv.is_ready());
+        assert_eq!(bv.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=120)
+            .map(|i| 100.0 + (f64::from(i) * 0.25).sin() * 9.0)
+            .collect();
+        let batch = BipowerVariation::new(20).unwrap().batch(&prices);
+        let mut b = BipowerVariation::new(20).unwrap();
+        let streamed: Vec<_> = prices.iter().map(|p| b.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}
@@ -0,0 +1,193 @@
+//! Body Size Percent — candle body as a fraction of its range.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Body Size Percent — the absolute body as a fraction of the bar's range.
+///
+/// ```text
+/// BodySizePct = |close − open| / (high − low)
+/// ```
+///
+/// The result lives in `[0, 1]`: `1` is a full-bodied marubozu (the bar opened
+/// at one extreme and closed at the other, no wicks), `0` a doji (open equals
+/// close, the bar is all wick). It is the *unsigned* magnitude companion to
+/// [`BalanceOfPower`](crate::BalanceOfPower) — where `BoP` keeps the direction,
+/// this keeps only the conviction, which is exactly what candlestick body /
+/// range filters key on. A zero-range bar carries no information and yields `0`.
+///
+/// This is a stateless per-bar transform: every candle produces one value.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, BodySizePct};
+///
+/// let mut indicator = BodySizePct::new();
+/// // body |12 - 10| = 2, range 14 - 10 = 4 -> 0.5.
+/// let c = Candle::new(10.0, 14.0, 10.0, 12.0, 10.0, 0).unwrap();
+/// assert!((indicator.update(c).unwrap() - 0.5).abs() < 1e-12);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct BodySizePct {
+    has_emitted: bool,
+}
+
+impl BodySizePct {
+    /// Construct a new Body Size Percent transform.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for BodySizePct {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let range = candle.high - candle.low;
+        let out = if range == 0.0 {
+            // A zero-range bar has no body proportion to speak of.
+            0.0
+        } else {
+            (candle.close - candle.open).abs() / range
+        };
+        Some(out)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "BodySizePct"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn candle(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn reference_value() {
+        // |12 - 10| / (14 - 10) = 0.5.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 14.0, 10.0, 12.0, 0)).unwrap(),
+            0.5,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn marubozu_is_one() {
+        // open == low, close == high, no wicks -> full body -> 1.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(9.0, 11.0, 9.0, 11.0, 0)).unwrap(),
+            1.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn doji_is_zero() {
+        // open == close with a real range -> body 0.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 12.0, 8.0, 10.0, 0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn unsigned_regardless_of_direction() {
+        // A red bar with the same body magnitude reads identically to a green one.
+        let mut bsp = BodySizePct::new();
+        let green = bsp.update(candle(10.0, 14.0, 10.0, 12.0, 0)).unwrap();
+        let mut bsp2 = BodySizePct::new();
+        let red = bsp2.update(candle(12.0, 14.0, 10.0, 10.0, 0)).unwrap();
+        assert_relative_eq!(green, red, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn zero_range_bar_yields_zero() {
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 10.0, 10.0, 10.0, 0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn stays_within_unit_range() {
+        let candles: Vec<Candle> = (0..100)
+            .map(|i| {
+                let mid = 100.0 + (f64::from(i) * 0.2).sin() * 8.0;
+                let close = mid + (f64::from(i) * 0.5).cos() * 2.0;
+                candle(mid, mid + 3.0, mid - 3.0, close, i64::from(i))
+            })
+            .collect();
+        let mut bsp = BodySizePct::new();
+        for v in bsp.batch(&candles).into_iter().flatten() {
+            assert!((0.0..=1.0).contains(&v), "BodySizePct {v} outside [0, 1]");
+        }
+    }
+
+    #[test]
+    fn name_metadata() {
+        let bsp = BodySizePct::new();
+        assert_eq!(bsp.name(), "BodySizePct");
+    }
+
+    #[test]
+    fn emits_from_first_candle() {
+        let mut bsp = BodySizePct::new();
+        assert_eq!(bsp.warmup_period(), 1);
+        assert!(!bsp.is_ready());
+        assert!(bsp.update(candle(10.0, 11.0, 9.0, 10.0, 0)).is_some());
+        assert!(bsp.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bsp = BodySizePct::new();
+        bsp.update(candle(10.0, 11.0, 9.0, 10.0, 0));
+        assert!(bsp.is_ready());
+        bsp.reset();
+        assert!(!bsp.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + f64::from(i);
+                candle(base, base + 2.0, base - 2.0, base + 1.0, i64::from(i))
+            })
+            .collect();
+        let mut a = BodySizePct::new();
+        let mut b = BodySizePct::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -1,7 +1,5 @@
 //! Bollinger Bands.

-use std::collections::VecDeque;
-
 use crate::error::{Error, Result};
 use crate::traits::Indicator;

@@ -49,7 +47,13 @@ pub struct BollingerOutput {
 pub struct BollingerBands {
    period: usize,
    multiplier: f64,
-    window: VecDeque<f64>,
+    /// Fixed-capacity ring buffer of the last `period` finite inputs. A flat
+    /// `Box<[f64]>` with a manual write cursor beats `VecDeque` on this hot path.
+    buf: Box<[f64]>,
+    /// Index of the next slot to write — also the oldest element once full.
+    head: usize,
+    /// Number of slots filled, saturating at `period`.
+    count: usize,
    sum: f64,
    sum_sq: f64,
    /// Number of finite updates since the running sums were last reseeded
@@ -80,7 +84,9 @@ impl BollingerBands {
        Ok(Self {
            period,
            multiplier,
-            window: VecDeque::with_capacity(period),
+            buf: vec![0.0; period].into_boxed_slice(),
+            head: 0,
+            count: 0,
            sum: 0.0,
            sum_sq: 0.0,
            updates_since_recompute: 0,
@@ -103,7 +109,7 @@ impl BollingerBands {
    }

    fn current(&self) -> Option<BollingerOutput> {
-        if self.window.len() != self.period {
+        if self.count != self.period {
            return None;
        }
        let n = self.period as f64;
@@ -129,25 +135,38 @@ impl Indicator for BollingerBands {
        if !input.is_finite() {
            return self.current();
        }
-        if self.window.len() == self.period {
-            let old = self.window.pop_front().expect("non-empty");
+        if self.count == self.period {
+            let old = self.buf[self.head];
            self.sum -= old;
            self.sum_sq -= old * old;
+            self.buf[self.head] = input;
+            self.sum += input;
+            self.sum_sq += input * input;
+        } else {
+            self.buf[self.head] = input;
+            self.sum += input;
+            self.sum_sq += input * input;
+            self.count += 1;
+        }
+        self.head += 1;
+        if self.head == self.period {
+            self.head = 0;
        }
-        self.window.push_back(input);
-        self.sum += input;
-        self.sum_sq += input * input;
        self.updates_since_recompute += 1;
        if self.updates_since_recompute >= RECOMPUTE_EVERY * self.period {
-            self.sum = self.window.iter().copied().sum();
-            self.sum_sq = self.window.iter().copied().map(|x| x * x).sum();
+            // Reseed in chronological order (oldest at `head`) to keep the running
+            // sums bit-equivalent to a fresh from-scratch pass on stable inputs.
+            let chronological = self.buf[self.head..].iter().chain(&self.buf[..self.head]);
+            self.sum = chronological.clone().copied().sum();
+            self.sum_sq = chronological.map(|&x| x * x).sum();
            self.updates_since_recompute = 0;
        }
        self.current()
    }

    fn reset(&mut self) {
-        self.window.clear();
+        self.head = 0;
+        self.count = 0;
        self.sum = 0.0;
        self.sum_sq = 0.0;
        self.updates_since_recompute = 0;
@@ -158,7 +177,7 @@ impl Indicator for BollingerBands {
    }

    fn is_ready(&self) -> bool {
-        self.window.len() == self.period
+        self.count == self.period
    }

    fn name(&self) -> &'static str {
@@ -171,6 +190,7 @@ mod tests {
    use super::*;
    use crate::traits::BatchExt;
    use approx::assert_relative_eq;
+    use std::collections::VecDeque;

    fn naive(prices: &[f64], period: usize, mult: f64) -> BollingerOutput {
        assert!(
@@ -0,0 +1,256 @@
+//! Bomar Bands — adaptive percentage bands that contain a target fraction of
+//! recent price.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::indicators::rolling_quantile::quantile_sorted;
+use crate::traits::Indicator;
+
+/// Bomar Bands output.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct BomarBandsOutput {
+    /// Upper band: `middle + |middle| · p`.
+    pub upper: f64,
+    /// Middle line: the simple moving average over the window.
+    pub middle: f64,
+    /// Lower band: `middle − |middle| · p`.
+    pub lower: f64,
+}
+
+/// Bomar Bands: percentage bands whose width adapts so that a fixed `coverage`
+/// fraction of recent closes falls inside them.
+///
+/// The Bomar Bands predate Bollinger Bands; John Bollinger cites them as an
+/// inspiration — percentage bands around a moving average, with the percentage
+/// tuned so a fixed share (classically ~85%) of price stayed within. Wickra
+/// realises that idea deterministically: the half-width is the `coverage`
+/// quantile of the relative deviations from the midline, so by construction
+/// `coverage` of the window's closes lie inside the bands.
+///
+/// ```text
+/// middle = SMA(close, period)
+/// dev_i  = | close_i / middle − 1 |          // relative distance from midline
+/// p      = coverage-quantile of { dev_i }     // type-7 interpolation
+/// upper  = middle + |middle| · p
+/// lower  = middle − |middle| · p
+/// ```
+///
+/// Unlike the fixed-percentage [`MaEnvelope`](crate::MaEnvelope), the offset
+/// here is data-driven: the bands widen in turbulent regimes and tighten in
+/// quiet ones without a volatility input. Unlike Bollinger Bands, the width is
+/// an order statistic of the actual deviations rather than a multiple of the
+/// standard deviation, so it is unaffected by the shape of the tails beyond the
+/// `coverage` rank. When the midline is zero the relative deviation is
+/// undefined and the bands collapse onto the midline.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BomarBands, Indicator};
+///
+/// let mut indicator = BomarBands::new(20, 0.85).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update(100.0 + f64::from(i % 7));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct BomarBands {
+    period: usize,
+    coverage: f64,
+    window: VecDeque<f64>,
+    scratch: Vec<f64>,
+}
+
+impl BomarBands {
+    /// Construct new Bomar Bands.
+    ///
+    /// `coverage` is the target fraction of closes to contain, in `(0.0, 1.0]`.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`, or
+    /// [`Error::InvalidParameter`] if `coverage` is not a finite value in
+    /// `(0.0, 1.0]`.
+    pub fn new(period: usize, coverage: f64) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if !coverage.is_finite() || coverage <= 0.0 || coverage > 1.0 {
+            return Err(Error::InvalidParameter {
+                message: "bomar bands coverage must be a finite value in (0.0, 1.0]",
+            });
+        }
+        Ok(Self {
+            period,
+            coverage,
+            window: VecDeque::with_capacity(period),
+            scratch: Vec::with_capacity(period),
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Configured coverage fraction.
+    pub const fn coverage(&self) -> f64 {
+        self.coverage
+    }
+}
+
+impl Indicator for BomarBands {
+    type Input = f64;
+    type Output = BomarBandsOutput;
+
+    fn update(&mut self, value: f64) -> Option<BomarBandsOutput> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(value);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let sum: f64 = self.window.iter().sum();
+        let middle = sum / (self.period as f64);
+        let denom = middle.abs();
+
+        self.scratch.clear();
+        for &v in &self.window {
+            let dev = if denom == 0.0 {
+                0.0
+            } else {
+                ((v - middle) / denom).abs()
+            };
+            self.scratch.push(dev);
+        }
+        self.scratch.sort_by(f64::total_cmp);
+        let p = quantile_sorted(&self.scratch, self.coverage);
+        let offset = denom * p;
+
+        Some(BomarBandsOutput {
+            upper: middle + offset,
+            middle,
+            lower: middle - offset,
+        })
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.scratch.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "BomarBands"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BomarBands::new(0, 0.85), Err(Error::PeriodZero)));
+        assert!(BomarBands::new(1, 0.85).is_ok());
+    }
+
+    #[test]
+    fn rejects_out_of_range_coverage() {
+        assert!(matches!(
+            BomarBands::new(20, 0.0),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, 1.1),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, -0.5),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, f64::NAN),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bb = BomarBands::new(20, 0.85).unwrap();
+        assert_eq!(bb.period(), 20);
+        assert_relative_eq!(bb.coverage(), 0.85, epsilon = 1e-12);
+        assert_eq!(bb.warmup_period(), 20);
+        assert_eq!(bb.name(), "BomarBands");
+        assert!(!bb.is_ready());
+    }
+
+    #[test]
+    fn warms_up_then_emits() {
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        assert!(bb.update(100.0).is_none());
+        assert!(bb.update(102.0).is_none());
+        assert!(bb.update(98.0).is_none());
+        assert!(bb.update(104.0).is_some());
+        assert!(bb.is_ready());
+    }
+
+    #[test]
+    fn known_bands() {
+        // mean=101; |dev| = {1,1,3,3}/101; coverage 0.85 quantile -> 3/101.
+        // offset = 101 * 3/101 = 3 -> upper 104, lower 98.
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        let out = bb.batch(&[100.0, 102.0, 98.0, 104.0]);
+        let last = out[3].unwrap();
+        assert_relative_eq!(last.middle, 101.0, epsilon = 1e-9);
+        assert_relative_eq!(last.upper, 104.0, epsilon = 1e-9);
+        assert_relative_eq!(last.lower, 98.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn zero_midline_collapses_bands() {
+        // Window mean exactly zero -> relative deviation undefined -> collapse.
+        let mut bb = BomarBands::new(2, 0.85).unwrap();
+        let out = bb.batch(&[3.0, -3.0]);
+        let last = out[1].unwrap();
+        assert_relative_eq!(last.middle, 0.0, epsilon = 1e-12);
+        assert_relative_eq!(last.upper, 0.0, epsilon = 1e-12);
+        assert_relative_eq!(last.lower, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rolling_window_evicts_oldest() {
+        // Eight values through a period-4 window: only the last four survive,
+        // reproducing the `known_bands` window.
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        let out = bb.batch(&[50.0, 50.0, 50.0, 50.0, 100.0, 102.0, 98.0, 104.0]);
+        let last = out[7].unwrap();
+        assert_relative_eq!(last.middle, 101.0, epsilon = 1e-9);
+        assert_relative_eq!(last.upper, 104.0, epsilon = 1e-9);
+        assert_relative_eq!(last.lower, 98.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        for v in [100.0, 102.0, 98.0, 104.0] {
+            bb.update(v);
+        }
+        assert!(bb.is_ready());
+        bb.reset();
+        assert!(!bb.is_ready());
+        assert!(bb.update(100.0).is_none());
+    }
+}
@@ -0,0 +1,165 @@
+//! Breadth Thrust (Zweig) — a moving average of the advancing-issues share.
+
+use crate::cross_section::CrossSection;
+use crate::error::Result;
+use crate::traits::Indicator;
+use crate::Sma;
+
+/// Breadth Thrust (Zweig) — a simple moving average of the advancing-issues
+/// share, `advancers / (advancers + decliners)`.
+///
+/// Martin Zweig's breadth thrust smooths the fraction of participating issues
+/// that are advancing over a short window (the classic period is 10). A "thrust"
+/// fires when this average climbs from below ~0.40 (oversold, washed-out breadth)
+/// to above ~0.615 within about ten sessions — historically a rare, reliable
+/// signal that a powerful new advance has begun with broad participation.
+///
+/// Each tick's share floors the participating count to one, so a tick with no
+/// advancing or declining issues contributes a defined `0.0` instead of dividing
+/// by zero. The reading is `None` until `period` ticks have been seen.
+///
+/// `Input = CrossSection`, `Output = f64` (a share in `0..=1`),
+/// `warmup_period == period`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BreadthThrust, CrossSection, Indicator, Member};
+///
+/// let mut bt = BreadthThrust::new(2).unwrap();
+/// let up = CrossSection::new(vec![Member::new(1.0, 1.0, false, false)], 0).unwrap();
+/// assert_eq!(bt.update(up.clone()), None); // warming up
+/// assert_eq!(bt.update(up), Some(1.0)); // both ticks 100% advancing
+/// ```
+#[derive(Debug, Clone)]
+pub struct BreadthThrust {
+    sma: Sma,
+}
+
+impl BreadthThrust {
+    /// Construct a new Breadth Thrust over the given window length.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`](crate::Error::PeriodZero) if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        Ok(Self {
+            sma: Sma::new(period)?,
+        })
+    }
+
+    /// Configured window length.
+    #[must_use]
+    pub const fn period(&self) -> usize {
+        self.sma.period()
+    }
+}
+
+impl Indicator for BreadthThrust {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let advancers = section.advancers();
+        let decliners = section.decliners();
+        let participating = (advancers + decliners).max(1) as f64;
+        let share = advancers as f64 / participating;
+        self.sma.update(share)
+    }
+
+    fn reset(&mut self) {
+        self.sma.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.sma.period()
+    }
+
+    fn is_ready(&self) -> bool {
+        self.sma.value().is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "BreadthThrust"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::error::Error;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bt = BreadthThrust::new(10).unwrap();
+        assert_eq!(bt.name(), "BreadthThrust");
+        assert_eq!(bt.warmup_period(), 10);
+        assert_eq!(bt.period(), 10);
+        assert!(!bt.is_ready());
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BreadthThrust::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn averages_the_advancing_share() {
+        let mut bt = BreadthThrust::new(2).unwrap();
+        // share = 8 / 10 = 0.8 ; window not full yet.
+        assert_eq!(bt.update(section(8, 2)), None);
+        // share = 6 / 10 = 0.6 ; SMA(2) = (0.8 + 0.6) / 2 = 0.7.
+        let value = bt.update(section(6, 4)).unwrap();
+        assert!((value - 0.7).abs() < 1e-9);
+        assert!(bt.is_ready());
+        // share = 5 / 10 = 0.5 ; SMA(2) = (0.6 + 0.5) / 2 = 0.55.
+        let value = bt.update(section(5, 5)).unwrap();
+        assert!((value - 0.55).abs() < 1e-9);
+    }
+
+    #[test]
+    fn empty_participation_floors_to_zero_share() {
+        let mut bt = BreadthThrust::new(1).unwrap();
+        // No advancers or decliners -> 0 / max(0, 1) = 0.0.
+        assert_eq!(bt.update(section(0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bt = BreadthThrust::new(2).unwrap();
+        bt.update(section(8, 2));
+        bt.update(section(6, 4));
+        assert!(bt.is_ready());
+        bt.reset();
+        assert!(!bt.is_ready());
+        assert_eq!(bt.update(section(8, 2)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(8, 2), section(6, 4), section(5, 5), section(0, 0)];
+        let mut a = BreadthThrust::new(2).unwrap();
+        let mut b = BreadthThrust::new(2).unwrap();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,250 @@
+//! Breakaway candlestick pattern.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Breakaway — a 5-bar reversal that fades an exhausted run. A trend gaps away on
+/// the second bar, drifts two more bars in the same direction, then the fifth bar
+/// snaps the other way and closes back inside the body gap left between the first
+/// and second bars, signalling the move has broken away from the crowd and is
+/// turning.
+///
+/// ```text
+/// bullish (+1.0)  — appears in a decline:
+///   bar1 black (close < open)
+///   bar2 black & its body gaps DOWN below bar1's body  (bar2.open < bar1.close)
+///   bar3 extends lower            (high & low below bar2)
+///   bar4 black & extends lower    (high & low below bar3)
+///   bar5 green & closes inside the bar1/bar2 body gap   (bar2.open < close < bar1.close)
+///
+/// bearish (−1.0) — the mirror in an advance:
+///   bar1 white (close > open)
+///   bar2 white & its body gaps UP above bar1's body    (bar2.open > bar1.close)
+///   bar3 extends higher           (high & low above bar2)
+///   bar4 white & extends higher   (high & low above bar3)
+///   bar5 red & closes inside the bar1/bar2 body gap     (bar1.close < close < bar2.open)
+/// ```
+///
+/// The middle bar (`bar3`) may be either colour — only its high/low must extend
+/// the run. Output is `+1.0` bullish, `−1.0` bearish, `0.0` otherwise. The first
+/// four bars always return `0.0` because the five-bar window is not yet filled.
+/// Pattern-shape check only — no trend filter is applied; combine with a trend
+/// indicator for actionable signals. Recognition uses TA-Lib's
+/// `CDLBREAKAWAY` body-gap and high/low ordering rules directly; it does not add
+/// TA-Lib's rolling body-length average, matching the geometric house style of
+/// the other multi-bar patterns in this family.
+///
+/// # Signed ±1 encoding
+///
+/// This detector emits the uniform candlestick sign convention shared across the
+/// pattern family — `+1.0` bullish, `−1.0` bearish, `0.0` no pattern — so it
+/// drops straight into a machine-learning feature matrix where the bullish and
+/// bearish variants occupy a single dimension.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Breakaway, Candle, Indicator};
+///
+/// let mut indicator = Breakaway::new();
+/// indicator.update(Candle::new(20.0, 20.2, 14.8, 15.0, 1.0, 0).unwrap());
+/// indicator.update(Candle::new(14.0, 14.1, 11.9, 12.0, 1.0, 1).unwrap());
+/// indicator.update(Candle::new(12.5, 13.0, 10.5, 11.0, 1.0, 2).unwrap());
+/// indicator.update(Candle::new(11.0, 11.5, 9.0, 9.5, 1.0, 3).unwrap());
+/// let out = indicator
+///     .update(Candle::new(9.5, 14.7, 9.4, 14.5, 1.0, 4).unwrap());
+/// assert_eq!(out, Some(1.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct Breakaway {
+    c1: Option<Candle>,
+    c2: Option<Candle>,
+    c3: Option<Candle>,
+    c4: Option<Candle>,
+    has_emitted: bool,
+}
+
+impl Breakaway {
+    /// Construct a new Breakaway detector.
+    pub const fn new() -> Self {
+        Self {
+            c1: None,
+            c2: None,
+            c3: None,
+            c4: None,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for Breakaway {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let bar1 = self.c1;
+        let bar2 = self.c2;
+        let bar3 = self.c3;
+        let bar4 = self.c4;
+        self.c1 = self.c2;
+        self.c2 = self.c3;
+        self.c3 = self.c4;
+        self.c4 = Some(candle);
+        let (Some(bar1), Some(bar2), Some(bar3), Some(bar4)) = (bar1, bar2, bar3, bar4) else {
+            return Some(0.0);
+        };
+        // Bullish: a decline gaps lower, runs two more bars down, then a green
+        // bar5 closes back inside the bar1/bar2 body gap.
+        if bar1.close < bar1.open
+            && bar2.close < bar2.open
+            && bar2.open < bar1.close
+            && bar3.high < bar2.high
+            && bar3.low < bar2.low
+            && bar4.close < bar4.open
+            && bar4.high < bar3.high
+            && bar4.low < bar3.low
+            && candle.close > candle.open
+            && candle.close > bar2.open
+            && candle.close < bar1.close
+        {
+            return Some(1.0);
+        }
+        // Bearish: the mirror — an advance gaps higher, runs two more bars up,
+        // then a red bar5 closes back inside the bar1/bar2 body gap.
+        if bar1.close > bar1.open
+            && bar2.close > bar2.open
+            && bar2.open > bar1.close
+            && bar3.high > bar2.high
+            && bar3.low > bar2.low
+            && bar4.close > bar4.open
+            && bar4.high > bar3.high
+            && bar4.low > bar3.low
+            && candle.close < candle.open
+            && candle.close < bar2.open
+            && candle.close > bar1.close
+        {
+            return Some(-1.0);
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.c1 = None;
+        self.c2 = None;
+        self.c3 = None;
+        self.c4 = None;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        5
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Breakaway"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = Breakaway::new();
+        assert_eq!(t.name(), "Breakaway");
+        assert_eq!(t.warmup_period(), 5);
+        assert!(!t.is_ready());
+    }
+
+    #[test]
+    fn bullish_breakaway_is_plus_one() {
+        let mut t = Breakaway::new();
+        assert_eq!(t.update(c(20.0, 20.2, 14.8, 15.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(14.0, 14.1, 11.9, 12.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(12.5, 13.0, 10.5, 11.0, 2)), Some(0.0));
+        assert_eq!(t.update(c(11.0, 11.5, 9.0, 9.5, 3)), Some(0.0));
+        assert_eq!(t.update(c(9.5, 14.7, 9.4, 14.5, 4)), Some(1.0));
+    }
+
+    #[test]
+    fn bearish_breakaway_is_minus_one() {
+        let mut t = Breakaway::new();
+        assert_eq!(t.update(c(15.0, 20.2, 14.8, 20.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(21.0, 23.1, 20.9, 23.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(22.5, 24.5, 21.5, 24.0, 2)), Some(0.0));
+        assert_eq!(t.update(c(24.0, 26.5, 23.0, 26.0, 3)), Some(0.0));
+        assert_eq!(t.update(c(27.0, 27.2, 20.4, 20.5, 4)), Some(-1.0));
+    }
+
+    #[test]
+    fn no_body_gap_yields_zero() {
+        let mut t = Breakaway::new();
+        // bar2 does not gap below bar1's body (bar2.open >= bar1.close).
+        t.update(c(20.0, 20.2, 14.8, 15.0, 0));
+        t.update(c(16.0, 16.1, 13.9, 14.0, 1));
+        t.update(c(13.5, 14.0, 11.5, 12.0, 2));
+        t.update(c(12.0, 12.5, 10.0, 10.5, 3));
+        assert_eq!(t.update(c(10.5, 15.7, 10.4, 15.5, 4)), Some(0.0));
+    }
+
+    #[test]
+    fn bullish_close_outside_gap_yields_zero() {
+        let mut t = Breakaway::new();
+        t.update(c(20.0, 20.2, 14.8, 15.0, 0));
+        t.update(c(14.0, 14.1, 11.9, 12.0, 1));
+        t.update(c(12.5, 13.0, 10.5, 11.0, 2));
+        t.update(c(11.0, 11.5, 9.0, 9.5, 3));
+        // bar5 closes at 13.0 — below bar2.open (14), so outside the body gap.
+        assert_eq!(t.update(c(9.5, 13.2, 9.4, 13.0, 4)), Some(0.0));
+    }
+
+    #[test]
+    fn first_four_bars_return_zero() {
+        let mut t = Breakaway::new();
+        assert_eq!(t.update(c(20.0, 20.2, 14.8, 15.0, 0)), Some(0.0));
+        assert_eq!(t.update(c(14.0, 14.1, 11.9, 12.0, 1)), Some(0.0));
+        assert_eq!(t.update(c(12.5, 13.0, 10.5, 11.0, 2)), Some(0.0));
+        assert_eq!(t.update(c(11.0, 11.5, 9.0, 9.5, 3)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + i as f64;
+                c(base, base + 2.0, base - 0.5, base + 1.5, i)
+            })
+            .collect();
+        let mut a = Breakaway::new();
+        let mut b = Breakaway::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = Breakaway::new();
+        t.update(c(20.0, 20.2, 14.8, 15.0, 0));
+        t.update(c(14.0, 14.1, 11.9, 12.0, 1));
+        t.update(c(12.5, 13.0, 10.5, 11.0, 2));
+        t.update(c(11.0, 11.5, 9.0, 9.5, 3));
+        t.update(c(9.5, 14.7, 9.4, 14.5, 4));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.update(c(20.0, 20.2, 14.8, 15.0, 0)), Some(0.0));
+    }
+}
@@ -0,0 +1,147 @@
+//! Bullish Percent Index — share of a universe on a point-and-figure buy signal.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Bullish Percent Index (BPI) — the percentage of symbols in a universe that are
+/// currently on a point-and-figure buy signal.
+///
+/// On each [`CrossSection`] tick the value is `100 * on_buy_signal_count /
+/// universe size`, read from the per-symbol `on_buy_signal` flag (the caller
+/// evaluates each symbol's point-and-figure chart when it builds the tick). It is
+/// a bounded `0..=100` gauge of how many issues are in a confirmed uptrend.
+/// Readings above 70 are considered overbought (broad strength, but a crowded
+/// market) and below 30 oversold; reversals from those zones are classic BPI
+/// buy/sell triggers.
+///
+/// `Input = CrossSection`, `Output = f64` (a percentage in `0..=100`),
+/// `warmup_period == 1`. The universe is non-empty by construction, so the share
+/// is always defined.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BullishPercentIndex, CrossSection, Indicator, Member};
+///
+/// let mut bpi = BullishPercentIndex::new();
+/// // 2 of 4 symbols on a buy signal -> 50%.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::with_signals(1.0, 10.0, false, false, false, true),
+///         Member::with_signals(1.0, 10.0, false, false, false, true),
+///         Member::with_signals(-1.0, 10.0, false, false, false, false),
+///         Member::with_signals(-1.0, 10.0, false, false, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(bpi.update(tick), Some(50.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct BullishPercentIndex {
+    has_emitted: bool,
+}
+
+impl BullishPercentIndex {
+    /// Construct a new Bullish Percent Index indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for BullishPercentIndex {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let bullish = section.on_buy_signal_count() as f64;
+        let total = section.members.len() as f64;
+        self.has_emitted = true;
+        Some(100.0 * bullish / total)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "BullishPercentIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn tick(bullish: usize, bearish: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..bullish {
+            members.push(Member::with_signals(1.0, 10.0, false, false, false, true));
+        }
+        for _ in 0..bearish {
+            members.push(Member::with_signals(-1.0, 10.0, false, false, false, false));
+        }
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.name(), "BullishPercentIndex");
+        assert_eq!(bpi.warmup_period(), 1);
+        assert!(!bpi.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_percentage() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(2, 2)), Some(50.0));
+        assert!(bpi.is_ready());
+    }
+
+    #[test]
+    fn all_bullish_is_one_hundred() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(5, 0)), Some(100.0));
+    }
+
+    #[test]
+    fn none_bullish_is_zero() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(0, 4)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bpi = BullishPercentIndex::new();
+        bpi.update(tick(2, 2));
+        assert!(bpi.is_ready());
+        bpi.reset();
+        assert!(!bpi.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![tick(2, 2), tick(5, 0), tick(0, 4)];
+        let mut a = BullishPercentIndex::new();
+        let mut b = BullishPercentIndex::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,154 @@
+//! Butterfly harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Butterfly — a 5-point (X-A-B-C-D) harmonic pattern with a `0.786` B and an
+/// **extended** D that overshoots X:
+///
+/// ```text
+/// AB / XA ∈ [0.74, 0.84]   (≈ 0.786)
+/// BC / AB ∈ [0.382, 0.886]
+/// CD / BC ∈ [1.618, 2.618]
+/// AD / XA ∈ [1.27, 1.618]  (the defining extended D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/butterfly.rs`.
+#[derive(Debug, Clone)]
+pub struct Butterfly {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Butterfly {
+    /// Construct a new Butterfly detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Butterfly {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Butterfly {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let cd = (p.d - p.c).abs();
+        let ad = (p.d - p.a).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.74, 0.84),
+            (bc / ab, 0.382, 0.886),
+            (cd / bc, 1.618, 2.618),
+            (ad / xa, 1.27, 1.618),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Butterfly"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Butterfly::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Butterfly::new();
+        assert_eq!(indicator.name(), "Butterfly");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Butterfly::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_butterfly_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 108.6, 128.0, 79.8]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_butterfly_is_minus_one() {
+        let out = run(&[150.0, 110.0, 141.4, 121.4, 170.2]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Butterfly::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 108.6, 128.0, 79.8]);
+        let mut a = Butterfly::new();
+        let mut b = Butterfly::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}
@@ -0,0 +1,141 @@
+//! Calendar Spread — the dated future's relative premium to the perpetual.
+
+use crate::derivatives::DerivativesTick;
+use crate::traits::Indicator;
+
+/// Calendar Spread — the relative spread between a dated (e.g. quarterly)
+/// futures price and the perpetual mark price.
+///
+/// ```text
+/// spread = (futuresPrice − markPrice) / markPrice
+/// ```
+///
+/// A calendar (or inter-delivery) spread trades the *near* leg against the
+/// *far* leg — here the perpetual against a dated future. The relative spread is
+/// the roll yield available between the two contracts: positive when the future
+/// trades over the perpetual (contango roll), negative when under
+/// (backwardation). Where [`TermStructureBasis`] measures the future against
+/// spot, this measures it against the perpetual — the leg a perp-vs-future
+/// basis trade actually holds. The output is a fraction; multiply by `10_000`
+/// for basis points.
+///
+/// `Input = DerivativesTick`, `Output = f64`. Stateless; ready after the first
+/// tick.
+///
+/// [`TermStructureBasis`]: crate::TermStructureBasis
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{CalendarSpread, DerivativesTick, Indicator};
+///
+/// fn tick(futures: f64, mark: f64) -> DerivativesTick {
+///     DerivativesTick::new(0.0, mark, mark, futures, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0)
+///         .unwrap()
+/// }
+///
+/// let mut cs = CalendarSpread::new();
+/// // futures 101 vs perpetual mark 100 -> 0.01.
+/// assert!((cs.update(tick(101.0, 100.0)).unwrap() - 0.01).abs() < 1e-12);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct CalendarSpread {
+    has_emitted: bool,
+}
+
+impl CalendarSpread {
+    /// Construct a new calendar-spread indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for CalendarSpread {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        self.has_emitted = true;
+        Some((tick.futures_price - tick.mark_price) / tick.mark_price)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "CalendarSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn tick(futures: f64, mark: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(
+            0.0, mark, mark, futures, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
+        )
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let cs = CalendarSpread::new();
+        assert_eq!(cs.name(), "CalendarSpread");
+        assert_eq!(cs.warmup_period(), 1);
+        assert!(!cs.is_ready());
+    }
+
+    #[test]
+    fn future_over_perp_is_positive() {
+        let mut cs = CalendarSpread::new();
+        let out = cs.update(tick(101.0, 100.0)).unwrap();
+        assert!((out - 0.01).abs() < 1e-12);
+        assert!(cs.is_ready());
+    }
+
+    #[test]
+    fn future_under_perp_is_negative() {
+        let mut cs = CalendarSpread::new();
+        let out = cs.update(tick(99.0, 100.0)).unwrap();
+        assert!((out + 0.01).abs() < 1e-12);
+    }
+
+    #[test]
+    fn flat_is_zero() {
+        let mut cs = CalendarSpread::new();
+        assert_eq!(cs.update(tick(100.0, 100.0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..20)
+            .map(|i| tick(100.0 + f64::from(i % 5), 100.0))
+            .collect();
+        let mut a = CalendarSpread::new();
+        let mut b = CalendarSpread::new();
+        assert_eq!(
+            a.batch(&ticks),
+            ticks.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut cs = CalendarSpread::new();
+        cs.update(tick(101.0, 100.0));
+        assert!(cs.is_ready());
+        cs.reset();
+        assert!(!cs.is_ready());
+    }
+}
--- a/Show More
+++ b/Show More