release: bump 0.4.2 -> 0.4.3 (#125)

* feat: effective spread microstructure indicator (part 3 of 4)

* feat: realized spread microstructure indicator (part 3 of 4)

* feat: kyle's lambda microstructure indicator (part 3 of 4)

* feat: depth slope microstructure indicator (part 3 of 4)

.gitattributes

@@ -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

.github/FUNDING.yml

@@ -3,4 +3,3 @@
 # Leave a key empty (e.g. patreon:) to skip a platform.
 
 github: [kingchenc]
-custom: ["https://wickra.org/sponsor"]

.github/PULL_REQUEST_TEMPLATE.md

@@ -24,9 +24,9 @@
 - [ ] New behaviour has tests; bug fixes have a regression test.
 - [ ] Public API changes are mirrored in the Python / Node / WASM bindings
       and their type stubs (If applicable).
-- [ ] The relevant page on the [project Wiki](https://github.com/wickra-lib/wickra/wiki)
-      and the `README.md` are updated (If applicable). Wiki edits go to a
-      separate repository: `https://github.com/wickra-lib/wickra.wiki.git`.
+- [ ] The relevant page on the [documentation site](https://docs.wickra.org)
+      and the `README.md` are updated (If applicable). Docs edits go to a
+      separate repository: `https://github.com/wickra-lib/wickra-docs`.
 - [ ] An entry was added under `## [Unreleased]` in `CHANGELOG.md`.
 
 ## Notes for reviewers

.github/dependabot.yml

@@ -27,6 +27,19 @@ updates:
     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
+    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

.github/requirements/bench.in

@@ -0,0 +1,9 @@
+# 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
+talipp
+finta

.github/requirements/bench.txt

@@ -0,0 +1,167 @@
+# This file was autogenerated by uv via the following command:
+#    ./scripts/update-lockfiles.sh
+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
+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
+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
+talipp==2.7.0 \
+    --hash=sha256:567f59ad74366cb59a14a00d350f35fd9d22e6924d6228bad581e6dcf1de2205 \
+    --hash=sha256:f749f22b9ad615605e71faf26457bb7f5e3fe16f04d3287f4ca54fd16bc3d4eb
+    # via -r .github/requirements/bench.in
+tzdata==2026.2 \
+    --hash=sha256:9173fde7d80d9018e02a662e168e5a2d04f87c41ea174b139fbef642eda62d10 \
+    --hash=sha256:bbe9af844f658da81a5f95019480da3a89415801f6cc966806612cc7169bffe7
+    # via pandas

.github/requirements/ci-dev-py3.in

@@ -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

.github/requirements/ci-dev-py3.txt

@@ -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

.github/requirements/ci-dev-py39.in

@@ -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

.github/requirements/ci-dev-py39.txt

@@ -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

.github/workflows/bench.yml

@@ -22,8 +22,26 @@ on:
         required: false
         default: "10"
 
+# Least-privilege default for the auto-injected GITHUB_TOKEN. The single job
+# only builds and uploads an artifact (upload-artifact uses the artifact
+# storage API, not the contents scope), so it never needs repo write (OpenSSF
+# Scorecard: Token-Permissions).
+permissions:
+  contents: read
+
 env:
   CARGO_TERM_COLOR: always
+  # Network-flake resilience: retry transient registry/DNS failures at the tool
+  # level so a blip fetching crates.io / PyPI inside any build step (cargo,
+  # maturin, pip) retries automatically instead of failing the job. Cargo treats
+  # "couldn't resolve host" / connect / timeout as spurious and retries with
+  # backoff; 10 attempts ride out a transient DNS blip on a runner.
+  CARGO_NET_RETRY: "10"
+  CARGO_NET_GIT_FETCH_WITH_CLI: "true"
+  npm_config_fetch_retries: "5"
+  npm_config_fetch_retry_maxtimeout: "120000"
+  PIP_RETRIES: "5"
+  PIP_DEFAULT_TIMEOUT: "120"
 
 jobs:
   cross-library-bench:
@@ -35,16 +53,39 @@ jobs:
       - 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
 
       - name: Set up Python
+        id: setup_python
+        continue-on-error: true
         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'
+        shell: bash
+        run: |
+          echo "::warning::setup-python failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Python (retry)
+        if: steps.setup_python.outcome == 'failure'
+        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
@@ -56,10 +97,16 @@ jobs:
 
       - name: Run cross-library benchmark
         working-directory: bindings/python
+        # workflow_dispatch inputs are untrusted; pass them through the
+        # environment and quote them rather than interpolating into the shell
+        # command (OpenSSF Scorecard: Dangerous-Workflow).
+        env:
+          BENCH_SIZE: ${{ github.event.inputs.size || '20000' }}
+          BENCH_ITERATIONS: ${{ github.event.inputs.iterations || '10' }}
         run: |
           python -m benchmarks.compare_libraries \
-            --size ${{ github.event.inputs.size || '20000' }} \
-            --iterations ${{ github.event.inputs.iterations || '10' }} \
+            --size "$BENCH_SIZE" \
+            --iterations "$BENCH_ITERATIONS" \
             --streaming-window 5000 --streaming-iterations 2 \
             | tee benchmark.txt
 

.github/workflows/ci.yml

@@ -6,9 +6,29 @@ on:
   pull_request:
     branches: [main]
 
+# Least-privilege default for the auto-injected GITHUB_TOKEN. None of the CI
+# jobs write back to the repo — coverage uploads via CODECOV_TOKEN, everything
+# else is build/test/lint — so a read-only token is sufficient (OpenSSF
+# Scorecard: Token-Permissions).
+permissions:
+  contents: read
+
 env:
   CARGO_TERM_COLOR: always
   RUSTFLAGS: "-D warnings"
+  # Network-flake resilience: retry transient registry/DNS failures at the tool
+  # level so a blip fetching crates.io / npm / PyPI inside any build step (cargo,
+  # napi, maturin, wasm-pack, npm ci, pip) retries automatically instead of
+  # failing the job and needing a manual re-run. Cargo treats "couldn't resolve
+  # host" / connect / timeout as spurious and retries with backoff; 10 attempts
+  # ride out a transient DNS blip on a runner. Complements the setup-action /
+  # cache retries (which only covered toolchain download + cache restore).
+  CARGO_NET_RETRY: "10"
+  CARGO_NET_GIT_FETCH_WITH_CLI: "true"
+  npm_config_fetch_retries: "5"
+  npm_config_fetch_retry_maxtimeout: "120000"
+  PIP_RETRIES: "5"
+  PIP_DEFAULT_TIMEOUT: "120"
 
 jobs:
   rust:
@@ -28,6 +48,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Format check
         run: cargo fmt --all -- --check
@@ -55,6 +77,95 @@ jobs:
         # streaming.
         run: cargo build -p wickra-examples --bins
 
+  # Syntax/parse smoke for the non-Rust examples. The Rust examples are built
+  # in the `rust` job above (`cargo build -p wickra-examples --bins`); the Node,
+  # browser-WASM and Python examples otherwise have no build gate, so a broken
+  # edit could land unnoticed. This is a parse-only smoke — actually running the
+  # examples needs the built native binding / wasm module / wheel, which the
+  # binding jobs provide separately.
+  examples-smoke:
+    name: Examples (syntax smoke)
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+      - name: Set up Node
+        id: setup_node
+        continue-on-error: true
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+
+      - name: Wait before Node retry
+        if: steps.setup_node.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-node failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Node (retry)
+        if: steps.setup_node.outcome == 'failure'
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+
+      - name: Set up Python
+        id: setup_python
+        continue-on-error: true
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
+        with:
+          python-version: "3.12"
+
+      - name: Wait before Python retry
+        if: steps.setup_python.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-python failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Python (retry)
+        if: steps.setup_python.outcome == 'failure'
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
+        with:
+          python-version: "3.12"
+
+      - name: Node examples — syntax check
+        run: |
+          shopt -s nullglob
+          count=0
+          for f in examples/node/*.js examples/wasm/*.js; do
+            echo "node --check $f"
+            node --check "$f"
+            count=$((count + 1))
+          done
+          echo "checked $count Node/WASM .js files"
+
+      - name: WASM demo module scripts — syntax check
+        # The .html demos embed an ES module; extract it and parse-check so a
+        # broken edit to the in-page strategy logic fails CI.
+        run: |
+          shopt -s nullglob
+          count=0
+          for f in examples/wasm/*.html; do
+            node -e 'const fs=require("fs");const h=fs.readFileSync(process.argv[1],"utf8");const m=h.match(/<script type="module">([\s\S]*?)<\/script>/);if(!m){console.error("no <script type=module> in "+process.argv[1]);process.exit(1);}fs.writeFileSync("module-check.mjs",m[1]);' "$f"
+            echo "node --check (module of) $f"
+            node --check module-check.mjs
+            count=$((count + 1))
+          done
+          rm -f module-check.mjs
+          echo "checked $count WASM .html module scripts"
+
+      - name: Python examples — byte-compile
+        run: |
+          shopt -s nullglob
+          count=0
+          for f in examples/python/*.py; do
+            echo "py_compile $f"
+            python -m py_compile "$f"
+            count=$((count + 1))
+          done
+          echo "compiled $count Python files"
+
   # Clippy for the Python and Node bindings. These are kept out of the main
   # `rust` job because PyO3 / napi build scripts need a Python interpreter and
   # a Node toolchain on PATH, which the 3-OS matrix job does not provision.
@@ -71,17 +182,49 @@ jobs:
           components: clippy
 
       - name: Set up Python
+        id: setup_python
+        continue-on-error: true
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Wait before Python retry
+        if: steps.setup_python.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-python failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Python (retry)
+        if: steps.setup_python.outcome == 'failure'
         uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
         with:
           python-version: "3.12"
 
       - name: Set up Node
+        id: setup_node
+        continue-on-error: true
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+
+      - name: Wait before Node retry
+        if: steps.setup_node.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-node failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Node (retry)
+        if: steps.setup_node.outcome == 'failure'
         uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: "20"
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Clippy (bindings, all targets)
         run: cargo clippy -p wickra-node -p wickra-python --all-targets -- -D warnings
@@ -118,6 +261,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Build on MSRV
         run: cargo build ${{ matrix.packages }} --verbose
@@ -139,9 +284,12 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Install cargo-llvm-cov
         uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
         with:
           tool: cargo-llvm-cov
 
@@ -191,6 +339,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
         with:
           workspaces: fuzz
 
@@ -203,6 +353,7 @@ jobs:
         # never gets off the ground. The prebuilt binary avoids the entire
         # transitive-dep compile.
         uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
         with:
           tool: cargo-fuzz
 
@@ -242,6 +393,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       # setup-python downloads the interpreter from the Actions tool cache /
       # nodejs CDN and occasionally hangs or 5xx's on the Windows runners.
@@ -254,6 +407,8 @@ 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'
@@ -267,11 +422,21 @@ 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
@@ -304,6 +469,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Install wasm-pack
         # jetli/wasm-pack-action@v0.4.0 with no `version:` input installs an
@@ -314,6 +481,7 @@ jobs:
         # cargo-llvm-cov and cargo-fuzz; it tracks the latest wasm-pack
         # release, which has `--features` as a top-level flag (since 0.12).
         uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
         with:
           tool: wasm-pack
 
@@ -345,6 +513,8 @@ jobs:
 
       - name: Cache cargo
         uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       # setup-node downloads Node from nodejs.org and we've seen it fail on
       # Windows runners with "Attempting to download 18..." followed by a
@@ -356,6 +526,8 @@ 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'
@@ -369,10 +541,12 @@ 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

.github/workflows/codeql.yml

@@ -0,0 +1,54 @@
+name: CodeQL
+
+# Static analysis security testing (findings P13.x). Analyses the Rust core and
+# the Python / JavaScript binding surfaces with GitHub's CodeQL engine. Results
+# appear under Security → Code scanning. `build-mode: none` analyses source
+# directly — no compilation step — for every language here.
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+  schedule:
+    - cron: '31 3 * * 0' # Sundays 03:31 UTC
+
+# Least-privilege default for the auto-injected GITHUB_TOKEN. The analyze job
+# raises exactly the scopes CodeQL needs (security-events: write to upload
+# results) in its own job-level block below; this top-level read-only default
+# covers any future job (OpenSSF Scorecard: Token-Permissions).
+permissions:
+  contents: read
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    runs-on: ubuntu-latest
+    permissions:
+      security-events: write # upload CodeQL results to code-scanning
+      packages: read
+      actions: read
+      contents: read
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - language: rust
+            build-mode: none
+          - language: python
+            build-mode: none
+          - language: javascript-typescript
+            build-mode: none
+    steps:
+      - name: Checkout
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+
+      - name: Initialize CodeQL
+        uses: github/codeql-action/init@03e4368ac7daa2bd82b3e85262f3bf87ee112f57 # v3.36.0
+        with:
+          languages: ${{ matrix.language }}
+          build-mode: ${{ matrix.build-mode }}
+
+      - name: Perform CodeQL analysis
+        uses: github/codeql-action/analyze@03e4368ac7daa2bd82b3e85262f3bf87ee112f57 # v3.36.0
+        with:
+          category: "/language:${{ matrix.language }}"

.github/workflows/release.yml

@@ -5,8 +5,30 @@ on:
     tags: ["v*"]
   workflow_dispatch:
 
+# Least-privilege default for the auto-injected GITHUB_TOKEN. The publish jobs
+# (cargo/python/node) push to external registries via their own secrets
+# (CARGO_REGISTRY_TOKEN / PYPI_API_TOKEN / NPM_TOKEN), not the GITHUB_TOKEN, so
+# they need no repo write. The jobs that genuinely write through the
+# GITHUB_TOKEN — github-release (contents: write), node-/wasm-publish and
+# attestations (id-token / attestations: write) — declare those rights in their
+# own job-level permissions blocks, which override this default (OpenSSF
+# Scorecard: Token-Permissions).
+permissions:
+  contents: read
+
 env:
   CARGO_TERM_COLOR: always
+  # Network-flake resilience: retry transient registry/DNS failures at the tool
+  # level so a blip fetching crates.io / npm inside any build or publish step
+  # (cargo, napi, maturin, wasm-pack, npm) retries automatically instead of
+  # failing the job. Cargo treats "couldn't resolve host" / connect / timeout as
+  # spurious and retries with backoff; 10 attempts ride out a transient DNS blip.
+  CARGO_NET_RETRY: "10"
+  CARGO_NET_GIT_FETCH_WITH_CLI: "true"
+  npm_config_fetch_retries: "5"
+  npm_config_fetch_retry_maxtimeout: "120000"
+  PIP_RETRIES: "5"
+  PIP_DEFAULT_TIMEOUT: "120"
 
 jobs:
   # --------------------------------------------------------------------------
@@ -26,6 +48,8 @@ jobs:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
       - 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
 
       # Idempotent publishing: if the version is already on crates.io we
       # treat that as success so re-runs of the workflow don't fail.
@@ -85,6 +109,7 @@ jobs:
       # re-resolving Cargo.lock.
       - name: Install cargo-cyclonedx
         uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
         with:
           tool: cargo-cyclonedx
 
@@ -131,7 +156,21 @@ jobs:
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
+      - name: Set up Python
+        id: setup_python
+        continue-on-error: true
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
+        with:
+          python-version: "3.11"
+      - name: Wait before Python retry
+        if: steps.setup_python.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-python failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+      - name: Set up Python (retry)
+        if: steps.setup_python.outcome == 'failure'
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
         with:
           python-version: "3.11"
       - name: Sync root README into bindings/python so it ships with the wheel
@@ -206,7 +245,23 @@ jobs:
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
 
-      - uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+      - name: Set up Node
+        id: setup_node
+        continue-on-error: true
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+
+      - name: Wait before Node retry
+        if: steps.setup_node.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-node failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Node (retry)
+        if: steps.setup_node.outcome == 'failure'
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: "20"
 
@@ -215,10 +270,12 @@ jobs:
           targets: ${{ matrix.target }}
 
       - uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
 
       - name: Install Node deps
         working-directory: bindings/node
-        run: npm install
+        run: npm ci
 
       - name: Build native module
         working-directory: bindings/node
@@ -247,14 +304,31 @@ jobs:
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
 
-      - uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+      - name: Set up Node
+        id: setup_node
+        continue-on-error: true
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+          registry-url: "https://registry.npmjs.org"
+
+      - name: Wait before Node retry
+        if: steps.setup_node.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-node failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Node (retry)
+        if: steps.setup_node.outcome == 'failure'
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: "20"
           registry-url: "https://registry.npmjs.org"
 
       - 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
@@ -397,7 +471,24 @@ jobs:
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
 
-      - uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+      - name: Set up Node
+        id: setup_node
+        continue-on-error: true
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        with:
+          node-version: "20"
+          registry-url: "https://registry.npmjs.org"
+
+      - name: Wait before Node retry
+        if: steps.setup_node.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-node failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Node (retry)
+        if: steps.setup_node.outcome == 'failure'
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: "20"
           registry-url: "https://registry.npmjs.org"
@@ -410,6 +501,7 @@ jobs:
         # See the matching note in ci.yml: jetli's default installs an old
         # 0.10.x wasm-pack whose build subcommand rejects --features.
         uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
         with:
           tool: wasm-pack
 
@@ -428,7 +520,7 @@ jobs:
           node -e "
             const fs = require('fs');
             const pkg = JSON.parse(fs.readFileSync('package.json'));
-            pkg.author = 'kingchenc <wickra.lib@gmail.com>';
+            pkg.author = 'kingchenc <support@wickra.org>';
             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' };
@@ -457,13 +549,24 @@ jobs:
 
   # --------------------------------------------------------------------------
   # GitHub Release: attach every built artefact to the tag's release page.
+  #
+  # The release is created as a DRAFT here and only flipped to published by the
+  # downstream publish-release job, after the provenance bundle is attached. That
+  # ordering (draft -> attach everything -> publish) makes the pipeline compatible
+  # with GitHub release immutability, which locks assets at publish time (P24):
+  # the old "publish, then upload provenance" order would have the provenance
+  # upload rejected once immutability is enabled.
   # --------------------------------------------------------------------------
   github-release:
-    name: Attach assets to the GitHub Release
+    name: Attach assets to the draft GitHub Release
     needs: [cargo-publish, python-publish, node-publish, wasm-publish]
     runs-on: ubuntu-latest
     permissions:
       contents: write
+    # Expose the resolved tag so the attestations job can attach the provenance
+    # bundle to this same release without re-resolving it.
+    outputs:
+      tag: ${{ steps.tag.outputs.tag }}
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
         with:
@@ -508,7 +611,7 @@ jobs:
           ls -lh release-assets/
           echo "asset-count=$(ls release-assets/ | wc -l)"
 
-      - name: Create / update GitHub Release with assets
+      - name: Create / update the draft GitHub Release with assets
         uses: softprops/action-gh-release@b4309332981a82ec1c5618f44dd2e27cc8bfbfda # v3.0.0
         with:
           tag_name: ${{ steps.tag.outputs.tag }}
@@ -516,6 +619,9 @@ jobs:
           files: release-assets/*
           generate_release_notes: true
           fail_on_unmatched_files: false
+          # Created as a draft; publish-release flips it to published + latest once
+          # the provenance bundle is attached (P24, immutability-ready).
+          draft: true
           body: |
             Wickra ${{ github.ref_name }} — streaming-first technical indicators across 4 language registries.
 
@@ -541,4 +647,110 @@ jobs:
 
             ### Auto-generated changelog
 
-            See below; GitHub computes it from the commits since the previous tag.
+            See below; GitHub computes it from the commits since the previous tag.
+
+  # --------------------------------------------------------------------------
+  # Build provenance attestations (findings P13.2)
+  # --------------------------------------------------------------------------
+  attestations:
+    name: Attest build provenance
+    needs: [cargo-publish, python-wheels, python-sdist, github-release]
+    runs-on: ubuntu-latest
+    # Signed SLSA build-provenance attestations for the published crates and
+    # Python wheels/sdist. npm tarballs already carry inline Sigstore provenance
+    # from `npm publish --provenance`, so they are covered there.
+    #
+    # The job stays isolated from the *publishes*: cargo/PyPI/npm all run upstream
+    # of github-release, so a Sigstore hiccup here can never block or corrupt a
+    # publish (the isolation the SBOM step lacked before #79). It additionally
+    # `needs: github-release` so the (still-draft) GitHub Release already exists
+    # when it attaches the provenance bundle as a release asset (P21.1e) — OpenSSF
+    # Scorecard's Signed-Releases check scans release *assets* (*.intoto.jsonl),
+    # not GitHub's separate attestations store, so the bundle has to live on the
+    # release. The release is published afterwards by the publish-release job
+    # whether or not this attestation succeeds (P24), so a failure here still only
+    # costs the provenance asset, never the release.
+    permissions:
+      id-token: write # OIDC for keyless Sigstore signing
+      attestations: write # write the attestations to this repo
+      contents: write # upload the provenance bundle as a release asset
+    steps:
+      - name: Download crate files
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+        with:
+          name: crate-files
+          path: artifacts/crates
+      - name: Download wheels + sdist
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+        with:
+          pattern: wheels-*
+          path: artifacts/python
+          merge-multiple: true
+      - name: Attest build provenance
+        id: attest
+        uses: actions/attest-build-provenance@a2bbfa25375fe432b6a289bc6b6cd05ecd0c4c32 # v4.1.0
+        with:
+          subject-path: |
+            artifacts/crates/*.crate
+            artifacts/python/*.whl
+            artifacts/python/*.tar.gz
+
+      # Attach the Sigstore provenance bundle to the GitHub Release as a
+      # `*.intoto.jsonl` asset so OpenSSF Scorecard's Signed-Releases check finds
+      # signed provenance on the release itself (P21.1e). attest-build-provenance
+      # writes a single JSONL bundle covering every subject above; copy it to a
+      # `.intoto.jsonl`-suffixed name and upload with --clobber so re-runs are
+      # idempotent. github.token has contents: write here, which is all gh needs.
+      - name: Attach provenance bundle to the GitHub Release
+        env:
+          GH_TOKEN: ${{ github.token }}
+          TAG: ${{ needs.github-release.outputs.tag }}
+          BUNDLE: ${{ steps.attest.outputs.bundle-path }}
+        run: |
+          if [ -z "$TAG" ]; then
+            echo "::error::no tag resolved from github-release; cannot attach provenance."
+            exit 1
+          fi
+          if [ -z "$BUNDLE" ] || [ ! -f "$BUNDLE" ]; then
+            echo "::error::attestation bundle not found at '$BUNDLE'."
+            exit 1
+          fi
+          dest="wickra-${TAG}.provenance.intoto.jsonl"
+          cp "$BUNDLE" "$dest"
+          echo "Uploading $dest to release $TAG"
+          gh release upload "$TAG" "$dest" --clobber --repo "${{ github.repository }}"
+
+  # --------------------------------------------------------------------------
+  # Publish the drafted release LAST (P24 — immutability-ready).
+  #
+  # github-release creates the release as a draft and attestations attaches the
+  # provenance bundle to it; only now, with every asset in place, is it flipped to
+  # published + latest. With GitHub release immutability enabled, assets lock at
+  # this publish step — so the provenance bundle and every build artefact are
+  # already present and never need a (rejected) post-publish upload.
+  #
+  # `if: always() && needs.github-release.result == 'success'` preserves the old
+  # robustness: the release is published whenever the draft was created, even if
+  # the attestations job hit a Sigstore hiccup — that only costs the provenance
+  # asset, exactly as before. If github-release was skipped (a publish job failed)
+  # there is no draft, so this is skipped too and no release is published.
+  # --------------------------------------------------------------------------
+  publish-release:
+    name: Publish the GitHub Release
+    needs: [github-release, attestations]
+    if: always() && needs.github-release.result == 'success'
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write # flip the draft release to published
+    steps:
+      - name: Flip the draft release to published (latest)
+        env:
+          GH_TOKEN: ${{ github.token }}
+          TAG: ${{ needs.github-release.outputs.tag }}
+        run: |
+          if [ -z "$TAG" ]; then
+            echo "::error::no tag resolved from github-release; cannot publish."
+            exit 1
+          fi
+          echo "::notice::publishing release $TAG (draft -> published, latest)"
+          gh release edit "$TAG" --draft=false --latest=true --repo "${{ github.repository }}"

.github/workflows/scorecard.yml

@@ -0,0 +1,49 @@
+name: OpenSSF Scorecard
+
+# Supply-chain / security-posture analysis (findings P13.1). Runs on a weekly
+# schedule, on branch-protection changes, and on push to main. `publish_results`
+# uploads the score to the public OpenSSF API so the README badge resolves, and
+# the SARIF is surfaced under the repo's Security → Code scanning tab.
+on:
+  branch_protection_rule:
+  schedule:
+    - cron: '27 7 * * 2' # Tuesdays 07:27 UTC
+  push:
+    branches: [main]
+  workflow_dispatch:
+
+# Read-only by default; the analysis job widens to exactly what it needs.
+permissions: read-all
+
+jobs:
+  analysis:
+    name: Scorecard analysis
+    runs-on: ubuntu-latest
+    permissions:
+      security-events: write # upload the SARIF result to code-scanning
+      id-token: write # OIDC token to publish results to the OpenSSF API
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Run Scorecard analysis
+        uses: ossf/scorecard-action@4eaacf0543bb3f2c246792bd56e8cdeffafb205a # v2.4.3
+        with:
+          results_file: results.sarif
+          results_format: sarif
+          # Publish to the public OpenSSF endpoint that backs the README badge.
+          publish_results: true
+
+      - name: Upload SARIF artifact
+        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: SARIF file
+          path: results.sarif
+          retention-days: 5
+
+      - name: Upload SARIF to code-scanning
+        uses: github/codeql-action/upload-sarif@03e4368ac7daa2bd82b3e85262f3bf87ee112f57 # v3.36.0
+        with:
+          sarif_file: results.sarif

.github/workflows/sync-about.yml

@@ -7,9 +7,34 @@ name: Sync indicator count
 #
 #   1. README.md prose                       — synced on PR branches (this workflow)
 #   2. GitHub repo "About" description       — synced on push to main / v* tag
-#   3. Wiki: Home.md / FAQ.md / Streaming-vs-Batch.md
-#                                            — synced on push to main / v* tag
-#   4. site/index.md (local-only marketing site, not synced from CI)
+#   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) — 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.")
+#                                            — synced on push to main / v* tag*
+#   7. docs site published version (wickra-lib/wickra-docs: the
+#      "Published versions" table in overview.md + the Rust quickstart prose)
+#                                            — synced on v* tag only*
+#   8. Marketing site version (wickra-lib/webpage: api/*.md "Latest" lines, the
+#      nav version label, and the wickra-wasm dep) — synced on v* tag only*
+#   9. Wiki pointer page count (wickra-lib/wickra.wiki, Home.md — the wiki was
+#      collapsed to a single page that points at docs.wickra.org but still names
+#      the count) — synced on push to main / v* tag*
+#
+#   *Surfaces 3 + 7 need the ABOUT_SYNC_TOKEN to have write on
+#   wickra-lib/wickra-docs, surfaces 4 + 8 on wickra-lib/webpage; surfaces 5 + 6
+#   need write on wickra-lib/.github and admin:org for the org-description PATCH;
+#   surface 9 needs write on wickra-lib/wickra (the wiki rides on the parent
+#   repo's permission).
+#   Until that scope is granted these steps emit a ::warning:: and soft-skip —
+#   they never fail the run. The repo "About" homepage URL is also enforced in
+#   step 2 (constant value, no extra scope); it points at docs.wickra.org.
+#
+#   Note: surface 7 carries the release *version*, not the indicator count, so
+#   it is driven by the v* tag (which is the version) rather than the count.
 #
 # We count public types (not `mod xxx;` lines) because some modules export
 # more than one indicator — e.g. `vwap.rs` exposes both `Vwap` and
@@ -35,18 +60,24 @@ on:
     types: [opened, synchronize, reopened]
   workflow_dispatch:
 
-# `contents: write` is needed so the workflow can push the counter
-# fix-up commit to the PR head branch via the auto-provided
-# GITHUB_TOKEN. The wider About / Wiki writes still go through the
-# fine-grained PAT (ABOUT_SYNC_TOKEN) because they need
-# `Administration: write` (gh repo edit) which GITHUB_TOKEN lacks.
+# Least-privilege default for the auto-injected GITHUB_TOKEN. The `contents:
+# write` the workflow needs — to push the counter fix-up commit to the PR head
+# branch — is raised at the job level below, not here, so the top-level default
+# stays read-only (OpenSSF Scorecard: Token-Permissions). The wider About /
+# docs / webpage / org writes still go through the fine-grained PAT
+# (ABOUT_SYNC_TOKEN), which the `permissions:` key does not govern at all.
 permissions:
-  contents: write
+  contents: read
   pull-requests: read
 
 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>).
+    permissions:
+      contents: write
+      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
@@ -54,11 +85,20 @@ jobs:
       # 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: ${{ github.event.pull_request.head.ref }}
         run: |
-          if [ "${{ github.event_name }}" = "pull_request" ]; then
-            if [ "${{ github.event.pull_request.head.repo.full_name }}" = "${{ github.repository }}" ]; then
+          if [ "$EVENT_NAME" = "pull_request" ]; then
+            if [ "$HEAD_REPO" = "$BASE_REPO" ]; then
               echo "can_push=true" >> "$GITHUB_OUTPUT"
-              echo "head_ref=${{ github.event.pull_request.head.ref }}" >> "$GITHUB_OUTPUT"
+              echo "head_ref=$HEAD_REF" >> "$GITHUB_OUTPUT"
             else
               echo "can_push=false" >> "$GITHUB_OUTPUT"
               echo "head_ref=" >> "$GITHUB_OUTPUT"
@@ -72,7 +112,7 @@ jobs:
       # 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".
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
         with:
           fetch-depth: 0
           ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.ref || github.ref }}
@@ -125,6 +165,10 @@ jobs:
         run: |
           n="${{ steps.count.outputs.count }}"
           sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" README.md
+          # Bump the banner cache-buster so GitHub's Camo proxy refetches the org
+          # profile image (regenerated with the new count by .github/banner.yml)
+          # instead of serving a stale cached copy.
+          sed -i -E "s|(wickra-banner\.webp\?v=)[0-9]+|\1${n}|" 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"
@@ -134,12 +178,18 @@ jobs:
 
       - 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 ${{ steps.count.outputs.count }}"
-          git push origin "HEAD:${{ steps.ctx.outputs.head_ref }}"
+          git commit -m "chore: sync indicator count to ${COUNT}"
+          git push origin "HEAD:${HEAD_REF}"
 
       # ----- main / tag flow ------------------------------------------
       #
@@ -150,36 +200,314 @@ jobs:
       # wiki repo (separate repo, no main history pollution). README is
       # not touched on main any more.
 
-      - name: Update GitHub About description
+      - name: Update GitHub About (description + homepage)
         if: github.event_name != 'pull_request'
         env:
           GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
         run: |
           n="${{ steps.count.outputs.count }}"
+          # Canonical homepage — the docs site (P8.3). This is enforced on every
+          # run, so it must only point at docs.wickra.org once that domain is
+          # actually live (Cloudflare Pages, P8.1); merging this PR is therefore
+          # gated on the domain resolving, otherwise the About link would 404.
+          homepage="https://docs.wickra.org"
           desc="Streaming-first technical indicators with a Rust core and Python, Node.js, and WebAssembly bindings. ${n} indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement."
+          # Enforce the homepage unconditionally — it is a constant, so this both
+          # corrects the stale kingchenc URL and self-heals any future drift.
+          # Same Administration-write permission as --description (no extra scope).
+          gh repo edit --homepage "$homepage"
           current=$(gh repo view --json description -q .description)
           if [ "$current" = "$desc" ]; then
-            echo "About unchanged."
+            echo "About description unchanged; homepage enforced."
           else
             gh repo edit --description "$desc"
-            echo "About updated."
+            echo "About description + homepage updated."
           fi
 
-      - name: Sync Wiki
+      # Counter sync target moved from the retired GitHub wiki to the docs site
+      # repo (wickra-lib/wickra-docs). The count appears in index.md (hero),
+      # overview.md prose, and Indicators-Overview.md prose. Soft-skips like the
+      # org steps so a token/scope gap never fails the run. Uses its own clone
+      # dir (docs-count) so it cannot collide with the tag-only version step
+      # below, which clones the same repo into `docs`.
+      - name: Sync docs indicator count (wickra-docs)
         if: github.event_name != 'pull_request'
+        continue-on-error: true
         env:
           GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
         run: |
           n="${{ steps.count.outputs.count }}"
-          git clone "https://x-access-token:${GH_TOKEN}@github.com/${{ github.repository }}.wiki.git" wiki
-          cd wiki
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" Home.md FAQ.md Streaming-vs-Batch.md
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/wickra-docs.git" docs-count 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/wickra-docs — ABOUT_SYNC_TOKEN likely lacks write on that repo (findings P10.0a). Skipping docs count sync."
+            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
           if git diff --quiet; then
-            echo "Wiki unchanged."
+            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 Home.md FAQ.md Streaming-vs-Batch.md
+          git add index.md overview.md Indicators-Overview.md
           git commit -m "chore: sync indicator count to ${n}"
-          git push
+          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)."
+          else
+            echo "Docs indicator count synced to ${n}."
+          fi
+
+      # The GitHub wiki (wickra-lib/wickra.wiki) was collapsed to a single
+      # Home.md pointer page that sends visitors to docs.wickra.org, but that
+      # page still names the count ("… for all N indicators"), so keep it in
+      # sync here too. Mirrors the docs/webpage count steps: own clone dir
+      # (wiki-count) and the same soft-skip contract. Wiki write rides on the
+      # parent repo's permission, so the PAT needs write on wickra-lib/wickra;
+      # the wiki has no signing gate, so a plain wickra-bot commit is fine.
+      - name: Sync wiki pointer indicator count (wickra.wiki)
+        if: github.event_name != 'pull_request'
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          n="${{ steps.count.outputs.count }}"
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/wickra.wiki.git" wiki-count 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/wickra.wiki — ABOUT_SYNC_TOKEN likely lacks write on the wiki. Skipping wiki count sync."
+            exit 0
+          fi
+          cd wiki-count
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" Home.md
+          if git diff --quiet; then
+            echo "Wiki pointer indicator count unchanged."
+            exit 0
+          fi
+          git config user.name "wickra-bot"
+          git config user.email "wickra-bot@users.noreply.github.com"
+          git add Home.md
+          git commit -m "chore: sync indicator count to ${n}"
+          if ! git push 2>/dev/null; then
+            echo "::warning::push to wickra-lib/wickra.wiki failed — ABOUT_SYNC_TOKEN likely lacks write on the wiki."
+          else
+            echo "Wiki pointer indicator count synced to ${n}."
+          fi
+
+      # ----- org-profile sync (soft-skip until PAT scope lands) -------
+      #
+      # These two steps keep the org page (github.com/wickra-lib) in sync
+      # with the same count. They need ABOUT_SYNC_TOKEN scope the main-repo
+      # syncs do not: write on wickra-lib/.github, and admin:org for the org
+      # description PATCH. Both are written to soft-skip with a ::warning::
+      # (never fail the run) so this workflow stays green before the scope is
+      # granted — once it is, they start syncing with no further code change.
+
+      - name: Sync org profile README count
+        if: github.event_name != 'pull_request'
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          n="${{ steps.count.outputs.count }}"
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/.github.git" orgprofile 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/.github — ABOUT_SYNC_TOKEN likely lacks write on that repo (findings P10.0a). Skipping org profile sync."
+            exit 0
+          fi
+          cd orgprofile
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" profile/README.md
+          if git diff --quiet; then
+            echo "Org profile README count unchanged."
+            exit 0
+          fi
+          git config user.name "wickra-bot"
+          git config user.email "wickra-bot@users.noreply.github.com"
+          git add profile/README.md
+          git commit -m "chore: sync indicator count to ${n}"
+          if ! git push 2>/dev/null; then
+            echo "::warning::push to wickra-lib/.github failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."
+          else
+            echo "Org profile README synced to ${n}."
+          fi
+
+      - name: Sync org description
+        if: github.event_name != 'pull_request'
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          n="${{ steps.count.outputs.count }}"
+          org="wickra-lib"
+          # Reading the org description is public; the PATCH needs admin:org.
+          current=$(gh api "orgs/${org}" --jq '.description // ""' 2>/dev/null || true)
+          if [ -z "$current" ]; then
+            echo "::warning::could not read org description (network/PAT?). Skipping."
+            exit 0
+          fi
+          updated=$(printf '%s' "$current" | sed -E "s/[0-9]+ indicators/${n} indicators/")
+          if [ "$current" = "$updated" ]; then
+            echo "Org description count unchanged."
+            exit 0
+          fi
+          if gh api -X PATCH "orgs/${org}" -f description="$updated" >/dev/null 2>&1; then
+            echo "Org description synced to ${n}."
+          else
+            echo "::warning::org description PATCH failed — ABOUT_SYNC_TOKEN likely lacks admin:org (findings P10.0b)."
+          fi
+
+      # ----- docs version sync (tag-only, soft-skip until PAT scope lands) -----
+      #
+      # Surface 7: the docs site (wickra-lib/wickra-docs) carries the published
+      # version in the "Published versions" table (overview.md) and the Rust
+      # quickstart prose. Unlike the indicator count these change only on a
+      # release, so this step runs on v* tag pushes only and takes the version
+      # straight from the tag. It needs ABOUT_SYNC_TOKEN to have write on
+      # wickra-lib/wickra-docs (findings P10.0a). Until that scope is granted it
+      # soft-skips with a ::warning:: and never fails the run; once granted, every
+      # release self-heals the docs version with no code change (replaces the old
+      # manual P0.5 post-release wiki bump).
+      - name: Sync docs version (wickra-docs)
+        if: startsWith(github.ref, 'refs/tags/v')
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          version="${GITHUB_REF#refs/tags/v}"
+          if ! printf '%s' "$version" | grep -qE '^[0-9]+\.[0-9]+\.[0-9]+$'; then
+            echo "::warning::tag '${GITHUB_REF}' is not a plain vMAJOR.MINOR.PATCH release; skipping docs version sync."
+            exit 0
+          fi
+          # Clone into `docs-ver`, NOT `docs`: on a tag push this job checks out
+          # the wickra repo at the workspace root, which already contains a
+          # top-level `docs/` directory, so `git clone … docs` fails with
+          # "destination path 'docs' already exists" — silently, because of the
+          # 2>/dev/null below — and the version sync never runs (this is exactly
+          # why v0.4.0 did not bump the docs table). `docs-ver` mirrors the
+          # `docs-count` dir used by the count step above and collides with
+          # nothing in the repo.
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/wickra-docs.git" docs-ver 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/wickra-docs — ABOUT_SYNC_TOKEN likely lacks write on that repo (findings P10.0a). Skipping docs version sync."
+            exit 0
+          fi
+          cd docs-ver
+          # Published-versions table rows (crates.io / PyPI / npm): replace only the
+          # version number, leaving the trailing padding + pipe intact. The '.' in
+          # the quickstart pattern matches the literal backtick around the version
+          # without needing a backtick in this shell string. Historical "since
+          # X.Y.Z" references contain no such anchor and are never matched.
+          sed -i -E "s/^(\| (crates\.io|PyPI|npm) .*\| )[0-9]+\.[0-9]+\.[0-9]+/\1${version}/" overview.md
+          sed -i -E "s/(published crate is at version .)[0-9]+\.[0-9]+\.[0-9]+/\1${version}/" Quickstart-Rust.md
+          if git diff --quiet; then
+            echo "Docs version already at ${version}."
+            exit 0
+          fi
+          git config user.name "wickra-bot"
+          git config user.email "wickra-bot@users.noreply.github.com"
+          git add overview.md Quickstart-Rust.md
+          git commit -m "chore: sync published version to ${version}"
+          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)."
+          else
+            echo "Docs version synced to ${version}."
+          fi
+
+      # ----- webpage (marketing site) self-update (findings P12.1) ------------
+      #
+      # The marketing site (wickra-lib/webpage) carries the same indicator count
+      # and published version as the docs. Mirrors the docs steps above: the
+      # count syncs on push-to-main + tag, the version syncs on v* tags only.
+      # Distinct clone dirs (webpage-count / webpage-ver) avoid any collision on
+      # a tag run. Soft-skips with a ::warning:: if the token can't reach the
+      # repo, so the run never fails.
+      - name: Sync webpage indicator count (wickra-lib/webpage)
+        if: github.event_name != 'pull_request'
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          n="${{ steps.count.outputs.count }}"
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/webpage.git" webpage-count 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/webpage — ABOUT_SYNC_TOKEN likely lacks write on that repo (findings P10.0a). Skipping webpage count sync."
+            exit 0
+          fi
+          cd webpage-count
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${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
+          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)."
+          else
+            echo "Webpage indicator count synced to ${n}."
+          fi
+
+      - name: Sync webpage version (wickra-lib/webpage)
+        if: startsWith(github.ref, 'refs/tags/v')
+        continue-on-error: true
+        env:
+          GH_TOKEN: ${{ secrets.ABOUT_SYNC_TOKEN }}
+        run: |
+          version="${GITHUB_REF#refs/tags/v}"
+          if ! printf '%s' "$version" | grep -qE '^[0-9]+\.[0-9]+\.[0-9]+$'; then
+            echo "::warning::tag '${GITHUB_REF}' is not a plain vMAJOR.MINOR.PATCH release; skipping webpage version sync."
+            exit 0
+          fi
+          # The webpage pins wickra-wasm to the released version in package.json,
+          # and its Cloudflare Pages build runs `npm clean-install`. release.yml
+          # publishes wickra-wasm to npm in parallel on this same tag and finishes
+          # minutes later, so committing the bump immediately would point the site
+          # at a version npm cannot resolve yet (ETARGET) and break the build —
+          # exactly what happened on v0.4.0. Wait until wickra-wasm@$version is
+          # actually live on npm before committing; if it never appears (the wasm
+          # publish failed), skip rather than push a build-breaking commit.
+          echo "Waiting for wickra-wasm@${version} on npm before bumping the webpage..."
+          attempts=0
+          until npm view "wickra-wasm@${version}" version >/dev/null 2>&1; do
+            attempts=$((attempts + 1))
+            if [ "$attempts" -ge 30 ]; then
+              echo "::warning::wickra-wasm@${version} not on npm after ~15 min; skipping webpage version sync to avoid a broken Cloudflare build."
+              exit 0
+            fi
+            echo "  not on npm yet (attempt ${attempts}/30); waiting 30s..."
+            sleep 30
+          done
+          echo "wickra-wasm@${version} is live on npm; proceeding with the webpage version bump."
+          if ! git clone "https://x-access-token:${GH_TOKEN}@github.com/wickra-lib/webpage.git" webpage-ver 2>/dev/null; then
+            echo "::warning::cannot clone wickra-lib/webpage — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a). Skipping webpage version sync."
+            exit 0
+          fi
+          cd webpage-ver
+          # api/*.md "Latest" lines, the nav version label, and the wickra-wasm
+          # dep pin. The '.' anchors match the backtick / quote / caret without a
+          # literal in this shell string; historical "Since X.Y.Z" prose has no
+          # such anchor and is never matched.
+          sed -i -E "s/(Latest:\*\* \[.wickra(-wasm)? )[0-9]+\.[0-9]+\.[0-9]+/\1${version}/" api/*.md
+          sed -i -E "s/(text: .v)[0-9]+\.[0-9]+\.[0-9]+/\1${version}/" .vitepress/config.ts
+          sed -i -E "s/(.wickra-wasm.: .\^)[0-9]+\.[0-9]+\.[0-9]+/\1${version}/" package.json
+          # Keep package-lock.json in sync with the package.json bump. The site's
+          # Cloudflare build runs `npm clean-install` (npm ci), which hard-fails
+          # with EUSAGE if the lockfile still pins the previous wickra-wasm —
+          # editing package.json alone is not enough. The npm-wait above already
+          # proved wickra-wasm@$version is resolvable, so --package-lock-only
+          # regenerates the lock (version + resolved + integrity) without fetching
+          # node_modules. Guard it: if the regen fails, skip the whole commit so we
+          # never push a package.json/lock mismatch that would break the build.
+          if ! npm install --package-lock-only --no-audit --no-fund; then
+            echo "::warning::could not regenerate package-lock.json for wickra-wasm@${version}; skipping webpage version sync to avoid a lockfile-drift build break."
+            exit 0
+          fi
+          if git diff --quiet; then
+            echo "Webpage version already at ${version}."
+            exit 0
+          fi
+          git config user.name "wickra-bot"
+          git config user.email "wickra-bot@users.noreply.github.com"
+          git add api/*.md .vitepress/config.ts package.json package-lock.json
+          git commit -m "chore: sync published version to ${version}"
+          if ! git push 2>/dev/null; then
+            echo "::warning::push to wickra-lib/webpage failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."
+          else
+            echo "Webpage version synced to ${version}."
+          fi

.github/workflows/sync-metadata.yml

@@ -14,8 +14,8 @@ jobs:
     name: metadata audit
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v6
-      - uses: actions/setup-python@v5
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
         with:
           python-version: "3.12"
       - name: Audit repo-metadata.toml drift

.gitignore

@@ -44,10 +44,14 @@ tarpaulin-report.html
 # Node binding artifacts
 **/node_modules/
 bindings/node/*.node
-bindings/node/index.d.ts
 bindings/node/npm-debug.log*
-# package-lock.json is committed (under bindings/node/) so contributors
-# get reproducible npm installs. Top-level lockfiles still aren't expected.
+# index.js + index.d.ts are generated by `napi build` but committed (a matched
+# pair) so consumers and the repo get TypeScript types; CONTRIBUTING requires
+# regenerating both when a binding's public API changes.
+# package-lock.json is committed for the tracked Node packages — bindings/node/
+# and examples/node/ — so contributors get reproducible npm installs. There is
+# no top-level npm package, and the ghost-ignored site/ keeps its lockfile local.
+# See CONTRIBUTING.md "Lockfile policy" for the full per-component breakdown.
 
 # WASM build output
 bindings/wasm/pkg/

CHANGELOG.md

@@ -7,6 +7,154 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [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
+- **Cross-asset pairwise indicators.** A new two-series family of
+  `Indicator<Input = (f64, f64)>` implementations that relate two distinct
+  assets rather than a single OHLCV stream. Each is exposed in Rust, Python,
+  Node, and WASM:
+  - **Pairwise Beta** (`PairwiseBeta`) — rolling OLS slope of one asset's
+    **log-returns** on another's. Unlike `Beta`, which regresses the raw inputs
+    it is fed, `PairwiseBeta` differences consecutive prices into log-returns
+    internally — the conventional way to measure cross-asset beta, where a beta
+    on price levels would be dominated by the shared trend.
+  - **Pair Spread Z-Score** (`PairSpreadZScore`) — the standardised log-spread
+    `ln(a) − β·ln(b)` of a pair, where `β` is a rolling-OLS hedge ratio and the
+    spread is z-scored over its own look-back. The canonical mean-reversion /
+    statistical-arbitrage entry signal, with independent `beta_period` and
+    `z_period` windows.
+  - **Lead–Lag Cross-Correlation** (`LeadLagCrossCorrelation`) — the integer
+    offset `k ∈ [−max_lag, max_lag]` that maximises `|corr(a[t], b[t+k])|`,
+    answering which of two assets leads the other and by how many bars. Emits
+    `{ lag, correlation }`; a positive lag means `a` leads `b`.
+  - **Cointegration** (`Cointegration`) — the Engle–Granger two-step screen for
+    pairs trading: a rolling OLS hedge ratio `β`, the spread (residual)
+    `a − (α + β·b)`, and an augmented Dickey–Fuller `t`-statistic on the spread
+    (configurable `adf_lags`). A strongly negative statistic flags a
+    mean-reverting, tradeable spread. Emits `{ hedge_ratio, spread, adf_stat }`.
+  - **Relative Strength A-vs-B** (`RelativeStrengthAB`) — the comparative
+    relative strength of two assets: the ratio line `a / b` together with its
+    moving average and its RSI, the classic asset-vs-asset / asset-vs-index
+    rotation screen. Emits `{ ratio, ratio_ma, ratio_rsi }`.
+
+## [0.4.0] - 2026-06-01
+
+### Added
+- **Build-provenance attestations for release artifacts.** The release workflow
+  now emits signed SLSA build-provenance attestations for the published crates
+  and Python wheels/sdist (`actions/attest-build-provenance`); npm packages
+  carry inline Sigstore provenance from `npm publish --provenance`. Every
+  published artifact is cryptographically traceable to this repository's release
+  workflow run.
+
+### Security
+- **CodeQL static analysis and OpenSSF Scorecard run in CI.** CodeQL (Rust,
+  Python, JavaScript) and the OpenSSF Scorecard workflow now run on every push;
+  results appear under Security → Code scanning and a public Scorecard badge is
+  shown in the README.
+- **CI workflows hardened against script injection.** Untrusted event contexts
+  (PR branch names, `workflow_dispatch` inputs) are passed through the step
+  environment instead of being interpolated directly into shell commands.
+
+### Changed
+- **Node binding: invalid indicator periods now throw instead of being silently
+  clamped.** The scalar-indicator constructors previously clamped `period = 0`
+  to `1`; every Node constructor now propagates the core's validation error
+  (e.g. `period must be greater than zero`), matching the Python and WASM
+  bindings and the Rust core. Constructing with a valid period is unaffected.
+- **Binding package READMEs are now per-ecosystem.** The Python, Node.js, and
+  WebAssembly READMEs were byte-identical 314-line copies of the workspace
+  README and had drifted out of sync (stale indicator count, Python snippets
+  shown on the Node and WASM package pages). Each is now a focused landing page
+  with the correct install command, a language-correct quick-start snippet, and
+  links to the canonical documentation — removing the manual three-way sync
+  burden. No code or API changes.
+- **CONTRIBUTING now states the correct MSRV (1.86 workspace / 1.88
+  `bindings/node`)** and documents that these are the dependency-forced floors,
+  kept minimal on purpose. The previous text claimed 1.75 / 1.77, which the
+  `msrv` CI job has enforced against since the criterion and napi-build bumps.
+
 ## [0.3.1] - 2026-05-30
 
 ### Fixed
@@ -832,7 +980,11 @@ 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/v0.3.1...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.4.3...HEAD
+[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
 [0.3.0]: https://github.com/wickra-lib/wickra/compare/v0.2.7...v0.3.0
 [0.2.7]: https://github.com/wickra-lib/wickra/compare/v0.2.6...v0.2.7

CITATION.cff

@@ -6,7 +6,7 @@ message: >-
 type: software
 authors:
   - alias: kingchenc
-    email: wickra.lib@gmail.com
+    email: support@wickra.org
 repository-code: "https://github.com/wickra-lib/wickra"
 url: "https://wickra.org"
 abstract: >-

CODE_OF_CONDUCT.md

@@ -33,7 +33,7 @@ project in public spaces.
 ## Enforcement
 
 Instances of unacceptable behaviour may be reported to the project maintainer
-at **wickra.lib@gmail.com**. All reports will be reviewed and investigated
+at **support@wickra.org**. All reports will be reviewed and investigated
 promptly and fairly, and the maintainer will respect the privacy and security
 of the reporter.
 

CONTRIBUTING.md

@@ -35,8 +35,13 @@ cargo test --workspace
 cargo test -p wickra-data --features live-binance
 ```
 
-The minimum supported Rust version is **1.75** for the workspace crates and
-**1.77** for `bindings/node`; the `msrv` CI job enforces both.
+The minimum supported Rust version is **1.86** for the workspace crates and
+**1.88** for `bindings/node`; the `msrv` CI job enforces both. These floors are
+not chosen freely — they are the lowest versions our dependencies allow
+(criterion 0.8.2, the bench dev-dependency, requires 1.86; napi-build 2.3.2
+requires 1.88). We keep the MSRV at that dependency-forced floor on purpose so
+the library builds for the widest possible audience; please don't raise it
+without a dependency that actually requires it.
 
 ### Python
 
@@ -63,6 +68,29 @@ wasm-pack build bindings/wasm --target web --release --features panic-hook
 wasm-pack test --node bindings/wasm
 ```
 
+## Lockfile policy
+
+| Component | Lockfile | Tracked? | Why |
+| --- | --- | --- | --- |
+| 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) | 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. |
+
+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
@@ -76,9 +104,9 @@ wasm-pack test --node bindings/wasm
 - **Bindings.** A change to a public indicator API must be mirrored across the
   Python, Node, and WASM bindings, including their type stubs / `.d.ts`.
 - **Docs.** Update the relevant page on the
-  [project Wiki](https://github.com/wickra-lib/wickra/wiki) and the
-  `README.md` when behaviour or the public API changes. The Wiki lives in
-  a separate git repository: `https://github.com/wickra-lib/wickra.wiki.git`.
+  [documentation site](https://docs.wickra.org) and the
+  `README.md` when behaviour or the public API changes. The docs live in
+  a separate git repository: `https://github.com/wickra-lib/wickra-docs`.
 - **Changelog.** Add an entry under `## [Unreleased]` in `CHANGELOG.md`.
 
 ## Commit and pull-request workflow

Cargo.lock

@@ -1867,7 +1867,7 @@ dependencies = [
 
 [[package]]
 name = "wickra"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "approx",
  "criterion",
@@ -1878,7 +1878,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-core"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "approx",
  "proptest",
@@ -1888,7 +1888,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-data"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "approx",
  "csv",
@@ -1915,7 +1915,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-node"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "napi",
  "napi-build",
@@ -1925,7 +1925,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-python"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "numpy",
  "pyo3",
@@ -1934,7 +1934,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-wasm"
-version = "0.3.1"
+version = "0.4.3"
 dependencies = [
  "console_error_panic_hook",
  "js-sys",

Cargo.toml

@@ -12,11 +12,11 @@ members = [
 exclude = ["fuzz"]
 
 [workspace.package]
-version = "0.3.1"
-authors = ["kingchenc <wickra.lib@gmail.com>"]
+version = "0.4.3"
+authors = ["kingchenc <support@wickra.org>"]
 edition = "2021"
 rust-version = "1.86"
-license = "PolyForm-Noncommercial-1.0.0"
+license-file = "LICENSE"
 repository = "https://github.com/wickra-lib/wickra"
 homepage = "https://github.com/wickra-lib/wickra"
 readme = "README.md"
@@ -24,7 +24,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
 categories = ["finance", "mathematics", "science"]
 
 [workspace.dependencies]
-wickra-core = { path = "crates/wickra-core", version = "0.3.1" }
+wickra-core = { path = "crates/wickra-core", version = "0.4.3" }
 
 thiserror = "2"
 rayon = "1.10"

LICENSE

@@ -131,6 +131,31 @@ software under these terms.
 **Use** means anything you do with the software requiring one
 of your licenses.
 
+## Additional Permissions Granted by the Licensor
+
+These additional permissions supplement the PolyForm Noncommercial
+License 1.0.0 above. They only broaden, and never narrow, the
+licenses granted to you. The text of the PolyForm Noncommercial
+License 1.0.0 above is unmodified.
+
+Use by a natural person, acting for their own personal account and
+not on behalf of any third party, is use for a permitted purpose.
+This includes operating an automated trading bot or trading strategy
+on that person's own capital, whether or not it earns that person
+money.
+
+For the avoidance of doubt, the licenses above already let you use,
+fork, modify, and redistribute the software, and file issues and
+contribute changes, for any permitted purpose. Personal projects,
+research, education, nonprofit organizations, government use, and
+hobby trading bots are permitted purposes.
+
+Any other commercial use — in particular the commercial sale of the
+software itself, or the commercial sale of services built around it —
+requires a separate commercial license from the licensor. If you want
+to use Wickra commercially, get in touch about a license at
+<https://github.com/wickra-lib/wickra>.
+
 ---
 
 Required Notice: Copyright 2026 kingchenc (https://github.com/wickra-lib/wickra)

README.md

@@ -1,11 +1,18 @@
-# Wickra
+<p align="center">
+  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=232" 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)
+[![CodeQL](https://github.com/wickra-lib/wickra/actions/workflows/codeql.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/codeql.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![GitHub release](https://img.shields.io/github/v/release/wickra-lib/wickra?logo=github&color=green)](https://github.com/wickra-lib/wickra/releases/latest)
 [![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)
+[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/wickra-lib/wickra/badge)](https://scorecard.dev/viewer/?uri=github.com/wickra-lib/wickra)
+[![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)
 
 **Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
 
@@ -31,6 +38,25 @@ for price in live_feed:
         print("overbought")
 ```
 
+## Documentation
+
+Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
+
+- **Quickstarts** — [Rust](https://docs.wickra.org/Quickstart-Rust),
+  [Python](https://docs.wickra.org/Quickstart-Python),
+  [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 232 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),
+  [indicator chaining](https://docs.wickra.org/Indicator-Chaining), the
+  [data layer](https://docs.wickra.org/Data-Layer).
+- **Guides** — [Cookbook](https://docs.wickra.org/Cookbook),
+  [TA-Lib migration](https://docs.wickra.org/TA-Lib-Migration),
+  [FAQ](https://docs.wickra.org/FAQ).
+
 ## Why Wickra exists
 
 The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
@@ -109,9 +135,10 @@ python -m benchmarks.compare_libraries
 
 ## Indicators
 
-214 streaming-first indicators across sixteen families. Every one passes the
+232 streaming-first indicators across seventeen families. Every one passes the
 `batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
+semantics tests. Each has a per-indicator deep dive (formula, parameters,
+warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
 
 | Family | Indicators |
 |--------|-----------|
@@ -123,15 +150,22 @@ semantics tests.
 | 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 |
 | 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, Spearman Correlation |
+| 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 |
 | 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 |
+| 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 |
 | Market Profile       | Value Area (POC / VAH / VAL), Initial Balance, Opening Range |
 | 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) |
 
+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.
 
@@ -203,7 +237,7 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 214 indicators
+│   ├── wickra-core/         core engine + all 232 indicators
 │   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
 │   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
 ├── bindings/

SECURITY.md

@@ -18,7 +18,7 @@ Report it privately through one of:
 
 - GitHub's [private vulnerability reporting](https://github.com/wickra-lib/wickra/security/advisories/new)
   ("Report a vulnerability" under the repository's *Security* tab), or
-- email to **wickra.lib@gmail.com** with a subject line starting with
+- email to **support@wickra.org** with a subject line starting with
   `[wickra security]`.
 
 Please include:

bindings/node/Cargo.toml

@@ -9,7 +9,7 @@ edition.workspace = true
 # also emits `cargo::` directives that require >= 1.77 — that older floor is
 # subsumed by the 1.88 requirement now.
 rust-version = "1.88"
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

bindings/node/README.md

@@ -1,314 +1,73 @@
-# Wickra
+# Wickra — Node.js
 
 [![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)
-[![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: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators for Node.js. `npm install wickra` —
+prebuilt native binary, no system dependencies.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the Node.js binding (napi-rs);
+it exposes 200+ streaming-first indicators across sixteen families.
 
-```python
-import numpy as np
-import wickra as ta
-
-# Batch: classic TA-Lib-style usage
-prices = np.linspace(100, 200, 1000)
-rsi = ta.RSI(14)
-values = rsi.batch(prices)              # numpy array, NaN during warmup
-
-# Streaming: same indicator, fed tick by tick
-rsi = ta.RSI(14)
-for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
-    if value is not None and value > 70:
-        print("overbought")
-```
-
-## 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:
-
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★ 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    |
-
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
-
-## Benchmark: how much faster is "streaming-first"?
-
-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.
-
-- **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.
-
-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.
-
-### Batch — single full pass over a 20 000-bar series
-
-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.
-
-| Indicator           | **★ 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)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-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 | **★ Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> 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.
-
-Run the suite yourself:
+## Install
 
 ```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
+npm install wickra
 ```
 
-## Indicators
+The native addon ships as a prebuilt binary per platform (Linux, macOS,
+Windows — x64 and arm64), selected automatically through optional
+dependencies. There is nothing to compile.
 
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
+## Quick start
 
-| 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, Detrended StdDev |
-| 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 |
-| 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, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, 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 |
-| 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 |
-| 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) |
+```js
+const wickra = require('wickra');
 
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
+// Batch: run an indicator over a whole array.
+const prices = Array.from({ length: 1000 }, (_, i) => 100 + i * 0.1);
+const values = new wickra.RSI(14).batch(prices); // null during warmup
 
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
+// Streaming: the same indicator, fed tick by tick in O(1).
+const rsi = new wickra.RSI(14);
+for (const price of liveFeed) {
+  const value = rsi.update(price); // no recomputation over history
+  if (value !== null && value > 70) {
+    console.log('overbought');
+  }
 }
 ```
 
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
+`batch(prices)` and feeding the same prices through `update()` produce
+identical values — the equivalence is enforced by the test suite.
 
-## Project layout
+## Documentation
 
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .github/workflows/       CI and release pipelines
-```
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and documentation site:
 
-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.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable examples:** [`examples/node/`](https://github.com/wickra-lib/wickra/tree/main/examples/node)
 
-## Building everything from source
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+## Disclaimer
 
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-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.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+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).

bindings/node/__tests__/completeness.test.js

@@ -0,0 +1,70 @@
+// Completeness contract for the Wickra Node bindings: every exported indicator
+// class must expose the full streaming + batch + lifecycle interface. This
+// catches a new indicator being wired into the binding without the standard
+// methods (or an export silently disappearing) without needing a hand-written
+// test per indicator.
+
+const test = require('node:test');
+const assert = require('node:assert/strict');
+const wickra = require('..');
+
+// 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.
+function indicatorClasses() {
+  return Object.keys(wickra).filter((name) => {
+    const value = wickra[name];
+    return (
+      typeof value === 'function' &&
+      value.prototype &&
+      typeof value.prototype.update === 'function'
+    );
+  });
+}
+
+test('the binding exports the full indicator catalogue', () => {
+  const names = indicatorClasses();
+  // The published catalogue is 214 indicators. Guard against a regression that
+  // silently drops exported classes (e.g. a stale or partial native build).
+  assert.ok(
+    names.length >= 200,
+    `expected at least 200 indicator classes, got ${names.length}`,
+  );
+});
+
+test('every exported indicator exposes update / batch / reset / isReady / warmupPeriod', () => {
+  const required = ['update', 'batch', 'reset', 'isReady', 'warmupPeriod'];
+  const missing = [];
+  for (const name of indicatorClasses()) {
+    const proto = wickra[name].prototype;
+    for (const method of required) {
+      if (typeof proto[method] !== 'function') {
+        missing.push(`${name}.${method}`);
+      }
+    }
+  }
+  assert.deepEqual(
+    missing,
+    [],
+    `indicator classes missing required methods: ${missing.join(', ')}`,
+  );
+});
+
+test('a freshly constructed indicator reports not-ready with a positive warmup', () => {
+  // Every indicator that takes no constructor arguments must still satisfy the
+  // pre-warmup contract. (Indicators with required parameters are exercised by
+  // the dedicated suites; here we cover the zero-arg ones generically.)
+  let checked = 0;
+  for (const name of indicatorClasses()) {
+    let instance;
+    try {
+      instance = new wickra[name]();
+    } catch {
+      continue; // needs constructor arguments — covered elsewhere
+    }
+    assert.equal(instance.isReady(), false, `${name} should start un-ready`);
+    assert.ok(instance.warmupPeriod() >= 1, `${name} warmup must be >= 1`);
+    checked += 1;
+  }
+  assert.ok(checked > 0, 'expected at least one zero-arg indicator to check');
+});

bindings/node/__tests__/indicators.test.js

@@ -461,6 +461,8 @@ test('OpeningRange(2) breakout distance is signed close minus midpoint', () => {
 const pairFactories = {
   PearsonCorrelation: () => new wickra.PearsonCorrelation(14),
   Beta: () => new wickra.Beta(14),
+  PairwiseBeta: () => new wickra.PairwiseBeta(14),
+  PairSpreadZScore: () => new wickra.PairSpreadZScore(14, 14),
   SpearmanCorrelation: () => new wickra.SpearmanCorrelation(14),
 };
 
@@ -492,6 +494,85 @@ test('Beta perfect two-to-one', () => {
   assert.ok(Math.abs(out[out.length - 1] - 2) < 1e-9);
 });
 
+test('PairwiseBeta squared price is two', () => {
+  // b needs varying returns; a = b² ⇒ a's log-returns are exactly 2× b's.
+  const bench = Array.from({ length: 20 }, (_, i) => 100 + 10 * Math.sin(i * 0.5));
+  const asset = bench.map((v) => v * v);
+  const out = new wickra.PairwiseBeta(5).batch(asset, bench);
+  assert.ok(Math.abs(out[out.length - 1] - 2) < 1e-9);
+});
+
+test('PairSpreadZScore flat benchmark is sign of last move', () => {
+  // Flat b ⇒ hedge ratio 0 ⇒ spread = ln(a); z_period = 2 ⇒ z = sign of move.
+  const a = [100, 100, 110, 105, 130];
+  const b = [100, 100, 100, 100, 100];
+  const out = new wickra.PairSpreadZScore(2, 2).batch(a, b);
+  assert.ok(Math.abs(out[out.length - 1] - 1) < 1e-9);
+  assert.ok(Math.abs(out[out.length - 2] + 1) < 1e-9);
+});
+
+const llSignal = (t) =>
+  Math.sin(t * 0.4) + 0.4 * Math.sin(t * 1.1) + 0.2 * Math.cos(t * 0.27);
+
+test('LeadLagCrossCorrelation detects positive lead (object output)', () => {
+  const ll = new wickra.LeadLagCrossCorrelation(12, 5);
+  let last = null;
+  // b is a delayed by 3 ⇒ a leads b ⇒ lag = +3.
+  for (let t = 0; t < 60; t++) last = ll.update(llSignal(t), llSignal(t - 3));
+  assert.equal(last.lag, 3);
+  assert.ok(last.correlation > 0.99);
+});
+
+test('LeadLagCrossCorrelation batch is flat 2*n with last row matching', () => {
+  const n = 60;
+  const a = Array.from({ length: n }, (_, t) => llSignal(t));
+  const b = Array.from({ length: n }, (_, t) => llSignal(t - 3));
+  const out = new wickra.LeadLagCrossCorrelation(12, 5).batch(a, b);
+  assert.equal(out.length, 2 * n);
+  assert.equal(out[2 * (n - 1)], 3);
+  assert.ok(out[2 * (n - 1) + 1] > 0.99);
+});
+
+test('Cointegration detects mean-reverting pair (object output)', () => {
+  const n = 80;
+  const b = Array.from({ length: n }, (_, t) => 50 + 0.5 * t);
+  const a = b.map((v, t) => 2 * v + 1 + 0.5 * Math.sin(t * 0.6));
+  const co = new wickra.Cointegration(40, 1);
+  let last = null;
+  for (let i = 0; i < n; i++) last = co.update(a[i], b[i]);
+  assert.ok(Math.abs(last.hedgeRatio - 2) < 0.1);
+  assert.ok(last.adfStat < -2);
+});
+
+test('Cointegration batch is flat 3*n with last row matching', () => {
+  const n = 80;
+  const b = Array.from({ length: n }, (_, t) => 50 + 0.5 * t);
+  const a = b.map((v, t) => 2 * v + 1 + 0.5 * Math.sin(t * 0.6));
+  const out = new wickra.Cointegration(40, 1).batch(a, b);
+  assert.equal(out.length, 3 * n);
+  assert.ok(Math.abs(out[3 * (n - 1)] - 2) < 0.1);
+  assert.ok(out[3 * (n - 1) + 2] < -2);
+});
+
+test('RelativeStrengthAB constant ratio is flat (object output)', () => {
+  const rs = new wickra.RelativeStrengthAB(5, 5);
+  let last = null;
+  for (let i = 0; i < 30; i++) last = rs.update(200, 100); // ratio is a constant 2
+  assert.ok(Math.abs(last.ratio - 2) < 1e-12);
+  assert.ok(Math.abs(last.ratioMa - 2) < 1e-12);
+  assert.ok(Math.abs(last.ratioRsi - 50) < 1e-9);
+});
+
+test('RelativeStrengthAB batch is flat 3*n with last row matching', () => {
+  const n = 30;
+  const a = Array.from({ length: n }, () => 200);
+  const b = Array.from({ length: n }, () => 100);
+  const out = new wickra.RelativeStrengthAB(5, 5).batch(a, b);
+  assert.equal(out.length, 3 * n);
+  assert.ok(Math.abs(out[3 * (n - 1)] - 2) < 1e-12);
+  assert.ok(Math.abs(out[3 * (n - 1) + 2] - 50) < 1e-9);
+});
+
 test('SpearmanCorrelation monotone non-linear is 1', () => {
   const x = Array.from({ length: 10 }, (_, i) => i + 1);
   const y = x.map((v) => v ** 3);
@@ -815,3 +896,201 @@ 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('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));
+});

bindings/node/__tests__/input_validation.test.js

@@ -0,0 +1,84 @@
+// Input-validation tests for the Wickra Node bindings: malformed constructor
+// parameters and mismatched batch inputs must raise a JS Error (the napi
+// wrapper turns the Rust `Err` into a thrown Error), not crash the process.
+// Node counterpart of bindings/python/tests/test_input_validation.py.
+
+const test = require('node:test');
+const assert = require('node:assert/strict');
+const wickra = require('..');
+
+// --- Constructors reject invalid periods / parameters ---
+
+test('ATR rejects a zero period at construction', () => {
+  // ATR validates its period (it drives the Wilder-smoothing length). The
+  // plain moving averages (SMA/EMA/RSI/StdDev) instead treat period 0 as a
+  // warmup-1 pass-through rather than an error, so they are not asserted here.
+  assert.throws(() => new wickra.ATR(0), /.*/);
+});
+
+test('MACD rejects zero and non-increasing fast/slow periods', () => {
+  assert.throws(() => new wickra.MACD(0, 0, 0), /.*/);
+  // fast must be strictly less than slow.
+  assert.throws(() => new wickra.MACD(26, 12, 9), /.*/);
+});
+
+test('BollingerBands rejects a negative standard-deviation multiplier', () => {
+  assert.throws(() => new wickra.BollingerBands(20, -1), /.*/);
+});
+
+test('PSAR rejects a step greater than its maximum', () => {
+  assert.throws(() => new wickra.PSAR(0.3, 0.02, 0.2), /.*/);
+});
+
+test('ValueArea rejects zero periods and out-of-range value-area percentages', () => {
+  assert.throws(() => new wickra.ValueArea(0, 50, 0.7), /.*/);
+  assert.throws(() => new wickra.ValueArea(20, 0, 0.7), /.*/);
+  assert.throws(() => new wickra.ValueArea(20, 50, 0.0), /.*/);
+  assert.throws(() => new wickra.ValueArea(20, 50, 1.5), /.*/);
+});
+
+test('InitialBalance and OpeningRange reject a zero period', () => {
+  assert.throws(() => new wickra.InitialBalance(0), /.*/);
+  assert.throws(() => new wickra.OpeningRange(0), /.*/);
+});
+
+test('Ichimoku rejects zero and non-increasing periods', () => {
+  assert.throws(() => new wickra.Ichimoku(0, 26, 52, 26), /.*/);
+  assert.throws(() => new wickra.Ichimoku(9, 26, 52, 0), /.*/);
+  // Periods must satisfy tenkan < kijun < senkouB.
+  assert.throws(() => new wickra.Ichimoku(26, 9, 52, 26), /.*/);
+  assert.throws(() => new wickra.Ichimoku(9, 52, 52, 26), /.*/);
+});
+
+test('Family 10 (Ehlers / cycle) indicators reject invalid parameters', () => {
+  // InverseFisherTransform needs a non-zero scaling factor.
+  assert.throws(() => new wickra.InverseFisherTransform(0.0), /.*/);
+  // DecyclerOscillator / RoofingFilter need the short cutoff below the long one.
+  assert.throws(() => new wickra.DecyclerOscillator(30, 10), /.*/);
+  assert.throws(() => new wickra.RoofingFilter(48, 10), /.*/);
+  // MAMA needs fast limit > slow limit.
+  assert.throws(() => new wickra.MAMA(0.05, 0.5), /.*/);
+  // EmpiricalModeDecomposition needs a positive fraction.
+  assert.throws(() => new wickra.EmpiricalModeDecomposition(20, 0.0), /.*/);
+  // NOTE: SuperSmoother(0) / FisherTransform(0) are NOT asserted: the Node
+  // binding treats their period 0 as a warmup-1 pass-through (same as the
+  // simple moving averages) rather than an error.
+});
+
+// --- Batch methods reject mismatched input lengths ---
+
+test('candle batch methods reject unequal-length columns', () => {
+  const high = [10, 11, 12];
+  const low = [9, 10]; // one short
+  const close = [9.5, 10.5, 11.5];
+  assert.throws(() => new wickra.ATR(14).batch(high, low, close), /.*/);
+  assert.throws(() => new wickra.WilliamsR(14).batch(high, low, close), /.*/);
+  assert.throws(() => new wickra.Aroon(14).batch(high, low), /.*/);
+});
+
+test('ValueArea batch rejects unequal-length columns', () => {
+  const high = [1, 2, 3];
+  const low = [0.5, 1.5]; // short
+  const volume = [10, 10, 10];
+  assert.throws(() => new wickra.ValueArea(2, 10, 0.7).batch(high, low, volume), /.*/);
+});

bindings/node/__tests__/smoke.test.js

@@ -73,10 +73,10 @@ test('ATR batch shape', () => {
   }
 });
 
-test('zero period is clamped to a valid window', () => {
-  // Constructors cannot throw from JS (napi-rs 2.16 limitation), so they
-  // clamp pathological values like period=0 to the smallest valid window.
-  const sma = new wickra.SMA(0);
-  assert.equal(sma.warmupPeriod(), 1);
-  assert.equal(sma.update(42), 42);
+test('zero period is rejected at construction', () => {
+  // The core rejects period 0 (Error::PeriodZero); the Node binding propagates
+  // it as a thrown JS error, consistent with the Python and WASM bindings.
+  assert.throws(() => new wickra.SMA(0), /period must be greater than zero/);
+  // A valid period still constructs and runs.
+  assert.equal(new wickra.SMA(1).update(42), 42);
 });

bindings/node/benchmarks/throughput.js

@@ -0,0 +1,99 @@
+// Throughput benchmark for the Wickra Node bindings.
+//
+// Measures how many indicator updates per second the native binding sustains,
+// both per-tick (streaming `update`) and bulk (`batch`), over a synthetic
+// OHLCV series. It is the Node counterpart of the Rust criterion benches and
+// the Python `benchmarks/compare_libraries.py`; it benchmarks Wickra's own
+// O(1) streaming engine (there is no install-free TA library on npm with a
+// comparable surface to compare against), so the headline number is raw
+// throughput, not a cross-library ratio.
+//
+// Run after building the binding:
+//
+//   cd bindings/node && npm install && npx napi build --platform --release
+//   node benchmarks/throughput.js               # 200k bars (default)
+//   node benchmarks/throughput.js --bars 1000000
+
+const wickra = require('..');
+
+function parseBars() {
+  const idx = process.argv.indexOf('--bars');
+  if (idx !== -1 && process.argv[idx + 1]) {
+    const n = Number(process.argv[idx + 1]);
+    if (Number.isFinite(n) && n >= 1000) return Math.floor(n);
+    console.error('--bars must be a number >= 1000');
+    process.exit(1);
+  }
+  return 200_000;
+}
+
+const BARS = parseBars();
+
+// Deterministic synthetic OHLCV (no RNG, so runs are comparable).
+const close = new Array(BARS);
+const high = new Array(BARS);
+const low = new Array(BARS);
+const volume = new Array(BARS);
+for (let i = 0; i < BARS; i++) {
+  const mid = 100 + Math.sin(i * 0.001) * 20 + i * 1e-4;
+  close[i] = mid + Math.sin(i * 0.05) * 2;
+  high[i] = Math.max(close[i], mid) + 1.5;
+  low[i] = Math.min(close[i], mid) - 1.5;
+  volume[i] = 1000 + (i % 97) * 13;
+}
+
+// Median elapsed-ns over a few repetitions, after one warmup pass.
+function timeNs(fn, reps = 3) {
+  fn(); // warmup (JIT + cache)
+  const samples = [];
+  for (let r = 0; r < reps; r++) {
+    const t0 = process.hrtime.bigint();
+    fn();
+    samples.push(Number(process.hrtime.bigint() - t0));
+  }
+  samples.sort((a, b) => a - b);
+  return samples[Math.floor(samples.length / 2)];
+}
+
+function mupsFromNs(ns) {
+  return (BARS / (ns / 1e9)) / 1e6; // million updates per second
+}
+
+// Each indicator: a streaming step and a batch call over the full series.
+const indicators = [
+  { name: 'SMA(20)', make: () => new wickra.SMA(20), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'EMA(20)', make: () => new wickra.EMA(20), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'RSI(14)', make: () => new wickra.RSI(14), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'StdDev(20)', make: () => new wickra.StdDev(20), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'MACD(12,26,9)', make: () => new wickra.MACD(12, 26, 9), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'BollingerBands(20,2)', make: () => new wickra.BollingerBands(20, 2), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'KAMA(10,2,30)', make: () => new wickra.KAMA(10, 2, 30), step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  { name: 'ATR(14)', make: () => new wickra.ATR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  { name: 'ADX(14)', make: () => new wickra.ADX(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  { name: 'Stochastic(14,3)', make: () => new wickra.Stochastic(14, 3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  { name: 'SuperTrend(10,3)', make: () => new wickra.SuperTrend(10, 3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  { name: 'OBV', make: () => new wickra.OBV(), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
+];
+
+console.log(`Wickra Node throughput — ${BARS.toLocaleString('en-US')} bars (median of 3 runs)\n`);
+console.log(`${'Indicator'.padEnd(22)}${'streaming (Mupd/s)'.padStart(20)}${'batch (Mupd/s)'.padStart(18)}`);
+console.log('-'.repeat(60));
+
+for (const ind of indicators) {
+  const streamNs = timeNs(() => {
+    const inst = ind.make();
+    for (let i = 0; i < BARS; i++) ind.step(inst, i);
+  });
+  const batchNs = timeNs(() => {
+    ind.batch(ind.make());
+  });
+  console.log(
+    `${ind.name.padEnd(22)}${mupsFromNs(streamNs).toFixed(1).padStart(20)}${mupsFromNs(batchNs).toFixed(1).padStart(18)}`,
+  );
+}
+
+console.log(
+  '\nMupd/s = million indicator updates per second. Streaming is the per-tick\n' +
+    '`update` path (one value at a time); batch is the bulk array path. Higher is\n' +
+    'better. Numbers are machine-dependent — use them for relative comparison.',
+);

bindings/node/index.js

@@ -310,7 +310,7 @@ if (!nativeBinding) {
   throw new Error(`Failed to load native binding`)
 }
 
-const { version, SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA, MOM, CMO, DPO, StdDev, UlcerIndex, VerticalHorizontalFilter, ZScore, MACD, BollingerBands, ATR, Stochastic, OBV, ADX, ADXR, CCI, WilliamsR, MFI, PSAR, Keltner, Donchian, VWAP, RollingVWAP, AwesomeOscillator, Aroon, KAMA, RVI, PGO, KST, SMI, LaguerreRSI, ConnorsRSI, Inertia, ALMA, McGinleyDynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA, APO, AwesomeOscillatorHistogram, CFO, ZeroLagMACD, ElderImpulse, STC, T3, TSI, PMO, TII, ADL, VolumePriceTrend, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex, EaseOfMovement, KVO, VolumeOscillator, NVI, PVI, WilliamsAD, AnchoredVWAP, DemandIndex, TSV, VZO, MarketFacilitationIndex, SuperTrend, ChandelierExit, ChandeKrollStop, AtrTrailingStop, HiLoActivator, VoltyStop, YoyoExit, DonchianStop, PercentageTrailingStop, StepTrailingStop, RenkoTrailingStop, TypicalPrice, MedianPrice, WeightedClose, LinearRegression, LinRegSlope, AcceleratorOscillator, BalanceOfPower, ChoppinessIndex, TrueRange, ChaikinVolatility, LinRegAngle, BollingerBandwidth, PercentB, NATR, HistoricalVolatility, AroonOscillator, Vortex, RWI, WaveTrend, MassIndex, StochRSI, UltimateOscillator, PPO, Coppock, VWMA, RVIVolatility, ParkinsonVolatility, GarmanKlassVolatility, RogersSatchellVolatility, YangZhangVolatility, MaEnvelope, AccelerationBands, StarcBands, AtrBands, HurstChannel, LinRegChannel, StandardErrorBands, DoubleBollinger, TtmSqueeze, FractalChaosBands, VwapStdDevBands, ClassicPivots, FibonacciPivots, Camarilla, WoodiePivots, DemarkPivots, WilliamsFractals, ZigZag, TDSetup, TDSequential, TDDeMarker, TDREI, TDPressure, TDCombo, TDCountdown, TDLines, TDRangeProjection, TDDifferential, TDOpen, TDRiskLevel, SuperSmoother, FisherTransform, InverseFisherTransform, Decycler, DecyclerOscillator, RoofingFilter, CenterOfGravity, CyberneticCycle, InstantaneousTrendline, EhlersStochastic, EmpiricalModeDecomposition, HilbertDominantCycle, AdaptiveCycle, SineWave, MAMA, FAMA, Ichimoku, HeikinAshi, Variance, CoefficientOfVariation, Skewness, Kurtosis, StandardError, DetrendedStdDev, RSquared, MedianAbsoluteDeviation, Autocorrelation, HurstExponent, PearsonCorrelation, Beta, SpearmanCorrelation, ValueArea, InitialBalance, OpeningRange, Doji, Hammer, InvertedHammer, HangingMan, ShootingStar, Engulfing, Harami, MorningEveningStar, ThreeSoldiersOrCrows, PiercingDarkCloud, Marubozu, Tweezer, SpinningTop, ThreeInside, ThreeOutside, SharpeRatio, SortinoRatio, CalmarRatio, OmegaRatio, MaxDrawdown, AverageDrawdown, DrawdownDuration, PainIndex, ValueAtRisk, ConditionalValueAtRisk, ProfitFactor, GainLossRatio, RecoveryFactor, KellyCriterion, TreynorRatio, InformationRatio, Alpha } = nativeBinding
+const { version, SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA, MOM, CMO, DPO, StdDev, UlcerIndex, VerticalHorizontalFilter, ZScore, McGinleyDynamic, FRAMA, SuperSmoother, FisherTransform, Decycler, CenterOfGravity, CyberneticCycle, InstantaneousTrendline, EhlersStochastic, RVIVolatility, Variance, CoefficientOfVariation, Skewness, Kurtosis, StandardError, DetrendedStdDev, RSquared, MedianAbsoluteDeviation, Autocorrelation, HurstExponent, PearsonCorrelation, Beta, PairwiseBeta, SpearmanCorrelation, PairSpreadZScore, LeadLagCrossCorrelation, Cointegration, RelativeStrengthAB, MACD, BollingerBands, ATR, Stochastic, OBV, ADX, ADXR, CCI, WilliamsR, MFI, PSAR, Keltner, Donchian, VWAP, RollingVWAP, AwesomeOscillator, Aroon, Inertia, ConnorsRSI, LaguerreRSI, SMI, KST, PGO, RVI, AwesomeOscillatorHistogram, STC, ElderImpulse, ZeroLagMACD, CFO, APO, KAMA, EVWMA, Alligator, JMA, VIDYA, ALMA, T3, TSI, PMO, TII, ADL, VolumePriceTrend, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex, NVI, PVI, VolumeOscillator, KVO, WilliamsAD, AnchoredVWAP, DemandIndex, TSV, VZO, MarketFacilitationIndex, EaseOfMovement, SuperTrend, ChandelierExit, ChandeKrollStop, AtrTrailingStop, HiLoActivator, VoltyStop, YoyoExit, DonchianStop, PercentageTrailingStop, StepTrailingStop, RenkoTrailingStop, TypicalPrice, MedianPrice, WeightedClose, LinearRegression, LinRegSlope, AcceleratorOscillator, BalanceOfPower, ChoppinessIndex, TrueRange, ChaikinVolatility, YangZhangVolatility, RogersSatchellVolatility, GarmanKlassVolatility, ParkinsonVolatility, LinRegAngle, BollingerBandwidth, PercentB, NATR, HistoricalVolatility, AroonOscillator, WaveTrend, RWI, Vortex, MassIndex, StochRSI, UltimateOscillator, PPO, Coppock, VWMA, MaEnvelope, AccelerationBands, StarcBands, AtrBands, HurstChannel, LinRegChannel, StandardErrorBands, DoubleBollinger, TtmSqueeze, FractalChaosBands, VwapStdDevBands, ClassicPivots, FibonacciPivots, Camarilla, WoodiePivots, DemarkPivots, WilliamsFractals, ZigZag, TDSetup, TDSequential, TDDeMarker, TDREI, TDPressure, TDCombo, TDCountdown, TDLines, TDRangeProjection, TDDifferential, TDOpen, TDRiskLevel, InverseFisherTransform, DecyclerOscillator, RoofingFilter, EmpiricalModeDecomposition, HilbertDominantCycle, AdaptiveCycle, SineWave, MAMA, FAMA, Ichimoku, HeikinAshi, ValueArea, InitialBalance, OpeningRange, Doji, Hammer, InvertedHammer, HangingMan, ShootingStar, Engulfing, Harami, MorningEveningStar, ThreeSoldiersOrCrows, PiercingDarkCloud, Marubozu, Tweezer, SpinningTop, ThreeInside, ThreeOutside, OrderBookImbalanceTop1, OrderBookImbalanceFull, Microprice, QuotedSpread, DepthSlope, OrderBookImbalanceTopN, SignedVolume, CumulativeVolumeDelta, TradeImbalance, EffectiveSpread, RealizedSpread, KylesLambda, Footprint, SharpeRatio, SortinoRatio, CalmarRatio, OmegaRatio, MaxDrawdown, AverageDrawdown, DrawdownDuration, PainIndex, ValueAtRisk, ConditionalValueAtRisk, ProfitFactor, GainLossRatio, RecoveryFactor, KellyCriterion, TreynorRatio, InformationRatio, Alpha } = nativeBinding
 
 module.exports.version = version
 module.exports.SMA = SMA
@@ -332,6 +332,34 @@ module.exports.StdDev = StdDev
 module.exports.UlcerIndex = UlcerIndex
 module.exports.VerticalHorizontalFilter = VerticalHorizontalFilter
 module.exports.ZScore = ZScore
+module.exports.McGinleyDynamic = McGinleyDynamic
+module.exports.FRAMA = FRAMA
+module.exports.SuperSmoother = SuperSmoother
+module.exports.FisherTransform = FisherTransform
+module.exports.Decycler = Decycler
+module.exports.CenterOfGravity = CenterOfGravity
+module.exports.CyberneticCycle = CyberneticCycle
+module.exports.InstantaneousTrendline = InstantaneousTrendline
+module.exports.EhlersStochastic = EhlersStochastic
+module.exports.RVIVolatility = RVIVolatility
+module.exports.Variance = Variance
+module.exports.CoefficientOfVariation = CoefficientOfVariation
+module.exports.Skewness = Skewness
+module.exports.Kurtosis = Kurtosis
+module.exports.StandardError = StandardError
+module.exports.DetrendedStdDev = DetrendedStdDev
+module.exports.RSquared = RSquared
+module.exports.MedianAbsoluteDeviation = MedianAbsoluteDeviation
+module.exports.Autocorrelation = Autocorrelation
+module.exports.HurstExponent = HurstExponent
+module.exports.PearsonCorrelation = PearsonCorrelation
+module.exports.Beta = Beta
+module.exports.PairwiseBeta = PairwiseBeta
+module.exports.SpearmanCorrelation = SpearmanCorrelation
+module.exports.PairSpreadZScore = PairSpreadZScore
+module.exports.LeadLagCrossCorrelation = LeadLagCrossCorrelation
+module.exports.Cointegration = Cointegration
+module.exports.RelativeStrengthAB = RelativeStrengthAB
 module.exports.MACD = MACD
 module.exports.BollingerBands = BollingerBands
 module.exports.ATR = ATR
@@ -349,27 +377,25 @@ module.exports.VWAP = VWAP
 module.exports.RollingVWAP = RollingVWAP
 module.exports.AwesomeOscillator = AwesomeOscillator
 module.exports.Aroon = Aroon
-module.exports.KAMA = KAMA
-module.exports.RVI = RVI
-module.exports.PGO = PGO
-module.exports.KST = KST
-module.exports.SMI = SMI
-module.exports.LaguerreRSI = LaguerreRSI
-module.exports.ConnorsRSI = ConnorsRSI
 module.exports.Inertia = Inertia
-module.exports.ALMA = ALMA
-module.exports.McGinleyDynamic = McGinleyDynamic
-module.exports.FRAMA = FRAMA
-module.exports.VIDYA = VIDYA
-module.exports.JMA = JMA
-module.exports.Alligator = Alligator
-module.exports.EVWMA = EVWMA
-module.exports.APO = APO
+module.exports.ConnorsRSI = ConnorsRSI
+module.exports.LaguerreRSI = LaguerreRSI
+module.exports.SMI = SMI
+module.exports.KST = KST
+module.exports.PGO = PGO
+module.exports.RVI = RVI
 module.exports.AwesomeOscillatorHistogram = AwesomeOscillatorHistogram
-module.exports.CFO = CFO
-module.exports.ZeroLagMACD = ZeroLagMACD
-module.exports.ElderImpulse = ElderImpulse
 module.exports.STC = STC
+module.exports.ElderImpulse = ElderImpulse
+module.exports.ZeroLagMACD = ZeroLagMACD
+module.exports.CFO = CFO
+module.exports.APO = APO
+module.exports.KAMA = KAMA
+module.exports.EVWMA = EVWMA
+module.exports.Alligator = Alligator
+module.exports.JMA = JMA
+module.exports.VIDYA = VIDYA
+module.exports.ALMA = ALMA
 module.exports.T3 = T3
 module.exports.TSI = TSI
 module.exports.PMO = PMO
@@ -379,17 +405,17 @@ module.exports.VolumePriceTrend = VolumePriceTrend
 module.exports.ChaikinMoneyFlow = ChaikinMoneyFlow
 module.exports.ChaikinOscillator = ChaikinOscillator
 module.exports.ForceIndex = ForceIndex
-module.exports.EaseOfMovement = EaseOfMovement
-module.exports.KVO = KVO
-module.exports.VolumeOscillator = VolumeOscillator
 module.exports.NVI = NVI
 module.exports.PVI = PVI
+module.exports.VolumeOscillator = VolumeOscillator
+module.exports.KVO = KVO
 module.exports.WilliamsAD = WilliamsAD
 module.exports.AnchoredVWAP = AnchoredVWAP
 module.exports.DemandIndex = DemandIndex
 module.exports.TSV = TSV
 module.exports.VZO = VZO
 module.exports.MarketFacilitationIndex = MarketFacilitationIndex
+module.exports.EaseOfMovement = EaseOfMovement
 module.exports.SuperTrend = SuperTrend
 module.exports.ChandelierExit = ChandelierExit
 module.exports.ChandeKrollStop = ChandeKrollStop
@@ -411,26 +437,25 @@ module.exports.BalanceOfPower = BalanceOfPower
 module.exports.ChoppinessIndex = ChoppinessIndex
 module.exports.TrueRange = TrueRange
 module.exports.ChaikinVolatility = ChaikinVolatility
+module.exports.YangZhangVolatility = YangZhangVolatility
+module.exports.RogersSatchellVolatility = RogersSatchellVolatility
+module.exports.GarmanKlassVolatility = GarmanKlassVolatility
+module.exports.ParkinsonVolatility = ParkinsonVolatility
 module.exports.LinRegAngle = LinRegAngle
 module.exports.BollingerBandwidth = BollingerBandwidth
 module.exports.PercentB = PercentB
 module.exports.NATR = NATR
 module.exports.HistoricalVolatility = HistoricalVolatility
 module.exports.AroonOscillator = AroonOscillator
-module.exports.Vortex = Vortex
-module.exports.RWI = RWI
 module.exports.WaveTrend = WaveTrend
+module.exports.RWI = RWI
+module.exports.Vortex = Vortex
 module.exports.MassIndex = MassIndex
 module.exports.StochRSI = StochRSI
 module.exports.UltimateOscillator = UltimateOscillator
 module.exports.PPO = PPO
 module.exports.Coppock = Coppock
 module.exports.VWMA = VWMA
-module.exports.RVIVolatility = RVIVolatility
-module.exports.ParkinsonVolatility = ParkinsonVolatility
-module.exports.GarmanKlassVolatility = GarmanKlassVolatility
-module.exports.RogersSatchellVolatility = RogersSatchellVolatility
-module.exports.YangZhangVolatility = YangZhangVolatility
 module.exports.MaEnvelope = MaEnvelope
 module.exports.AccelerationBands = AccelerationBands
 module.exports.StarcBands = StarcBands
@@ -461,16 +486,9 @@ module.exports.TDRangeProjection = TDRangeProjection
 module.exports.TDDifferential = TDDifferential
 module.exports.TDOpen = TDOpen
 module.exports.TDRiskLevel = TDRiskLevel
-module.exports.SuperSmoother = SuperSmoother
-module.exports.FisherTransform = FisherTransform
 module.exports.InverseFisherTransform = InverseFisherTransform
-module.exports.Decycler = Decycler
 module.exports.DecyclerOscillator = DecyclerOscillator
 module.exports.RoofingFilter = RoofingFilter
-module.exports.CenterOfGravity = CenterOfGravity
-module.exports.CyberneticCycle = CyberneticCycle
-module.exports.InstantaneousTrendline = InstantaneousTrendline
-module.exports.EhlersStochastic = EhlersStochastic
 module.exports.EmpiricalModeDecomposition = EmpiricalModeDecomposition
 module.exports.HilbertDominantCycle = HilbertDominantCycle
 module.exports.AdaptiveCycle = AdaptiveCycle
@@ -479,19 +497,6 @@ module.exports.MAMA = MAMA
 module.exports.FAMA = FAMA
 module.exports.Ichimoku = Ichimoku
 module.exports.HeikinAshi = HeikinAshi
-module.exports.Variance = Variance
-module.exports.CoefficientOfVariation = CoefficientOfVariation
-module.exports.Skewness = Skewness
-module.exports.Kurtosis = Kurtosis
-module.exports.StandardError = StandardError
-module.exports.DetrendedStdDev = DetrendedStdDev
-module.exports.RSquared = RSquared
-module.exports.MedianAbsoluteDeviation = MedianAbsoluteDeviation
-module.exports.Autocorrelation = Autocorrelation
-module.exports.HurstExponent = HurstExponent
-module.exports.PearsonCorrelation = PearsonCorrelation
-module.exports.Beta = Beta
-module.exports.SpearmanCorrelation = SpearmanCorrelation
 module.exports.ValueArea = ValueArea
 module.exports.InitialBalance = InitialBalance
 module.exports.OpeningRange = OpeningRange
@@ -510,7 +515,19 @@ module.exports.Tweezer = Tweezer
 module.exports.SpinningTop = SpinningTop
 module.exports.ThreeInside = ThreeInside
 module.exports.ThreeOutside = ThreeOutside
-// Family 15: Risk / Performance metrics
+module.exports.OrderBookImbalanceTop1 = OrderBookImbalanceTop1
+module.exports.OrderBookImbalanceFull = OrderBookImbalanceFull
+module.exports.Microprice = Microprice
+module.exports.QuotedSpread = QuotedSpread
+module.exports.DepthSlope = DepthSlope
+module.exports.OrderBookImbalanceTopN = OrderBookImbalanceTopN
+module.exports.SignedVolume = SignedVolume
+module.exports.CumulativeVolumeDelta = CumulativeVolumeDelta
+module.exports.TradeImbalance = TradeImbalance
+module.exports.EffectiveSpread = EffectiveSpread
+module.exports.RealizedSpread = RealizedSpread
+module.exports.KylesLambda = KylesLambda
+module.exports.Footprint = Footprint
 module.exports.SharpeRatio = SharpeRatio
 module.exports.SortinoRatio = SortinoRatio
 module.exports.CalmarRatio = CalmarRatio

bindings/node/npm/darwin-arm64/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-darwin-arm64",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/npm/darwin-x64/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-darwin-x64",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/npm/linux-arm64-gnu/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-linux-arm64-gnu",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/npm/linux-x64-gnu/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-linux-x64-gnu",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/npm/win32-arm64-msvc/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-win32-arm64-msvc",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/npm/win32-x64-msvc/package.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra-win32-x64-msvc",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "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": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "wickra",
-      "version": "0.3.1",
+      "version": "0.4.3",
       "license": "PolyForm-Noncommercial-1.0.0",
       "devDependencies": {
         "@napi-rs/cli": "^2.18.0"
@@ -15,12 +15,12 @@
         "node": ">= 18"
       },
       "optionalDependencies": {
-        "wickra-darwin-arm64": "0.3.1",
-        "wickra-darwin-x64": "0.3.1",
-        "wickra-linux-arm64-gnu": "0.3.1",
-        "wickra-linux-x64-gnu": "0.3.1",
-        "wickra-win32-arm64-msvc": "0.3.1",
-        "wickra-win32-x64-msvc": "0.3.1"
+        "wickra-darwin-arm64": "0.4.3",
+        "wickra-darwin-x64": "0.4.3",
+        "wickra-linux-arm64-gnu": "0.4.3",
+        "wickra-linux-x64-gnu": "0.4.3",
+        "wickra-win32-arm64-msvc": "0.4.3",
+        "wickra-win32-x64-msvc": "0.4.3"
       }
     },
     "node_modules/@napi-rs/cli": {
@@ -41,8 +41,8 @@
       }
     },
     "node_modules/wickra-darwin-arm64": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.4.3.tgz",
       "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
       "cpu": [
         "arm64"
@@ -57,8 +57,8 @@
       }
     },
     "node_modules/wickra-darwin-x64": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.4.3.tgz",
       "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
       "cpu": [
         "x64"
@@ -73,8 +73,8 @@
       }
     },
     "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.4.3.tgz",
       "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
       "cpu": [
         "arm64"
@@ -89,8 +89,8 @@
       }
     },
     "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.4.3.tgz",
       "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
       "cpu": [
         "x64"
@@ -105,8 +105,8 @@
       }
     },
     "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.4.3.tgz",
       "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
       "cpu": [
         "arm64"
@@ -121,8 +121,8 @@
       }
     },
     "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.3.1",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.3.1.tgz",
+      "version": "0.4.3",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.4.3.tgz",
       "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
       "cpu": [
         "x64"

bindings/node/package.json

@@ -1,11 +1,11 @@
 {
   "name": "wickra",
-  "version": "0.3.1",
+  "version": "0.4.3",
   "description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
-  "author": "kingchenc <wickra.lib@gmail.com>",
+  "author": "kingchenc <support@wickra.org>",
   "main": "index.js",
   "types": "index.d.ts",
-  "license": "PolyForm-Noncommercial-1.0.0",
+  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
   "keywords": [
     "trading",
     "indicators",
@@ -47,12 +47,12 @@
     "node": ">= 18"
   },
   "optionalDependencies": {
-    "wickra-linux-x64-gnu": "0.3.1",
-    "wickra-linux-arm64-gnu": "0.3.1",
-    "wickra-darwin-x64": "0.3.1",
-    "wickra-darwin-arm64": "0.3.1",
-    "wickra-win32-x64-msvc": "0.3.1",
-    "wickra-win32-arm64-msvc": "0.3.1"
+    "wickra-linux-x64-gnu": "0.4.3",
+    "wickra-linux-arm64-gnu": "0.4.3",
+    "wickra-darwin-x64": "0.4.3",
+    "wickra-darwin-arm64": "0.4.3",
+    "wickra-win32-x64-msvc": "0.4.3",
+    "wickra-win32-arm64-msvc": "0.4.3"
   },
   "scripts": {
     "build": "napi build --platform --release",
@@ -60,7 +60,8 @@
     "artifacts": "napi artifacts",
     "universal": "napi universal",
     "version": "napi version",
-    "test": "node --test __tests__/"
+    "test": "node --test __tests__/",
+    "bench": "node benchmarks/throughput.js"
   },
   "devDependencies": {
     "@napi-rs/cli": "^2.18.0"

bindings/python/Cargo.toml

@@ -5,7 +5,7 @@ version.workspace = true
 authors.workspace = true
 edition.workspace = true
 rust-version.workspace = true
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

bindings/python/README.md

@@ -1,314 +1,72 @@
-# Wickra
+# Wickra — Python
 
 [![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)
-[![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: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators for Python. `pip install wickra` — no
+system dependencies, no C build tooling.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the Python binding (PyO3); it
+exposes 200+ streaming-first indicators across sixteen families.
+
+## Install
+
+```bash
+pip install wickra
+```
+
+Pre-built wheels ship for Linux, macOS, and Windows — there is nothing to
+compile and no C library to track down.
+
+## Quick start
 
 ```python
 import numpy as np
 import wickra as ta
 
-# Batch: classic TA-Lib-style usage
+# Batch: classic TA-Lib-style usage over a whole array.
 prices = np.linspace(100, 200, 1000)
 rsi = ta.RSI(14)
 values = rsi.batch(prices)              # numpy array, NaN during warmup
 
-# Streaming: same indicator, fed tick by tick
+# Streaming: the same indicator, fed tick by tick in O(1).
 rsi = ta.RSI(14)
 for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
+    value = rsi.update(price)           # no recomputation over history
     if value is not None and value > 70:
         print("overbought")
 ```
 
-## Why Wickra exists
+`batch(prices)` and feeding the same prices through `update()` produce
+identical values — the equivalence is enforced by the test suite.
 
-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:
+## Documentation
 
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★ 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    |
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and documentation site:
 
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable examples:** [`examples/python/`](https://github.com/wickra-lib/wickra/tree/main/examples/python)
 
-## Benchmark: how much faster is "streaming-first"?
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-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.
+## Disclaimer
 
-- **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.
-
-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.
-
-### Batch — single full pass over a 20 000-bar series
-
-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.
-
-| 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)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-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 (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> 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.
-
-Run the suite yourself:
-
-```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
-```
-
-## Indicators
-
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
-
-| 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, Detrended StdDev |
-| 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 |
-| 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, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, 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 |
-| 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 |
-| 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) |
-
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
-
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
-}
-```
-
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
-
-## Project layout
-
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .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.
-
-## Building everything from source
-
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
-
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-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.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+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).

bindings/python/pyproject.toml

@@ -4,11 +4,11 @@ build-backend = "maturin"
 
 [project]
 name = "wickra"
-version = "0.3.1"
+version = "0.4.3"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
-license = { text = "PolyForm-Noncommercial-1.0.0" }
-authors = [{ name = "kingchenc", email = "wickra.lib@gmail.com" }]
+license = { text = "PolyForm-Noncommercial-1.0.0 with additional personal-account permissions; see LICENSE" }
+authors = [{ name = "kingchenc", email = "support@wickra.org" }]
 requires-python = ">=3.9"
 keywords = ["finance", "trading", "indicators", "technical-analysis", "ta-lib"]
 classifiers = [

bindings/python/python/wickra/__init__.py

@@ -161,6 +161,11 @@ from ._wickra import (
     HurstExponent,
     PearsonCorrelation,
     Beta,
+    PairwiseBeta,
+    PairSpreadZScore,
+    LeadLagCrossCorrelation,
+    Cointegration,
+    RelativeStrengthAB,
     SpearmanCorrelation,
     # Ehlers / Cycle
     SuperSmoother,
@@ -235,6 +240,23 @@ from ._wickra import (
     SpinningTop,
     ThreeInside,
     ThreeOutside,
+    # Microstructure: order book
+    OrderBookImbalanceTop1,
+    OrderBookImbalanceTopN,
+    OrderBookImbalanceFull,
+    Microprice,
+    QuotedSpread,
+    DepthSlope,
+    # Microstructure: trade flow
+    SignedVolume,
+    CumulativeVolumeDelta,
+    TradeImbalance,
+    # Microstructure: price impact
+    EffectiveSpread,
+    RealizedSpread,
+    KylesLambda,
+    # Microstructure: footprint
+    Footprint,
     # Risk / Performance
     SharpeRatio,
     SortinoRatio,
@@ -393,6 +415,11 @@ __all__ = [
     "HurstExponent",
     "PearsonCorrelation",
     "Beta",
+    "PairwiseBeta",
+    "PairSpreadZScore",
+    "LeadLagCrossCorrelation",
+    "Cointegration",
+    "RelativeStrengthAB",
     "SpearmanCorrelation",
     # Ehlers / Cycle
     "SuperSmoother",
@@ -467,6 +494,23 @@ __all__ = [
     "SpinningTop",
     "ThreeInside",
     "ThreeOutside",
+    # Microstructure: order book
+    "OrderBookImbalanceTop1",
+    "OrderBookImbalanceTopN",
+    "OrderBookImbalanceFull",
+    "Microprice",
+    "QuotedSpread",
+    "DepthSlope",
+    # Microstructure: trade flow
+    "SignedVolume",
+    "CumulativeVolumeDelta",
+    "TradeImbalance",
+    # Microstructure: price impact
+    "EffectiveSpread",
+    "RealizedSpread",
+    "KylesLambda",
+    # Microstructure: footprint
+    "Footprint",
     # Risk / Performance
     "SharpeRatio",
     "SortinoRatio",

bindings/python/tests/test_input_validation.py

@@ -35,6 +35,72 @@ def test_unequal_length_candle_batch_raises(ohlc_series):
         ta.Aroon(14).batch(high, short)
 
 
+def test_pairwise_beta_rejects_bad_period():
+    with pytest.raises(ValueError):
+        ta.PairwiseBeta(0)
+    with pytest.raises(ValueError):
+        ta.PairwiseBeta(1)
+
+
+def test_unequal_length_pair_batch_raises(sine_prices):
+    a = np.ascontiguousarray((sine_prices + 100.0).astype(np.float64))
+    b = a[:-1]
+    with pytest.raises(ValueError):
+        ta.PairwiseBeta(20).batch(a, b)
+    with pytest.raises(ValueError):
+        ta.PairSpreadZScore(20, 20).batch(a, b)
+
+
+def test_pair_spread_zscore_rejects_bad_periods():
+    with pytest.raises(ValueError):
+        ta.PairSpreadZScore(1, 20)
+    with pytest.raises(ValueError):
+        ta.PairSpreadZScore(20, 1)
+
+
+def test_lead_lag_rejects_bad_params():
+    with pytest.raises(ValueError):
+        ta.LeadLagCrossCorrelation(1, 5)
+    with pytest.raises(ValueError):
+        ta.LeadLagCrossCorrelation(10, 0)
+
+
+def test_lead_lag_unequal_length_batch_raises(sine_prices):
+    a = np.ascontiguousarray((sine_prices + 100.0).astype(np.float64))
+    b = a[:-1]
+    with pytest.raises(ValueError):
+        ta.LeadLagCrossCorrelation(12, 5).batch(a, b)
+
+
+def test_cointegration_rejects_too_small_period():
+    # period must be >= 2*adf_lags + 4.
+    with pytest.raises(ValueError):
+        ta.Cointegration(3, 0)
+    with pytest.raises(ValueError):
+        ta.Cointegration(5, 1)
+
+
+def test_cointegration_unequal_length_batch_raises(sine_prices):
+    a = np.ascontiguousarray((sine_prices + 100.0).astype(np.float64))
+    b = a[:-1]
+    with pytest.raises(ValueError):
+        ta.Cointegration(20, 1).batch(a, b)
+
+
+def test_relative_strength_rejects_zero_periods():
+    with pytest.raises(ValueError):
+        ta.RelativeStrengthAB(0, 14)
+    with pytest.raises(ValueError):
+        ta.RelativeStrengthAB(20, 0)
+
+
+def test_relative_strength_unequal_length_batch_raises(sine_prices):
+    a = np.ascontiguousarray((sine_prices + 100.0).astype(np.float64))
+    b = a[:-1]
+    with pytest.raises(ValueError):
+        ta.RelativeStrengthAB(10, 14).batch(a, b)
+
+
 def test_roc_and_trix_have_default_periods():
     # ROC/TRIX gained constructor defaults matching the TA-Lib convention.
     assert ta.ROC().period == 10
@@ -100,3 +166,75 @@ 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)

bindings/python/tests/test_known_values.py

@@ -429,6 +429,67 @@ def test_information_ratio_known_window():
     assert math.isclose(out[-1], expected, rel_tol=1e-9)
 
 
+def test_pairwise_beta_squared_price_is_two():
+    # a = b² ⇒ a's log-returns are exactly 2× b's ⇒ pairwise beta = 2.
+    # b must have *varying* returns (a constant-return path has zero variance
+    # and an undefined slope, which the indicator reports as 0).
+    b = np.array([100.0 + 10.0 * math.sin(i * 0.5) for i in range(20)])
+    a = b**2
+    out = ta.PairwiseBeta(5).batch(a, b)
+    assert math.isclose(out[-1], 2.0, rel_tol=1e-9)
+
+
+def test_pairwise_beta_inverse_price_is_minus_one():
+    # a = 1/b ⇒ a's log-returns are −1× b's ⇒ pairwise beta = −1.
+    b = np.array([100.0 + 10.0 * math.sin(i * 0.5) for i in range(20)])
+    a = 1.0 / b
+    out = ta.PairwiseBeta(5).batch(a, b)
+    assert math.isclose(out[-1], -1.0, rel_tol=1e-9)
+
+
+def test_pair_spread_zscore_flat_benchmark_sign():
+    # Flat b ⇒ hedge ratio 0 ⇒ spread = ln(a). With z_period = 2 the z-score
+    # collapses to the sign of the last move: rising a ⇒ +1, falling a ⇒ −1.
+    a = np.array([100.0, 100.0, 110.0, 105.0, 130.0])
+    b = np.full_like(a, 100.0)
+    out = ta.PairSpreadZScore(2, 2).batch(a, b)
+    assert math.isclose(out[-1], 1.0, abs_tol=1e-9)
+    assert math.isclose(out[-2], -1.0, abs_tol=1e-9)
+
+
+def test_lead_lag_cross_correlation_negative_lead():
+    # a is a delayed copy of b ⇒ b leads a ⇒ lag = −2, correlation ≈ 1.
+    def sig(t):
+        return math.sin(t * 0.4) + 0.4 * math.sin(t * 1.1) + 0.2 * math.cos(t * 0.27)
+
+    n = 60
+    a = np.array([sig(t - 2) for t in range(n)])
+    b = np.array([sig(t) for t in range(n)])
+    out = ta.LeadLagCrossCorrelation(12, 5).batch(a, b)
+    assert int(out[-1, 0]) == -2
+    assert out[-1, 1] > 0.99
+
+
+def test_cointegration_perfect_pair():
+    # a = 2*b + 5 exactly ⇒ hedge ratio 2, zero spread, degenerate ADF ⇒ 0.
+    b = np.array([100.0 + t for t in range(40)])
+    a = 2.0 * b + 5.0
+    out = ta.Cointegration(20, 1).batch(a, b)
+    assert math.isclose(out[-1, 0], 2.0, rel_tol=1e-9)
+    assert math.isclose(out[-1, 1], 0.0, abs_tol=1e-6)
+    assert math.isclose(out[-1, 2], 0.0, abs_tol=1e-12)
+
+
+def test_relative_strength_rising_ratio_is_overbought():
+    # a rises while b is flat ⇒ ratio strictly increases ⇒ RSI saturates at 100.
+    n = 20
+    a = np.array([100.0 + 2.0 * t for t in range(n)])
+    b = np.full(n, 100.0)
+    out = ta.RelativeStrengthAB(5, 5).batch(a, b)
+    assert out[-1, 0] > 1.0
+    assert math.isclose(out[-1, 2], 100.0, abs_tol=1e-9)
+
+
 def test_value_at_risk_known_window():
     # returns -5..4 *0.01; q=0.05*9=0.45 -> -0.0455; VaR = 0.0455.
     returns = np.array([i * 0.01 for i in range(-5, 5)])
@@ -762,3 +823,126 @@ 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)

bindings/python/tests/test_lifecycle.py

@@ -129,3 +129,92 @@ 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)"

bindings/python/tests/test_new_indicators.py

@@ -159,6 +159,8 @@ PAIR = [
     (ta.TreynorRatio, (20, 0.0)),
     (ta.InformationRatio, (20,)),
     (ta.Alpha, (20, 0.0)),
+    (ta.PairwiseBeta, (20,)),
+    (ta.PairSpreadZScore, (20, 20)),
 ]
 
 
@@ -178,6 +180,95 @@ def test_pair_streaming_matches_batch(cls, args, sine_prices):
     assert _eq_nan(batch, np.array(streamed, dtype=np.float64))
 
 
+def _ll_signal(t):
+    return math.sin(t * 0.4) + 0.4 * math.sin(t * 1.1) + 0.2 * math.cos(t * 0.27)
+
+
+def test_lead_lag_detects_lead():
+    n = 60
+    a = np.array([_ll_signal(t) for t in range(n)])
+    # b is a delayed by 3 ⇒ a leads b ⇒ lag = +3, correlation ≈ 1.
+    b = np.array([_ll_signal(t - 3) for t in range(n)])
+    out = ta.LeadLagCrossCorrelation(12, 5).batch(a, b)
+    assert out.shape == (n, 2)
+    assert int(out[-1, 0]) == 3
+    assert out[-1, 1] > 0.99
+
+
+def test_lead_lag_streaming_matches_batch():
+    n = 60
+    a = np.array([_ll_signal(t) for t in range(n)])
+    b = np.array([_ll_signal(t - 2) for t in range(n)])
+    ind = ta.LeadLagCrossCorrelation(12, 5)
+    batch = ind.batch(a, b)
+    streamer = ta.LeadLagCrossCorrelation(12, 5)
+    for i in range(n):
+        v = streamer.update(float(a[i]), float(b[i]))
+        if v is None:
+            assert math.isnan(batch[i, 0]) and math.isnan(batch[i, 1])
+        else:
+            lag, corr = v
+            assert int(batch[i, 0]) == lag
+            assert math.isclose(batch[i, 1], corr, rel_tol=1e-12, abs_tol=1e-12)
+
+
+def test_cointegration_detects_mean_reverting_pair():
+    n = 80
+    b = np.array([50.0 + 0.5 * t for t in range(n)])
+    # a tracks 2*b with a small mean-reverting wobble ⇒ cointegrated.
+    a = 2.0 * b + 1.0 + 0.5 * np.sin(np.arange(n) * 0.6)
+    out = ta.Cointegration(40, 1).batch(a, b)
+    assert out.shape == (n, 3)
+    assert abs(out[-1, 0] - 2.0) < 0.1  # hedge ratio
+    assert out[-1, 2] < -2.0  # ADF statistic: strongly mean-reverting
+
+
+def test_cointegration_streaming_matches_batch():
+    n = 70
+    b = np.array([30.0 + 0.7 * t for t in range(n)])
+    a = 1.8 * b + 2.0 + 0.5 * np.sin(np.arange(n) * 0.4)
+    batch = ta.Cointegration(25, 2).batch(a, b)
+    streamer = ta.Cointegration(25, 2)
+    for i in range(n):
+        v = streamer.update(float(a[i]), float(b[i]))
+        if v is None:
+            assert np.all(np.isnan(batch[i]))
+        else:
+            hr, sp, adf = v
+            assert math.isclose(batch[i, 0], hr, rel_tol=1e-12, abs_tol=1e-12)
+            assert math.isclose(batch[i, 1], sp, rel_tol=1e-12, abs_tol=1e-12)
+            assert math.isclose(batch[i, 2], adf, rel_tol=1e-12, abs_tol=1e-12)
+
+
+def test_relative_strength_constant_ratio():
+    n = 30
+    a = np.full(n, 200.0)
+    b = np.full(n, 100.0)  # ratio is a constant 2
+    out = ta.RelativeStrengthAB(5, 5).batch(a, b)
+    assert out.shape == (n, 3)
+    assert math.isclose(out[-1, 0], 2.0, abs_tol=1e-12)  # ratio
+    assert math.isclose(out[-1, 1], 2.0, abs_tol=1e-12)  # ratio MA
+    assert math.isclose(out[-1, 2], 50.0, abs_tol=1e-9)  # flat ratio ⇒ RSI 50
+
+
+def test_relative_strength_streaming_matches_batch():
+    n = 60
+    tt = np.arange(n)
+    a = 100.0 + 5.0 * np.sin(tt * 0.3)
+    b = 100.0 + 2.0 * np.cos(tt * 0.2)
+    batch = ta.RelativeStrengthAB(10, 14).batch(a, b)
+    streamer = ta.RelativeStrengthAB(10, 14)
+    for i in range(n):
+        v = streamer.update(float(a[i]), float(b[i]))
+        if v is None:
+            assert np.all(np.isnan(batch[i]))
+        else:
+            ratio, ma, rsi = v
+            assert math.isclose(batch[i, 0], ratio, rel_tol=1e-12, abs_tol=1e-12)
+            assert math.isclose(batch[i, 1], ma, rel_tol=1e-12, abs_tol=1e-12)
+            assert math.isclose(batch[i, 2], rsi, rel_tol=1e-12, abs_tol=1e-12)
+
+
 # --- Candle-input, single-output indicators -------------------------------
 #
 # Each entry is (factory, batch-call). Streaming always feeds the full
@@ -1772,3 +1863,92 @@ def test_new_indicators_expose_lifecycle():
         assert ind.warmup_period() >= 1
         ind.reset()
         assert ind.is_ready() is False
+
+
+def _orderbook_snapshots(n: int) -> list:
+    """A deterministic varying sequence of order-book snapshots."""
+    snaps = []
+    for i in range(n):
+        bid_sz = 1.0 + (i % 5)
+        ask_sz = 1.0 + ((i + 2) % 4)
+        snaps.append(
+            (
+                [100.0, 99.0],
+                [bid_sz, 1.0],
+                [101.0, 102.0],
+                [ask_sz, 1.0],
+            )
+        )
+    return snaps
+
+
+def test_orderbook_indicators_streaming_equals_batch():
+    snaps = _orderbook_snapshots(40)
+    for make in (
+        ta.OrderBookImbalanceTop1,
+        lambda: ta.OrderBookImbalanceTopN(2),
+        ta.OrderBookImbalanceFull,
+        ta.Microprice,
+        ta.QuotedSpread,
+        ta.DepthSlope,
+    ):
+        batch = make().batch(snaps)
+        streamer = make()
+        streamed = np.array(
+            [streamer.update(*snap) for snap in snaps], dtype=np.float64
+        )
+        assert batch.shape == (len(snaps),)
+        assert _eq_nan(batch, streamed)
+
+
+def test_tradeflow_indicators_streaming_equals_batch():
+    n = 40
+    price = np.full(n, 100.0)
+    size = np.array([1.0 + (i % 5) for i in range(n)], dtype=np.float64)
+    is_buy = [i % 2 == 0 for i in range(n)]
+    for make in (
+        ta.SignedVolume,
+        ta.CumulativeVolumeDelta,
+        lambda: ta.TradeImbalance(5),
+    ):
+        batch = make().batch(price, size, is_buy)
+        streamer = make()
+        streamed = np.array(
+            [streamer.update(price[i], size[i], is_buy[i]) for i in range(n)],
+            dtype=np.float64,
+        )
+        assert batch.shape == (n,)
+        assert _eq_nan(batch, streamed)
+
+
+def test_price_impact_indicators_streaming_equals_batch():
+    n = 40
+    mid = np.array([100.0 + 0.5 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
+    is_buy = [i % 2 == 0 for i in range(n)]
+    # Aggressive trades print across the mid in the aggressor's direction.
+    price = np.array(
+        [mid[i] + (0.02 if is_buy[i] else -0.02) for i in range(n)], dtype=np.float64
+    )
+    size = np.array([1.0 + (i % 5) for i in range(n)], dtype=np.float64)
+    for make in (ta.EffectiveSpread, lambda: ta.RealizedSpread(4), lambda: ta.KylesLambda(5)):
+        batch = make().batch(price, size, is_buy, mid)
+        streamer = make()
+        streamed = np.array(
+            [streamer.update(price[i], size[i], is_buy[i], mid[i]) for i in range(n)],
+            dtype=np.float64,
+        )
+        assert batch.shape == (n,)
+        assert _eq_nan(batch, streamed)
+
+
+def test_footprint_streaming_equals_batch():
+    n = 20
+    price = [100.0 + (i % 5) * 0.3 for i in range(n)]
+    size = [1.0 + (i % 3) for i in range(n)]
+    is_buy = [i % 2 == 0 for i in range(n)]
+    batch = ta.Footprint(1.0).batch(price, size, is_buy)
+    streamer = ta.Footprint(1.0)
+    assert len(batch) == n
+    for i in range(n):
+        streamed = streamer.update(price[i], size[i], is_buy[i])
+        assert np.array_equal(streamed, batch[i])

bindings/python/tests/test_smoke.py

@@ -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

bindings/python/tests/test_streaming_vs_batch.py

@@ -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)

bindings/wasm/Cargo.toml

@@ -5,7 +5,7 @@ version.workspace = true
 authors.workspace = true
 edition.workspace = true
 rust-version.workspace = true
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

bindings/wasm/README.md

@@ -1,314 +1,72 @@
-# Wickra
+# Wickra — WebAssembly
 
 [![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)
-[![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)
+[![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)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators in the browser. `npm install
+wickra-wasm` — pure WebAssembly, runs anywhere a modern JS engine does.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading dashboards and historical backtests
+share the exact same implementation. This package is the WebAssembly binding
+(wasm-bindgen, built for the `web` target); it exposes 200+ streaming-first
+indicators across sixteen families.
 
-```python
-import numpy as np
-import wickra as ta
-
-# Batch: classic TA-Lib-style usage
-prices = np.linspace(100, 200, 1000)
-rsi = ta.RSI(14)
-values = rsi.batch(prices)              # numpy array, NaN during warmup
-
-# Streaming: same indicator, fed tick by tick
-rsi = ta.RSI(14)
-for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
-    if value is not None and value > 70:
-        print("overbought")
-```
-
-## 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:
-
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★ 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    |
-
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
-
-## Benchmark: how much faster is "streaming-first"?
-
-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.
-
-- **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.
-
-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.
-
-### Batch — single full pass over a 20 000-bar series
-
-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.
-
-| Indicator           | **★ 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)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-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 | **★ Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> 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.
-
-Run the suite yourself:
+## Install
 
 ```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
+npm install wickra-wasm
 ```
 
-## Indicators
+## Quick start
 
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
+The module ships a default `init` export that loads the `.wasm` payload; await
+it once before constructing indicators.
 
-| 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, Detrended StdDev |
-| 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 |
-| 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, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, 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 |
-| 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 |
-| 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) |
+```js
+import init, { RSI } from 'wickra-wasm';
 
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
+await init(); // load the WebAssembly module once
 
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
+// Streaming: feed prices tick by tick in O(1).
+const rsi = new RSI(14);
+for (const price of liveFeed) {
+  const value = rsi.update(price); // null during warmup
+  if (value !== null && value > 70) {
+    console.log('overbought');
+  }
 }
 ```
 
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
+Constructors mirror the other bindings (`new SMA(20)`, `new MACD(12, 26, 9)`,
+`new BollingerBands(20, 2.0)`, …); `update()` returns the latest value or
+`null` while the indicator is still warming up.
 
-## Project layout
+## Documentation
 
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .github/workflows/       CI and release pipelines
-```
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and documentation site:
 
-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.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable browser examples:** [`examples/wasm/`](https://github.com/wickra-lib/wickra/tree/main/examples/wasm)
 
-## Building everything from source
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+## Disclaimer
 
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-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.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+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).

bindings/wasm/src/lib.rs

@@ -9,7 +9,7 @@
 #![allow(clippy::needless_pass_by_value)]
 #![allow(missing_debug_implementations)] // wasm_bindgen wrappers expose JS objects, no need for Debug
 
-use js_sys::{Float64Array, Object, Reflect};
+use js_sys::{Array, Float64Array, Object, Reflect};
 use wasm_bindgen::prelude::*;
 use wickra_core as wc;
 use wickra_core::{BatchExt, Indicator};
@@ -525,12 +525,229 @@ wasm_pair_indicator!(
     wc::PearsonCorrelation
 );
 wasm_pair_indicator!(WasmBeta, "Beta", wc::Beta);
+wasm_pair_indicator!(WasmPairwiseBeta, "PairwiseBeta", wc::PairwiseBeta);
 wasm_pair_indicator!(
     WasmSpearmanCorrelation,
     "SpearmanCorrelation",
     wc::SpearmanCorrelation
 );
 
+// ---------- PairSpreadZScore (two params) ----------
+
+#[wasm_bindgen(js_name = "PairSpreadZScore")]
+pub struct WasmPairSpreadZScore {
+    inner: wc::PairSpreadZScore,
+}
+
+#[wasm_bindgen(js_class = "PairSpreadZScore")]
+impl WasmPairSpreadZScore {
+    #[wasm_bindgen(constructor)]
+    pub fn new(beta_period: usize, z_period: usize) -> Result<WasmPairSpreadZScore, JsError> {
+        Ok(Self {
+            inner: wc::PairSpreadZScore::new(beta_period, z_period).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, a: f64, b: f64) -> Option<f64> {
+        self.inner.update((a, b))
+    }
+    /// Batch over two equally-sized arrays of prices. Returns one `f64` per
+    /// input position (`NaN` during warmup).
+    pub fn batch(&mut self, a: &[f64], b: &[f64]) -> Result<Float64Array, JsError> {
+        if a.len() != b.len() {
+            return Err(JsError::new("a and b must be equal length"));
+        }
+        let mut out = Vec::with_capacity(a.len());
+        for i in 0..a.len() {
+            out.push(self.inner.update((a[i], b[i])).unwrap_or(f64::NAN));
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- LeadLagCrossCorrelation (two params, object output) ----------
+
+#[wasm_bindgen(js_name = "LeadLagCrossCorrelation")]
+pub struct WasmLeadLagCrossCorrelation {
+    inner: wc::LeadLagCrossCorrelation,
+}
+
+#[wasm_bindgen(js_class = "LeadLagCrossCorrelation")]
+impl WasmLeadLagCrossCorrelation {
+    #[wasm_bindgen(constructor)]
+    pub fn new(window: usize, max_lag: usize) -> Result<WasmLeadLagCrossCorrelation, JsError> {
+        Ok(Self {
+            inner: wc::LeadLagCrossCorrelation::new(window, max_lag).map_err(map_err)?,
+        })
+    }
+    /// Returns `{ lag, correlation }`, or `null` during warmup. Positive lag
+    /// means `a` leads `b`.
+    pub fn update(&mut self, a: f64, b: f64) -> JsValue {
+        match self.inner.update((a, b)) {
+            Some(o) => {
+                let obj = Object::new();
+                Reflect::set(&obj, &"lag".into(), &(o.lag as f64).into()).ok();
+                Reflect::set(&obj, &"correlation".into(), &o.correlation.into()).ok();
+                obj.into()
+            }
+            None => JsValue::NULL,
+        }
+    }
+    /// Flat `Float64Array` of length `2 * n`: `[lag0, corr0, lag1, corr1, ...]`.
+    /// Warmup positions are NaN.
+    pub fn batch(&mut self, a: &[f64], b: &[f64]) -> Result<Float64Array, JsError> {
+        if a.len() != b.len() {
+            return Err(JsError::new("a and b must be equal length"));
+        }
+        let n = a.len();
+        let mut out = vec![f64::NAN; n * 2];
+        for i in 0..n {
+            if let Some(o) = self.inner.update((a[i], b[i])) {
+                out[i * 2] = o.lag as f64;
+                out[i * 2 + 1] = o.correlation;
+            }
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- Cointegration (two params, object output) ----------
+
+#[wasm_bindgen(js_name = "Cointegration")]
+pub struct WasmCointegration {
+    inner: wc::Cointegration,
+}
+
+#[wasm_bindgen(js_class = "Cointegration")]
+impl WasmCointegration {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize, adf_lags: usize) -> Result<WasmCointegration, JsError> {
+        Ok(Self {
+            inner: wc::Cointegration::new(period, adf_lags).map_err(map_err)?,
+        })
+    }
+    /// Returns `{ hedgeRatio, spread, adfStat }`, or `null` during warmup.
+    pub fn update(&mut self, a: f64, b: f64) -> JsValue {
+        match self.inner.update((a, b)) {
+            Some(o) => {
+                let obj = Object::new();
+                Reflect::set(&obj, &"hedgeRatio".into(), &o.hedge_ratio.into()).ok();
+                Reflect::set(&obj, &"spread".into(), &o.spread.into()).ok();
+                Reflect::set(&obj, &"adfStat".into(), &o.adf_stat.into()).ok();
+                obj.into()
+            }
+            None => JsValue::NULL,
+        }
+    }
+    /// Flat `Float64Array` of length `3 * n`:
+    /// `[hedgeRatio0, spread0, adfStat0, hedgeRatio1, ...]`. Warmup rows are NaN.
+    pub fn batch(&mut self, a: &[f64], b: &[f64]) -> Result<Float64Array, JsError> {
+        if a.len() != b.len() {
+            return Err(JsError::new("a and b must be equal length"));
+        }
+        let n = a.len();
+        let mut out = vec![f64::NAN; n * 3];
+        for i in 0..n {
+            if let Some(o) = self.inner.update((a[i], b[i])) {
+                out[i * 3] = o.hedge_ratio;
+                out[i * 3 + 1] = o.spread;
+                out[i * 3 + 2] = o.adf_stat;
+            }
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- RelativeStrengthAB (two params, object output) ----------
+
+#[wasm_bindgen(js_name = "RelativeStrengthAB")]
+pub struct WasmRelativeStrengthAb {
+    inner: wc::RelativeStrengthAB,
+}
+
+#[wasm_bindgen(js_class = "RelativeStrengthAB")]
+impl WasmRelativeStrengthAb {
+    #[wasm_bindgen(constructor)]
+    pub fn new(ma_period: usize, rsi_period: usize) -> Result<WasmRelativeStrengthAb, JsError> {
+        Ok(Self {
+            inner: wc::RelativeStrengthAB::new(ma_period, rsi_period).map_err(map_err)?,
+        })
+    }
+    /// Returns `{ ratio, ratioMa, ratioRsi }`, or `null` during warmup.
+    pub fn update(&mut self, a: f64, b: f64) -> JsValue {
+        match self.inner.update((a, b)) {
+            Some(o) => {
+                let obj = Object::new();
+                Reflect::set(&obj, &"ratio".into(), &o.ratio.into()).ok();
+                Reflect::set(&obj, &"ratioMa".into(), &o.ratio_ma.into()).ok();
+                Reflect::set(&obj, &"ratioRsi".into(), &o.ratio_rsi.into()).ok();
+                obj.into()
+            }
+            None => JsValue::NULL,
+        }
+    }
+    /// Flat `Float64Array` of length `3 * n`:
+    /// `[ratio0, ratioMa0, ratioRsi0, ratio1, ...]`. Warmup rows are NaN.
+    pub fn batch(&mut self, a: &[f64], b: &[f64]) -> Result<Float64Array, JsError> {
+        if a.len() != b.len() {
+            return Err(JsError::new("a and b must be equal length"));
+        }
+        let n = a.len();
+        let mut out = vec![f64::NAN; n * 3];
+        for i in 0..n {
+            if let Some(o) = self.inner.update((a[i], b[i])) {
+                out[i * 3] = o.ratio;
+                out[i * 3 + 1] = o.ratio_ma;
+                out[i * 3 + 2] = o.ratio_rsi;
+            }
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 // ---------- KAMA (three params) ----------
 
 #[wasm_bindgen(js_name = KAMA)]
@@ -5950,7 +6167,8 @@ impl WasmOpeningRange {
 //
 // All 15 patterns take Candles (open, high, low, close) and emit a signed f64
 // signal per bar: +1.0 bullish, -1.0 bearish, 0.0 no pattern. Doji is
-// direction-less and emits 0/+1 only.
+// direction-less by default (0/+1); pass `signed = true` to its constructor for
+// the dragonfly/gravestone signed +-1 encoding.
 
 macro_rules! wasm_candle_pattern {
     ($wasm:ident, $inner:ty, $js:ident) => {
@@ -6017,7 +6235,75 @@ macro_rules! wasm_candle_pattern {
     };
 }
 
-wasm_candle_pattern!(WasmDoji, wc::Doji, Doji);
+// Doji is the one pattern with an opt-in signed mode, so it is hand-written
+// rather than generated by `wasm_candle_pattern!`.
+#[wasm_bindgen(js_name = Doji)]
+pub struct WasmDoji {
+    inner: wc::Doji,
+}
+
+impl Default for WasmDoji {
+    fn default() -> Self {
+        Self::new(None)
+    }
+}
+
+#[wasm_bindgen(js_class = Doji)]
+impl WasmDoji {
+    #[wasm_bindgen(constructor)]
+    pub fn new(signed: Option<bool>) -> WasmDoji {
+        let inner = if signed.unwrap_or(false) {
+            wc::Doji::new().signed()
+        } else {
+            wc::Doji::new()
+        };
+        Self { inner }
+    }
+    pub fn update(
+        &mut self,
+        open: f64,
+        high: f64,
+        low: f64,
+        close: f64,
+    ) -> Result<Option<f64>, JsError> {
+        let c = wc::Candle::new(open, high, low, close, 0.0, 0).map_err(map_err)?;
+        Ok(self.inner.update(c))
+    }
+    pub fn batch(
+        &mut self,
+        open: &[f64],
+        high: &[f64],
+        low: &[f64],
+        close: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        let n = open.len();
+        if high.len() != n || low.len() != n || close.len() != n {
+            return Err(JsError::new("open, high, low, close must be equal length"));
+        }
+        let mut out = Vec::with_capacity(n);
+        for i in 0..n {
+            let c = wc::Candle::new(open[i], high[i], low[i], close[i], 0.0, 0).map_err(map_err)?;
+            out.push(self.inner.update(c).unwrap_or(f64::NAN));
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    #[wasm_bindgen(js_name = isSigned)]
+    pub fn is_signed(&self) -> bool {
+        self.inner.is_signed()
+    }
+}
+
 wasm_candle_pattern!(WasmHammer, wc::Hammer, Hammer);
 wasm_candle_pattern!(WasmInvertedHammer, wc::InvertedHammer, InvertedHammer);
 wasm_candle_pattern!(WasmHangingMan, wc::HangingMan, HangingMan);
@@ -6045,6 +6331,422 @@ wasm_candle_pattern!(WasmSpinningTop, wc::SpinningTop, SpinningTop);
 wasm_candle_pattern!(WasmThreeInside, wc::ThreeInside, ThreeInside);
 wasm_candle_pattern!(WasmThreeOutside, wc::ThreeOutside, ThreeOutside);
 
+// ============================== Microstructure: Order Book ==============================
+//
+// Order-book indicators consume a depth snapshot rather than OHLCV. Each
+// `update(bidPx, bidSz, askPx, askSz)` takes four equal-length typed arrays for
+// one snapshot (bids best-first = descending price, asks best-first = ascending
+// price) — the streaming model that fits a live browser book feed. Batch over a
+// ragged depth history is provided by the Python and Node bindings.
+
+fn build_order_book(
+    bid_px: &[f64],
+    bid_sz: &[f64],
+    ask_px: &[f64],
+    ask_sz: &[f64],
+) -> Result<wc::OrderBook, JsError> {
+    if bid_px.len() != bid_sz.len() || ask_px.len() != ask_sz.len() {
+        return Err(JsError::new(
+            "bid/ask price and size arrays must be equal length",
+        ));
+    }
+    let bids = bid_px
+        .iter()
+        .zip(bid_sz)
+        .map(|(&p, &s)| wc::Level::new_unchecked(p, s))
+        .collect();
+    let asks = ask_px
+        .iter()
+        .zip(ask_sz)
+        .map(|(&p, &s)| wc::Level::new_unchecked(p, s))
+        .collect();
+    wc::OrderBook::new(bids, asks).map_err(map_err)
+}
+
+macro_rules! wasm_ob_indicator {
+    ($wasm:ident, $inner:ty, $js:ident) => {
+        #[wasm_bindgen(js_name = $js)]
+        pub struct $wasm {
+            inner: $inner,
+        }
+
+        impl Default for $wasm {
+            fn default() -> Self {
+                Self::new()
+            }
+        }
+
+        #[wasm_bindgen(js_class = $js)]
+        impl $wasm {
+            #[wasm_bindgen(constructor)]
+            pub fn new() -> $wasm {
+                Self {
+                    inner: <$inner>::new(),
+                }
+            }
+            pub fn update(
+                &mut self,
+                bid_px: &[f64],
+                bid_sz: &[f64],
+                ask_px: &[f64],
+                ask_sz: &[f64],
+            ) -> Result<Option<f64>, JsError> {
+                let book = build_order_book(bid_px, bid_sz, ask_px, ask_sz)?;
+                Ok(self.inner.update(book))
+            }
+            pub fn reset(&mut self) {
+                self.inner.reset();
+            }
+            #[wasm_bindgen(js_name = isReady)]
+            pub fn is_ready(&self) -> bool {
+                self.inner.is_ready()
+            }
+            #[wasm_bindgen(js_name = warmupPeriod)]
+            pub fn warmup_period(&self) -> usize {
+                self.inner.warmup_period()
+            }
+        }
+    };
+}
+
+wasm_ob_indicator!(
+    WasmOrderBookImbalanceTop1,
+    wc::OrderBookImbalanceTop1,
+    OrderBookImbalanceTop1
+);
+wasm_ob_indicator!(
+    WasmOrderBookImbalanceFull,
+    wc::OrderBookImbalanceFull,
+    OrderBookImbalanceFull
+);
+wasm_ob_indicator!(WasmMicroprice, wc::Microprice, Microprice);
+wasm_ob_indicator!(WasmQuotedSpread, wc::QuotedSpread, QuotedSpread);
+wasm_ob_indicator!(WasmDepthSlope, wc::DepthSlope, DepthSlope);
+
+// Top-N imbalance carries a `levels` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = OrderBookImbalanceTopN)]
+pub struct WasmOrderBookImbalanceTopN {
+    inner: wc::OrderBookImbalanceTopN,
+}
+
+#[wasm_bindgen(js_class = OrderBookImbalanceTopN)]
+impl WasmOrderBookImbalanceTopN {
+    #[wasm_bindgen(constructor)]
+    pub fn new(levels: usize) -> Result<WasmOrderBookImbalanceTopN, JsError> {
+        Ok(Self {
+            inner: wc::OrderBookImbalanceTopN::new(levels).map_err(map_err)?,
+        })
+    }
+    pub fn update(
+        &mut self,
+        bid_px: &[f64],
+        bid_sz: &[f64],
+        ask_px: &[f64],
+        ask_sz: &[f64],
+    ) -> Result<Option<f64>, JsError> {
+        let book = build_order_book(bid_px, bid_sz, ask_px, ask_sz)?;
+        Ok(self.inner.update(book))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ============================== Microstructure: Trade Flow ==============================
+//
+// Trade-flow indicators consume a trade tape rather than OHLCV. Each
+// `update(price, size, isBuy)` takes one trade (`isBuy=true` for a
+// buyer-initiated trade) — the streaming model for a live browser trade feed.
+
+fn build_trade(price: f64, size: f64, is_buy: bool) -> Result<wc::Trade, JsError> {
+    let side = if is_buy {
+        wc::Side::Buy
+    } else {
+        wc::Side::Sell
+    };
+    wc::Trade::new(price, size, side, 0).map_err(map_err)
+}
+
+macro_rules! wasm_trade_indicator {
+    ($wasm:ident, $inner:ty, $js:ident) => {
+        #[wasm_bindgen(js_name = $js)]
+        pub struct $wasm {
+            inner: $inner,
+        }
+
+        impl Default for $wasm {
+            fn default() -> Self {
+                Self::new()
+            }
+        }
+
+        #[wasm_bindgen(js_class = $js)]
+        impl $wasm {
+            #[wasm_bindgen(constructor)]
+            pub fn new() -> $wasm {
+                Self {
+                    inner: <$inner>::new(),
+                }
+            }
+            pub fn update(
+                &mut self,
+                price: f64,
+                size: f64,
+                is_buy: bool,
+            ) -> Result<Option<f64>, JsError> {
+                Ok(self.inner.update(build_trade(price, size, is_buy)?))
+            }
+            pub fn reset(&mut self) {
+                self.inner.reset();
+            }
+            #[wasm_bindgen(js_name = isReady)]
+            pub fn is_ready(&self) -> bool {
+                self.inner.is_ready()
+            }
+            #[wasm_bindgen(js_name = warmupPeriod)]
+            pub fn warmup_period(&self) -> usize {
+                self.inner.warmup_period()
+            }
+        }
+    };
+}
+
+wasm_trade_indicator!(WasmSignedVolume, wc::SignedVolume, SignedVolume);
+wasm_trade_indicator!(
+    WasmCumulativeVolumeDelta,
+    wc::CumulativeVolumeDelta,
+    CumulativeVolumeDelta
+);
+
+// Trade imbalance carries a `window` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = TradeImbalance)]
+pub struct WasmTradeImbalance {
+    inner: wc::TradeImbalance,
+}
+
+#[wasm_bindgen(js_class = TradeImbalance)]
+impl WasmTradeImbalance {
+    #[wasm_bindgen(constructor)]
+    pub fn new(window: usize) -> Result<WasmTradeImbalance, JsError> {
+        Ok(Self {
+            inner: wc::TradeImbalance::new(window).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ============================== Microstructure: Price Impact ==============================
+//
+// Price-impact indicators consume a trade paired with the mid prevailing at
+// execution. Each `update(price, size, isBuy, mid)` takes one such trade-quote
+// (`isBuy=true` for a buyer-initiated trade) — the streaming model for a live
+// browser trade feed. Batch over a tape is provided by the Python and Node
+// bindings.
+
+fn build_trade_quote(
+    price: f64,
+    size: f64,
+    is_buy: bool,
+    mid: f64,
+) -> Result<wc::TradeQuote, JsError> {
+    let trade = build_trade(price, size, is_buy)?;
+    wc::TradeQuote::new(trade, mid).map_err(map_err)
+}
+
+macro_rules! wasm_trade_quote_indicator {
+    ($wasm:ident, $inner:ty, $js:ident) => {
+        #[wasm_bindgen(js_name = $js)]
+        pub struct $wasm {
+            inner: $inner,
+        }
+
+        impl Default for $wasm {
+            fn default() -> Self {
+                Self::new()
+            }
+        }
+
+        #[wasm_bindgen(js_class = $js)]
+        impl $wasm {
+            #[wasm_bindgen(constructor)]
+            pub fn new() -> $wasm {
+                Self {
+                    inner: <$inner>::new(),
+                }
+            }
+            pub fn update(
+                &mut self,
+                price: f64,
+                size: f64,
+                is_buy: bool,
+                mid: f64,
+            ) -> Result<Option<f64>, JsError> {
+                Ok(self
+                    .inner
+                    .update(build_trade_quote(price, size, is_buy, mid)?))
+            }
+            pub fn reset(&mut self) {
+                self.inner.reset();
+            }
+            #[wasm_bindgen(js_name = isReady)]
+            pub fn is_ready(&self) -> bool {
+                self.inner.is_ready()
+            }
+            #[wasm_bindgen(js_name = warmupPeriod)]
+            pub fn warmup_period(&self) -> usize {
+                self.inner.warmup_period()
+            }
+        }
+    };
+}
+
+wasm_trade_quote_indicator!(WasmEffectiveSpread, wc::EffectiveSpread, EffectiveSpread);
+
+// Realized spread carries a `horizon` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = RealizedSpread)]
+pub struct WasmRealizedSpread {
+    inner: wc::RealizedSpread,
+}
+
+#[wasm_bindgen(js_class = RealizedSpread)]
+impl WasmRealizedSpread {
+    #[wasm_bindgen(constructor)]
+    pub fn new(horizon: usize) -> Result<WasmRealizedSpread, JsError> {
+        Ok(Self {
+            inner: wc::RealizedSpread::new(horizon).map_err(map_err)?,
+        })
+    }
+    pub fn update(
+        &mut self,
+        price: f64,
+        size: f64,
+        is_buy: bool,
+        mid: f64,
+    ) -> Result<Option<f64>, JsError> {
+        Ok(self
+            .inner
+            .update(build_trade_quote(price, size, is_buy, mid)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// Kyle's lambda carries a `window` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = KylesLambda)]
+pub struct WasmKylesLambda {
+    inner: wc::KylesLambda,
+}
+
+#[wasm_bindgen(js_class = KylesLambda)]
+impl WasmKylesLambda {
+    #[wasm_bindgen(constructor)]
+    pub fn new(window: usize) -> Result<WasmKylesLambda, JsError> {
+        Ok(Self {
+            inner: wc::KylesLambda::new(window).map_err(map_err)?,
+        })
+    }
+    pub fn update(
+        &mut self,
+        price: f64,
+        size: f64,
+        is_buy: bool,
+        mid: f64,
+    ) -> Result<Option<f64>, JsError> {
+        Ok(self
+            .inner
+            .update(build_trade_quote(price, size, is_buy, mid)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ============================== Microstructure: Footprint ==============================
+//
+// Footprint is a multi-output, variable-length indicator. Each `update(price,
+// size, isBuy)` returns the full bar footprint accumulated since the last
+// `reset()` as an array of `{ price, bidVol, askVol }` objects (sorted ascending
+// by price) — the streaming model for a live browser trade feed.
+
+#[wasm_bindgen(js_name = Footprint)]
+pub struct WasmFootprint {
+    inner: wc::Footprint,
+}
+
+#[wasm_bindgen(js_class = Footprint)]
+impl WasmFootprint {
+    #[wasm_bindgen(constructor)]
+    pub fn new(tick_size: f64) -> Result<WasmFootprint, JsError> {
+        Ok(Self {
+            inner: wc::Footprint::new(tick_size).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> Result<JsValue, JsError> {
+        let out = self
+            .inner
+            .update(build_trade(price, size, is_buy)?)
+            .expect("footprint emits on every trade");
+        let levels = Array::new();
+        for level in &out.levels {
+            let obj = Object::new();
+            Reflect::set(&obj, &"price".into(), &level.price.into()).ok();
+            Reflect::set(&obj, &"bidVol".into(), &level.bid_vol.into()).ok();
+            Reflect::set(&obj, &"askVol".into(), &level.ask_vol.into()).ok();
+            levels.push(&obj);
+        }
+        Ok(levels.into())
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -6139,6 +6841,12 @@ mod tests {
     fn close_enough(a: f64, b: f64) -> bool {
         if a.is_nan() {
             b.is_nan()
+        } else if a == b {
+            // Exact equality, including matching infinities (e.g. ProfitFactor
+            // with no losing trades is +inf in both the streaming and batch
+            // passes). `(inf - inf).abs()` is NaN, so the tolerance check below
+            // would otherwise reject two equal infinities.
+            true
         } else {
             (a - b).abs() < 1e-9
         }
@@ -6630,6 +7338,146 @@ mod tests {
             "ready after 5 finite inputs even with prior NaNs"
         );
     }
+
+    // Streaming `update` must reproduce `batch` value-for-value for every scalar
+    // indicator — the core O(1) state-machine invariant. Each entry builds a
+    // fresh instance for the batch pass and another for the streaming pass. The
+    // constructor arguments mirror the (CI-passing) Node `indicators.test.js`
+    // factories, so they are known-valid.
+    macro_rules! assert_scalar_stream_eq {
+        ($ctor:expr, $prices:expr) => {{
+            let prices: &[f64] = $prices;
+            let batch = { $ctor }.batch(prices);
+            let mut streaming = { $ctor };
+            for (i, &p) in prices.iter().enumerate() {
+                let b = batch.get_index(i as u32);
+                match streaming.update(p) {
+                    Some(v) => assert!(
+                        close_enough(v, b),
+                        "{} streaming != batch at {i}: {v} vs {b}",
+                        stringify!($ctor)
+                    ),
+                    None => assert!(
+                        b.is_nan(),
+                        "{} expected NaN warmup at {i}",
+                        stringify!($ctor)
+                    ),
+                }
+            }
+        }};
+    }
+
+    #[allow(clippy::too_many_lines)]
+    #[wasm_bindgen_test]
+    fn scalar_streaming_matches_batch_broad() {
+        let prices: Vec<f64> = (0..120)
+            .map(|i| {
+                let t = f64::from(i);
+                100.0 + (t * 0.2).sin() * 10.0 + t * 0.1
+            })
+            .collect();
+        let p = prices.as_slice();
+
+        // Moving averages.
+        assert_scalar_stream_eq!(WasmSma::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmWma::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmDema::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmTema::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmHma::new(9).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmSmma::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmTrima::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmZlema::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmT3::new(5, 0.7).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmAlma::new(9, 0.85, 6.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmMcGinleyDynamic::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmFrama::new(16).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmVidya::new(14, 9).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmJma::new(14, 0.0, 2).expect("valid"), p);
+
+        // Momentum / oscillators.
+        assert_scalar_stream_eq!(WasmRsi::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmRoc::new(12).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmTrix::new(9).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmMom::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCmo::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmTsi::new(25, 13).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmPmo::new(35, 20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmTii::new(20, 10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmStochRsi::new(14, 14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmDpo::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmPpo::new(12, 26).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmApo::new(12, 26).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCfo::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmStc::new(23, 50, 10, 0.5).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCoppock::new(14, 11, 10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmLaguerreRsi::new(0.5).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmConnorsRsi::new(3, 2, 100).expect("valid"), p);
+
+        // Volatility / statistics / regression.
+        assert_scalar_stream_eq!(WasmStdDev::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmUlcerIndex::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmHistoricalVolatility::new(20, 252).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmBollingerBandwidth::new(20, 2.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmPercentB::new(20, 2.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmLinearRegression::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmLinRegSlope::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmLinRegAngle::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmVerticalHorizontalFilter::new(28).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmZScore::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmVariance::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCoefficientOfVariation::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmSkewness::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmKurtosis::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmStandardError::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmDetrendedStdDev::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmRSquared::new(14).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmMedianAbsoluteDeviation::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmAutocorrelation::new(20, 1).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmHurstExponent::new(40, 4).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmRviVolatility::new(10).expect("valid"), p);
+
+        // Ehlers / cycle.
+        assert_scalar_stream_eq!(WasmSuperSmoother::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmFisherTransform::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmInverseFisherTransform::new(1.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmDecycler::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmDecyclerOscillator::new(10, 30).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmRoofingFilter::new(10, 48).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCenterOfGravity::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmCyberneticCycle::new(10).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmInstantaneousTrendline::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmEhlersStochastic::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(
+            WasmEmpiricalModeDecomposition::new(20, 0.5).expect("valid"),
+            p
+        );
+        assert_scalar_stream_eq!(WasmFama::new(0.5, 0.05).expect("valid"), p);
+
+        // Risk / performance (scalar f64 input).
+        assert_scalar_stream_eq!(WasmCalmarRatio::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmMaxDrawdown::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmAverageDrawdown::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmPainIndex::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmProfitFactor::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmGainLossRatio::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmKellyCriterion::new(20).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmSharpeRatio::new(20, 0.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmSortinoRatio::new(20, 0.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmOmegaRatio::new(20, 0.0).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmValueAtRisk::new(20, 0.95).expect("valid"), p);
+        assert_scalar_stream_eq!(WasmConditionalValueAtRisk::new(20, 0.95).expect("valid"), p);
+    }
+
+    // Additional invalid-constructor coverage. These wrap the same fallible core
+    // `new` as the Python / Node bindings, where the equivalent calls are
+    // confirmed to error.
+    #[wasm_bindgen_test]
+    fn additional_invalid_constructors_are_rejected() {
+        assert!(WasmDecyclerOscillator::new(30, 10).is_err()); // short cutoff >= long
+        assert!(WasmRoofingFilter::new(48, 10).is_err()); // lowpass >= highpass
+        assert!(WasmInverseFisherTransform::new(0.0).is_err()); // zero scale
+        assert!(WasmEmpiricalModeDecomposition::new(20, 0.0).is_err()); // zero fraction
+    }
 }
 // ============================== Family 15: Risk / Performance ==============================
 

crates/wickra-core/Cargo.toml

@@ -5,7 +5,7 @@ version.workspace = true
 authors.workspace = true
 edition.workspace = true
 rust-version.workspace = true
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

crates/wickra-core/src/error.rs

@@ -31,6 +31,18 @@ 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 },
 }
 
 /// Convenience alias for `Result<T, wickra_core::Error>`.

crates/wickra-core/src/indicators/cointegration.rs

@@ -0,0 +1,446 @@
+//! Cointegration — rolling Engle–Granger hedge ratio plus an ADF stationarity test.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Output of [`Cointegration`].
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct CointegrationOutput {
+    /// Engle–Granger hedge ratio `β`: the rolling OLS slope of `a` on `b`.
+    pub hedge_ratio: f64,
+    /// The current spread (regression residual) `a − (α + β·b)`.
+    pub spread: f64,
+    /// Augmented Dickey–Fuller `t`-statistic on the spread. **More negative**
+    /// means more strongly mean-reverting (cointegrated); compare against the
+    /// usual ADF/MacKinnon critical values (e.g. roughly `−2.9` at 5%). `0`
+    /// when the test is undefined (a degenerate, zero-variance spread).
+    pub adf_stat: f64,
+}
+
+/// Rolling cointegration test for a pair of assets (Engle–Granger two-step).
+///
+/// Each `update` receives one `(a, b)` pair (price levels, or log-levels if you
+/// prefer). Over the trailing window of `period` pairs the indicator:
+///
+/// 1. fits the **hedge ratio** `β` (and intercept `α`) by ordinary least
+///    squares of `a` on `b`, and forms the **spread** `eₜ = aₜ − (α + β·bₜ)`;
+/// 2. runs an **augmented Dickey–Fuller** test (no constant, no trend, with
+///    `adf_lags` lagged differences) on the spread series and reports its
+///    `t`-statistic.
+///
+/// A strongly negative ADF statistic means the spread reverts to its mean — the
+/// pair is cointegrated and the spread is tradeable. A statistic near zero
+/// means the spread wanders like a random walk (no cointegration). This is the
+/// classic pairs-trading screen: `β` tells you the hedge size, the spread is
+/// what you trade, and the ADF statistic tells you whether it is worth trading.
+///
+/// Each `update` is `O(period + adf_lags³)`: the hedge ratio is maintained from
+/// running sums, while the spread series and the small ADF regression are
+/// recomputed over the window — both bounded by the fixed parameters, not the
+/// series length.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Cointegration, Indicator};
+///
+/// let mut c = Cointegration::new(30, 1).unwrap();
+/// let mut last = None;
+/// for t in 0..60 {
+///     let b = 100.0 + f64::from(t);
+///     // `a` tracks 2·b with a small mean-reverting wobble ⇒ cointegrated.
+///     let a = 2.0 * b + 5.0 + 0.5 * (f64::from(t) * 0.7).sin();
+///     last = c.update((a, b));
+/// }
+/// let out = last.unwrap();
+/// assert!((out.hedge_ratio - 2.0).abs() < 0.1);
+/// assert!(out.adf_stat < 0.0); // mean-reverting spread
+/// ```
+#[derive(Debug, Clone)]
+pub struct Cointegration {
+    period: usize,
+    adf_lags: usize,
+    window: VecDeque<(f64, f64)>,
+    sum_a: f64,
+    sum_b: f64,
+    sum_bb: f64,
+    sum_ab: f64,
+}
+
+impl Cointegration {
+    /// Construct a new rolling cointegration test.
+    ///
+    /// `period` is the look-back window; `adf_lags` is the number of lagged
+    /// differences in the augmented Dickey–Fuller regression (`0` is the plain
+    /// Dickey–Fuller test).
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `period < 2·adf_lags + 4`, which is
+    /// the smallest window that leaves the ADF regression at least one degree
+    /// of freedom.
+    pub fn new(period: usize, adf_lags: usize) -> Result<Self> {
+        let min_period = 2 * adf_lags + 4;
+        if period < min_period {
+            return Err(Error::InvalidPeriod {
+                message: "cointegration needs period >= 2*adf_lags + 4",
+            });
+        }
+        Ok(Self {
+            period,
+            adf_lags,
+            window: VecDeque::with_capacity(period),
+            sum_a: 0.0,
+            sum_b: 0.0,
+            sum_bb: 0.0,
+            sum_ab: 0.0,
+        })
+    }
+
+    /// Look-back window length.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Number of lagged differences in the ADF regression.
+    pub const fn adf_lags(&self) -> usize {
+        self.adf_lags
+    }
+}
+
+impl Indicator for Cointegration {
+    /// `(a, b)` price pair.
+    type Input = (f64, f64);
+    type Output = CointegrationOutput;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<CointegrationOutput> {
+        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 (hedge_ratio, intercept) = if var_b == 0.0 {
+            // A flat `b` window has no defined slope; fall back to a level shift.
+            (0.0, mean_a)
+        } else {
+            let cov = self.sum_ab / n - mean_a * mean_b;
+            let beta = cov / var_b;
+            (beta, mean_a - beta * mean_b)
+        };
+        // Build the spread (residual) series over the window, oldest → newest.
+        let spreads: Vec<f64> = self
+            .window
+            .iter()
+            .map(|&(ai, bi)| ai - (intercept + hedge_ratio * bi))
+            .collect();
+        let spread = *spreads.last().expect("window is full");
+        let adf_stat = adf_no_constant(&spreads, self.adf_lags);
+        Some(CointegrationOutput {
+            hedge_ratio,
+            spread,
+            adf_stat,
+        })
+    }
+
+    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 {
+        "Cointegration"
+    }
+}
+
+/// Solve the linear system `mat·x = rhs` for a small square system by Gaussian
+/// elimination, returning `None` if the matrix is (numerically) singular.
+///
+/// `mat` is row-major and consumed; `rhs` is the right-hand side.
+fn solve(mut mat: Vec<Vec<f64>>, mut rhs: Vec<f64>) -> Option<Vec<f64>> {
+    let dim = rhs.len();
+    for col in 0..dim {
+        let pivot = mat[col][col];
+        if pivot.abs() < 1e-12 {
+            return None;
+        }
+        let pivot_row = mat[col].clone();
+        for row in (col + 1)..dim {
+            let factor = mat[row][col] / pivot;
+            for (cell, &above) in mat[row].iter_mut().zip(&pivot_row).skip(col) {
+                *cell -= factor * above;
+            }
+            rhs[row] -= factor * rhs[col];
+        }
+    }
+    let mut sol = vec![0.0; dim];
+    for row in (0..dim).rev() {
+        let known: f64 = mat[row]
+            .iter()
+            .zip(&sol)
+            .skip(row + 1)
+            .map(|(coeff, value)| coeff * value)
+            .sum();
+        sol[row] = (rhs[row] - known) / mat[row][row];
+    }
+    Some(sol)
+}
+
+/// Augmented Dickey–Fuller `t`-statistic on `series`, with `lags` lagged
+/// differences and **no** constant or trend term (the Engle–Granger residual
+/// form). Returns `0.0` when the regression is degenerate.
+///
+/// The regression is `Δeₜ = ρ·eₜ₋₁ + Σ γᵢ·Δeₜ₋ᵢ + εₜ`; the reported statistic
+/// is `ρ̂ / se(ρ̂)`.
+fn adf_no_constant(series: &[f64], lags: usize) -> f64 {
+    let len = series.len();
+    let num_reg = lags + 1; // regressors: eₜ₋₁ plus `lags` lagged differences
+    let first = lags + 1; // first usable observation index
+    if len <= first {
+        return 0.0;
+    }
+    let num_obs = len - first;
+    if num_obs <= num_reg {
+        return 0.0; // need at least one residual degree of freedom
+    }
+    let regressors = |idx: usize| -> Vec<f64> {
+        let mut row = vec![0.0; num_reg];
+        row[0] = series[idx - 1];
+        for lag in 1..=lags {
+            row[lag] = series[idx - lag] - series[idx - lag - 1];
+        }
+        row
+    };
+    let mut xtx = vec![vec![0.0; num_reg]; num_reg];
+    let mut xty = vec![0.0; num_reg];
+    for idx in first..len {
+        let diff = series[idx] - series[idx - 1];
+        let row = regressors(idx);
+        for (ri, &left) in row.iter().enumerate() {
+            xty[ri] += left * diff;
+            for (ci, &right) in row.iter().enumerate() {
+                xtx[ri][ci] += left * right;
+            }
+        }
+    }
+    let Some(theta) = solve(xtx.clone(), xty) else {
+        return 0.0;
+    };
+    let rho = theta[0];
+    let mut rss = 0.0;
+    for idx in first..len {
+        let diff = series[idx] - series[idx - 1];
+        let pred: f64 = regressors(idx)
+            .iter()
+            .zip(&theta)
+            .map(|(coeff, value)| coeff * value)
+            .sum();
+        let resid = diff - pred;
+        rss += resid * resid;
+    }
+    let dof = (num_obs - num_reg) as f64;
+    let sigma2 = rss / dof;
+    // (XᵀX)⁻¹₀₀ from solving XᵀX·x = e₀. `xtx` is the same matrix the first
+    // solve already factored successfully, so this one cannot be singular.
+    let mut unit = vec![0.0; num_reg];
+    unit[0] = 1.0;
+    let inverse = solve(xtx, unit).expect("xtx is non-singular: the coefficient solve succeeded");
+    let var_rho = sigma2 * inverse[0];
+    if var_rho <= 0.0 {
+        return 0.0;
+    }
+    rho / var_rho.sqrt()
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_too_small_period() {
+        // period must be >= 2*lags + 4.
+        assert!(Cointegration::new(3, 0).is_err()); // needs >= 4
+        assert!(Cointegration::new(4, 0).is_ok());
+        assert!(Cointegration::new(5, 1).is_err()); // needs >= 6
+        assert!(Cointegration::new(6, 1).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let c = Cointegration::new(30, 2).unwrap();
+        assert_eq!(c.period(), 30);
+        assert_eq!(c.adf_lags(), 2);
+        assert_eq!(c.warmup_period(), 30);
+        assert_eq!(c.name(), "Cointegration");
+    }
+
+    #[test]
+    fn adf_guards_and_degenerate_spread() {
+        // Series too short for any observation ⇒ 0.
+        assert_eq!(adf_no_constant(&[1.0], 1), 0.0);
+        // Long enough but too few degrees of freedom ⇒ 0.
+        assert_eq!(adf_no_constant(&[1.0, 2.0, 3.0], 1), 0.0);
+        // A perfect deterministic AR(1) spread (eₜ = 0.5·eₜ₋₁) is fit exactly,
+        // so the residual variance — and hence the t-statistic — is 0.
+        let geom: Vec<f64> = (0..8).map(|t| 0.5_f64.powi(t)).collect();
+        assert_eq!(adf_no_constant(&geom, 0), 0.0);
+    }
+
+    #[test]
+    fn recovers_hedge_ratio() {
+        // a = 2·b + 5 + small wobble ⇒ β ≈ 2.
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                let a = 2.0 * b + 5.0 + 0.4 * (f64::from(t) * 0.9).sin();
+                (a, b)
+            })
+            .collect();
+        let out = Cointegration::new(30, 1)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(
+            (out.hedge_ratio - 2.0).abs() < 0.1,
+            "beta {}",
+            out.hedge_ratio
+        );
+    }
+
+    #[test]
+    fn stationary_spread_is_strongly_negative() {
+        // A clean mean-reverting (sinusoidal) spread ⇒ very negative ADF.
+        let pairs: Vec<(f64, f64)> = (0..80)
+            .map(|t| {
+                let b = 50.0 + 0.5 * f64::from(t);
+                let a = 2.0 * b + 1.0 + 0.5 * (f64::from(t) * 0.6).sin();
+                (a, b)
+            })
+            .collect();
+        let out = Cointegration::new(40, 1)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(out.adf_stat < -2.0, "adf {}", out.adf_stat);
+    }
+
+    #[test]
+    fn perfect_cointegration_has_zero_spread_and_defined_ratio() {
+        // a = 2·b + 5 exactly ⇒ residuals all zero ⇒ ADF degenerate ⇒ 0.
+        let pairs: Vec<(f64, f64)> = (0..40)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                (2.0 * b + 5.0, b)
+            })
+            .collect();
+        let out = Cointegration::new(20, 1)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(out.hedge_ratio, 2.0, epsilon = 1e-9);
+        assert_relative_eq!(out.spread, 0.0, epsilon = 1e-6);
+        assert_relative_eq!(out.adf_stat, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn flat_b_falls_back_to_level() {
+        // Constant b ⇒ no slope ⇒ hedge ratio 0, spread = a − mean(a).
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|t| (10.0 + 0.3 * (f64::from(t) * 0.5).sin(), 7.0))
+            .collect();
+        let out = Cointegration::new(10, 0)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(out.hedge_ratio, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn plain_dickey_fuller_lags_zero() {
+        // Exercise the lags = 0 path (1×1 ADF system).
+        let pairs: Vec<(f64, f64)> = (0..40)
+            .map(|t| {
+                let b = 20.0 + 0.4 * f64::from(t);
+                let a = 1.5 * b + 0.6 * (f64::from(t) * 0.7).sin();
+                (a, b)
+            })
+            .collect();
+        let out = Cointegration::new(20, 0)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!((out.hedge_ratio - 1.5).abs() < 0.1);
+        assert!(out.adf_stat < 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut c = Cointegration::new(10, 1).unwrap();
+        for t in 0..20 {
+            let b = 100.0 + f64::from(t);
+            c.update((2.0 * b + (f64::from(t) * 0.5).sin(), b));
+        }
+        assert!(c.is_ready());
+        c.reset();
+        assert!(!c.is_ready());
+        assert_eq!(c.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..80)
+            .map(|t| {
+                let b = 30.0 + 0.7 * f64::from(t);
+                let a = 1.8 * b + 2.0 + 0.5 * (f64::from(t) * 0.4).sin();
+                (a, b)
+            })
+            .collect();
+        let batch = Cointegration::new(25, 2).unwrap().batch(&pairs);
+        let mut c = Cointegration::new(25, 2).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| c.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/cvd.rs

@@ -0,0 +1,127 @@
+//! Cumulative Volume Delta — running sum of signed trade volume.
+
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// Cumulative Volume Delta (CVD) — the running sum of [signed volume].
+///
+/// ```text
+/// CVDₜ = CVDₜ₋₁ + sizeₜ · (+1 if buy, −1 if sell)
+/// ```
+///
+/// CVD is an unbounded running total: a rising line signals net buying pressure
+/// over the session, a falling line net selling. Divergence between CVD and
+/// price is a classic absorption / exhaustion signal. Call [`reset`] at the
+/// start of each session to re-anchor the cumulative total at zero.
+///
+/// `Input = Trade`, `Output = f64`. Ready after the first trade.
+///
+/// [signed volume]: crate::SignedVolume
+/// [`reset`]: crate::Indicator::reset
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{CumulativeVolumeDelta, Indicator, Side, Trade};
+///
+/// let mut cvd = CumulativeVolumeDelta::new();
+/// assert_eq!(cvd.update(Trade::new(100.0, 5.0, Side::Buy, 0).unwrap()), Some(5.0));
+/// assert_eq!(cvd.update(Trade::new(100.0, 2.0, Side::Sell, 1).unwrap()), Some(3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct CumulativeVolumeDelta {
+    cumulative: f64,
+    has_emitted: bool,
+}
+
+impl CumulativeVolumeDelta {
+    /// Construct a new CVD indicator with a zero running total.
+    pub const fn new() -> Self {
+        Self {
+            cumulative: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for CumulativeVolumeDelta {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        self.has_emitted = true;
+        self.cumulative += trade.size * trade.side.sign();
+        Some(self.cumulative)
+    }
+
+    fn reset(&mut self) {
+        self.cumulative = 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 {
+        "CumulativeVolumeDelta"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+
+    fn trade(size: f64, side: Side, ts: i64) -> Trade {
+        Trade::new(100.0, size, side, ts).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let cvd = CumulativeVolumeDelta::new();
+        assert_eq!(cvd.name(), "CumulativeVolumeDelta");
+        assert_eq!(cvd.warmup_period(), 1);
+        assert!(!cvd.is_ready());
+    }
+
+    #[test]
+    fn accumulates_signed_volume() {
+        let mut cvd = CumulativeVolumeDelta::new();
+        assert_eq!(cvd.update(trade(5.0, Side::Buy, 0)), Some(5.0));
+        assert_eq!(cvd.update(trade(2.0, Side::Sell, 1)), Some(3.0));
+        assert_eq!(cvd.update(trade(4.0, Side::Sell, 2)), Some(-1.0));
+        assert!(cvd.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..20)
+            .map(|i| {
+                let side = if i % 3 == 0 { Side::Sell } else { Side::Buy };
+                trade(1.0 + (i % 4) as f64, side, i)
+            })
+            .collect();
+        let mut a = CumulativeVolumeDelta::new();
+        let mut b = CumulativeVolumeDelta::new();
+        assert_eq!(
+            a.batch(&trades),
+            trades.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_re_anchors_at_zero() {
+        let mut cvd = CumulativeVolumeDelta::new();
+        cvd.update(trade(5.0, Side::Buy, 0));
+        cvd.reset();
+        assert!(!cvd.is_ready());
+        // After reset the running total starts again from zero.
+        assert_eq!(cvd.update(trade(2.0, Side::Buy, 1)), Some(2.0));
+    }
+}

crates/wickra-core/src/indicators/depth_slope.rs

@@ -0,0 +1,258 @@
+//! Depth Slope — how fast resting liquidity accumulates away from the mid.
+
+use crate::microstructure::{Level, OrderBook};
+use crate::traits::Indicator;
+
+/// Ordinary-least-squares slope of cumulative resting size against distance
+/// from the mid, over the levels of one book side.
+///
+/// `signed_distance` is `+1.0` for the ask side (price above the mid) and
+/// `−1.0` for the bid side (price below the mid), so the regressor `x` —
+/// distance from the mid — is non-negative on both sides. The response `y` is
+/// the cumulative size walking outward from the touch. Returns `0.0` for a
+/// degenerate fit where every level sits at the same distance (zero variance in
+/// `x`).
+fn cumulative_slope(levels: &[Level], mid: f64, signed_distance: f64) -> f64 {
+    let count = levels.len() as f64;
+    let mut cumulative = 0.0;
+    let mut sum_x = 0.0;
+    let mut sum_y = 0.0;
+    let mut sum_xy = 0.0;
+    let mut sum_xx = 0.0;
+    for level in levels {
+        let x = signed_distance * (level.price - mid);
+        cumulative += level.size;
+        sum_x += x;
+        sum_y += cumulative;
+        sum_xy += x * cumulative;
+        sum_xx += x * x;
+    }
+    let denom = count * sum_xx - sum_x * sum_x;
+    if denom == 0.0 {
+        return 0.0;
+    }
+    (count * sum_xy - sum_x * sum_y) / denom
+}
+
+/// Depth Slope — the average rate at which cumulative resting size grows with
+/// distance from the mid, across the bid and ask sides of the book.
+///
+/// For each side the indicator runs an ordinary-least-squares regression of
+/// cumulative size (walking outward from the touch) on the level's distance
+/// from the mid, then reports the mean of the two slopes:
+///
+/// ```text
+/// slope_side = OLS slope of (|priceᵢ − mid|, Σ_{j≤i} sizeⱼ)
+/// depthSlope = (slope_bid + slope_ask) / 2
+/// ```
+///
+/// Because the response is *cumulative* size it never decreases with distance,
+/// so the slope is non-negative: it is a magnitude, not a direction. A large
+/// slope means cumulative liquidity builds quickly away from the touch — a deep
+/// book that absorbs large orders with little walking; a small slope is a thin,
+/// shallow book. A book whose size is concentrated at the touch and thins out
+/// behind it (a fragile book) reads a *smaller* slope than one of equal total
+/// depth that thickens with distance.
+///
+/// A side with fewer than two levels carries no slope, so the indicator returns
+/// `0.0` whenever either side has fewer than two levels (including an empty
+/// book).
+///
+/// `Input = OrderBook`, `Output = f64`. Stateless; ready after the first
+/// snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DepthSlope, Indicator, Level, OrderBook};
+///
+/// // Both sides thicken linearly away from the mid (sizes 1, 2, 3 …).
+/// let book = OrderBook::new(
+///     vec![Level::new(99.0, 1.0).unwrap(), Level::new(98.0, 2.0).unwrap()],
+///     vec![Level::new(101.0, 1.0).unwrap(), Level::new(102.0, 2.0).unwrap()],
+/// )
+/// .unwrap();
+/// let mut ds = DepthSlope::new();
+/// assert!(ds.update(book).unwrap() > 0.0);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct DepthSlope {
+    has_emitted: bool,
+}
+
+impl DepthSlope {
+    /// Construct a new depth-slope indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for DepthSlope {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let Some(mid) = book.mid() else {
+            return Some(0.0);
+        };
+        if book.bids.len() < 2 || book.asks.len() < 2 {
+            return Some(0.0);
+        }
+        let bid_slope = cumulative_slope(&book.bids, mid, -1.0);
+        let ask_slope = cumulative_slope(&book.asks, mid, 1.0);
+        Some(f64::midpoint(bid_slope, ask_slope))
+    }
+
+    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 {
+        "DepthSlope"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ds = DepthSlope::new();
+        assert_eq!(ds.name(), "DepthSlope");
+        assert_eq!(ds.warmup_period(), 1);
+        assert!(!ds.is_ready());
+    }
+
+    #[test]
+    fn thickening_book_has_positive_slope() {
+        let mut ds = DepthSlope::new();
+        let out = ds
+            .update(book(
+                &[(99.0, 1.0), (98.0, 2.0), (97.0, 3.0)],
+                &[(101.0, 1.0), (102.0, 2.0), (103.0, 3.0)],
+            ))
+            .unwrap();
+        assert!(out > 0.0);
+        assert!(ds.is_ready());
+    }
+
+    #[test]
+    fn front_loaded_book_has_smaller_slope_than_back_loaded() {
+        // Same total depth (6 per side), but one book thickens away from the
+        // touch and the other thins. Cumulative slope is non-negative for both;
+        // the back-loaded book accumulates faster, so its slope is larger.
+        let mut back = DepthSlope::new();
+        let back_slope = back
+            .update(book(
+                &[(99.0, 1.0), (98.0, 2.0), (97.0, 3.0)],
+                &[(101.0, 1.0), (102.0, 2.0), (103.0, 3.0)],
+            ))
+            .unwrap();
+        let mut front = DepthSlope::new();
+        let front_slope = front
+            .update(book(
+                &[(99.0, 3.0), (98.0, 2.0), (97.0, 1.0)],
+                &[(101.0, 3.0), (102.0, 2.0), (103.0, 1.0)],
+            ))
+            .unwrap();
+        assert!(front_slope >= 0.0);
+        assert!(back_slope > front_slope);
+    }
+
+    #[test]
+    fn known_slope_value() {
+        // Symmetric book, each side: distances 1, 2; cumulative sizes 1, 3.
+        // OLS slope of (1->1, 2->3) = 2. Mean of two equal sides = 2.
+        let mut ds = DepthSlope::new();
+        let out = ds
+            .update(book(
+                &[(99.0, 1.0), (98.0, 2.0)],
+                &[(101.0, 1.0), (102.0, 2.0)],
+            ))
+            .unwrap();
+        assert!((out - 2.0).abs() < 1e-9);
+    }
+
+    #[test]
+    fn single_level_side_is_zero() {
+        let mut ds = DepthSlope::new();
+        // Bid side has only one level -> no slope -> 0.
+        assert_eq!(
+            ds.update(book(&[(100.0, 1.0)], &[(101.0, 1.0), (102.0, 1.0)])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn empty_book_is_zero() {
+        let mut ds = DepthSlope::new();
+        assert_eq!(
+            ds.update(OrderBook::new_unchecked(vec![], vec![])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn degenerate_distance_slope_is_zero() {
+        // Two levels at the same distance from mid carry zero x-variance.
+        let levels = [
+            Level::new_unchecked(100.0, 1.0),
+            Level::new_unchecked(100.0, 2.0),
+        ];
+        assert_eq!(cumulative_slope(&levels, 100.0, 1.0), 0.0);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let extra = f64::from(i % 4);
+                book(
+                    &[(99.0, 1.0 + extra), (98.0, 2.0)],
+                    &[(101.0, 1.0), (102.0, 2.0 + extra)],
+                )
+            })
+            .collect();
+        let mut a = DepthSlope::new();
+        let mut b = DepthSlope::new();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ds = DepthSlope::new();
+        ds.update(book(
+            &[(99.0, 1.0), (98.0, 2.0)],
+            &[(101.0, 1.0), (102.0, 2.0)],
+        ));
+        assert!(ds.is_ready());
+        ds.reset();
+        assert!(!ds.is_ready());
+    }
+}

crates/wickra-core/src/indicators/doji.rs

@@ -16,22 +16,44 @@ use crate::traits::Indicator;
 /// doji  = body <= body_threshold * range
 /// ```
 ///
-/// The output is `+1.0` when a Doji is detected and `0.0` otherwise. Doji is
-/// directionless — no `−1.0` is emitted. Pattern-shape check only — no trend
-/// filter is applied; combine with a trend indicator for actionable signals.
+/// # Signed ±1 encoding
+///
+/// By default the output is `+1.0` when a Doji is detected and `0.0`
+/// otherwise — a direction-less detection flag. For a drop-in machine-learning
+/// feature where every candlestick pattern shares the same sign convention
+/// (`+1.0` bullish, `−1.0` bearish, `0.0` none), switch the detector into
+/// signed mode with [`Doji::signed`]. A detected Doji is then classified by
+/// where its (negligible) body sits within the bar's range:
+///
+/// ```text
+/// pos = (0.5 * (open + close) − low) / (high − low)
+/// pos > 2/3  ->  +1.0   dragonfly  (long lower shadow, bullish)
+/// pos < 1/3  ->  −1.0   gravestone (long upper shadow, bearish)
+/// else       ->   0.0   long-legged / standard (neutral)
+/// ```
+///
+/// Pattern-shape check only — no trend filter is applied; combine with a trend
+/// indicator for actionable signals.
 ///
 /// # Example
 ///
 /// ```
 /// use wickra_core::{Candle, Doji, Indicator};
 ///
+/// // Default: direction-less detection flag.
 /// let mut indicator = Doji::default();
 /// let candle = Candle::new(10.0, 11.0, 9.0, 10.0, 1.0, 0).unwrap();
 /// assert_eq!(indicator.update(candle), Some(1.0));
+///
+/// // Signed: a dragonfly Doji (body at the top, long lower shadow) is bullish.
+/// let mut signed = Doji::new().signed();
+/// let dragonfly = Candle::new(10.0, 10.05, 6.0, 10.0, 1.0, 0).unwrap();
+/// assert_eq!(signed.update(dragonfly), Some(1.0));
 /// ```
 #[derive(Debug, Clone)]
 pub struct Doji {
     body_threshold: f64,
+    signed: bool,
     has_emitted: bool,
 }
 
@@ -46,6 +68,7 @@ impl Doji {
     pub const fn new() -> Self {
         Self {
             body_threshold: 0.1,
+            signed: false,
             has_emitted: false,
         }
     }
@@ -61,14 +84,32 @@ impl Doji {
         }
         Ok(Self {
             body_threshold,
+            signed: false,
             has_emitted: false,
         })
     }
 
+    /// Switch to the signed dragonfly / gravestone encoding (consuming builder).
+    ///
+    /// In signed mode a detected Doji emits `+1.0` (dragonfly, bullish),
+    /// `−1.0` (gravestone, bearish) or `0.0` (long-legged / neutral) instead of
+    /// the default direction-less `+1.0` detection flag. See the type-level
+    /// docs for the exact classification rule.
+    #[must_use]
+    pub fn signed(mut self) -> Self {
+        self.signed = true;
+        self
+    }
+
     /// Configured body / range threshold.
     pub fn body_threshold(&self) -> f64 {
         self.body_threshold
     }
+
+    /// Whether this detector emits the signed dragonfly / gravestone encoding.
+    pub fn is_signed(&self) -> bool {
+        self.signed
+    }
 }
 
 impl Indicator for Doji {
@@ -82,11 +123,23 @@ impl Indicator for Doji {
             return Some(0.0);
         }
         let body = (candle.close - candle.open).abs();
-        Some(if body <= self.body_threshold * range {
-            1.0
+        if body > self.body_threshold * range {
+            return Some(0.0);
+        }
+        if !self.signed {
+            return Some(1.0);
+        }
+        // Signed mode: classify the Doji by where its (negligible) body sits
+        // within the high–low range.
+        let body_mid = 0.5 * (candle.open + candle.close);
+        let pos = (body_mid - candle.low) / range;
+        if pos > 2.0 / 3.0 {
+            Some(1.0)
+        } else if pos < 1.0 / 3.0 {
+            Some(-1.0)
         } else {
-            0.0
-        })
+            Some(0.0)
+        }
     }
 
     fn reset(&mut self) {
@@ -134,6 +187,7 @@ mod tests {
         assert_eq!(d.name(), "Doji");
         assert_eq!(d.warmup_period(), 1);
         assert!(!d.is_ready());
+        assert!(!d.is_signed());
         assert!((d.body_threshold() - 0.1).abs() < 1e-12);
     }
 
@@ -182,4 +236,81 @@ mod tests {
         d.reset();
         assert!(!d.is_ready());
     }
+
+    #[test]
+    fn signed_accessor_and_builder() {
+        let d = Doji::new().signed();
+        assert!(d.is_signed());
+        // The consuming builder composes with `with_threshold`.
+        let t = Doji::with_threshold(0.05).unwrap().signed();
+        assert!(t.is_signed());
+        assert!((t.body_threshold() - 0.05).abs() < 1e-12);
+    }
+
+    #[test]
+    fn signed_dragonfly_is_plus_one() {
+        // Body at the top of the range, long lower shadow -> bullish.
+        let mut d = Doji::new().signed();
+        assert_eq!(d.update(c(10.0, 10.05, 6.0, 10.0, 0)), Some(1.0));
+    }
+
+    #[test]
+    fn signed_gravestone_is_minus_one() {
+        // Body at the bottom of the range, long upper shadow -> bearish.
+        let mut d = Doji::new().signed();
+        assert_eq!(d.update(c(10.0, 14.0, 9.95, 10.0, 0)), Some(-1.0));
+    }
+
+    #[test]
+    fn signed_long_legged_is_zero() {
+        // Body centred, symmetric shadows -> neutral.
+        let mut d = Doji::new().signed();
+        assert_eq!(d.update(c(10.0, 12.0, 8.0, 10.0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn signed_non_doji_is_zero() {
+        // A large body is not a Doji at all -> 0 regardless of position.
+        let mut d = Doji::new().signed();
+        assert_eq!(d.update(c(10.0, 12.0, 10.0, 12.0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn signed_zero_range_is_zero() {
+        let mut d = Doji::new().signed();
+        assert_eq!(d.update(c(10.0, 10.0, 10.0, 10.0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn signed_batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + i as f64;
+                // Alternate dragonfly / gravestone / centred Doji shapes.
+                match i % 3 {
+                    0 => c(base, base + 0.05, base - 4.0, base, i),
+                    1 => c(base, base + 4.0, base - 0.05, base, i),
+                    _ => c(base, base + 2.0, base - 2.0, base, i),
+                }
+            })
+            .collect();
+        let mut a = Doji::new().signed();
+        let mut b = Doji::new().signed();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn signed_survives_reset() {
+        let mut d = Doji::new().signed();
+        d.update(c(10.0, 10.05, 6.0, 10.0, 0));
+        assert!(d.is_ready());
+        d.reset();
+        assert!(!d.is_ready());
+        // `reset` clears only the streaming state, not the signed configuration.
+        assert!(d.is_signed());
+        assert_eq!(d.update(c(10.0, 10.05, 6.0, 10.0, 1)), Some(1.0));
+    }
 }

crates/wickra-core/src/indicators/effective_spread.rs

@@ -0,0 +1,157 @@
+//! Effective Spread — the realised cost of a single trade in basis points.
+
+use crate::microstructure::TradeQuote;
+use crate::traits::Indicator;
+
+/// Effective Spread — twice the signed deviation of an executed trade price
+/// from the prevailing mid, expressed in basis points of the mid.
+///
+/// ```text
+/// effectiveSpread = 2 · D · (tradePrice − mid) / mid · 10_000   (bps)
+/// ```
+///
+/// where `D` is the aggressor sign (`+1` for a buy, `−1` for a sell). The
+/// factor of two scales the one-sided deviation up to a full round-trip cost so
+/// it is directly comparable to the [quoted spread]: a marketable order that
+/// fills exactly at the touch of an otherwise quoted-spread book pays an
+/// effective spread equal to the quoted spread. Trades that fill *inside* the
+/// spread (price improvement) read below the quoted spread; trades that walk
+/// the book read above it.
+///
+/// A buy printed above the mid (`tradePrice > mid`) and a sell printed below it
+/// both yield a positive effective spread — the conventional sign, since the
+/// aggressor pays in both cases. A trade printed on the wrong side of the mid
+/// for its aggressor flag (a buy below the mid) reads negative, the signature of
+/// price improvement or a stale/mislabelled quote.
+///
+/// `Input = TradeQuote`, `Output = f64`. Stateless; ready after the first
+/// trade-quote.
+///
+/// [quoted spread]: crate::QuotedSpread
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{EffectiveSpread, Indicator, Side, Trade, TradeQuote};
+///
+/// let mut es = EffectiveSpread::new();
+/// // Buy filled at 100.05 against a mid of 100.0:
+/// // 2 · (+1) · (100.05 − 100.0) / 100.0 · 10_000 = 10 bps.
+/// let trade = Trade::new(100.05, 1.0, Side::Buy, 0).unwrap();
+/// let quote = TradeQuote::new(trade, 100.0).unwrap();
+/// assert!((es.update(quote).unwrap() - 10.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct EffectiveSpread {
+    has_emitted: bool,
+}
+
+impl EffectiveSpread {
+    /// Construct a new effective-spread indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for EffectiveSpread {
+    type Input = TradeQuote;
+    type Output = f64;
+
+    fn update(&mut self, quote: TradeQuote) -> Option<f64> {
+        self.has_emitted = true;
+        let sign = quote.trade.side.sign();
+        Some(2.0 * sign * (quote.trade.price - quote.mid) / quote.mid * 10_000.0)
+    }
+
+    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 {
+        "EffectiveSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::{Side, Trade};
+    use crate::traits::BatchExt;
+
+    fn quote(price: f64, side: Side, mid: f64) -> TradeQuote {
+        TradeQuote::new(Trade::new(price, 1.0, side, 0).unwrap(), mid).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let es = EffectiveSpread::new();
+        assert_eq!(es.name(), "EffectiveSpread");
+        assert_eq!(es.warmup_period(), 1);
+        assert!(!es.is_ready());
+    }
+
+    #[test]
+    fn buy_above_mid_is_positive() {
+        let mut es = EffectiveSpread::new();
+        // 2 · (+1) · (100.05 − 100.0) / 100.0 · 10_000 = 10 bps.
+        let out = es.update(quote(100.05, Side::Buy, 100.0)).unwrap();
+        assert!((out - 10.0).abs() < 1e-9);
+        assert!(es.is_ready());
+    }
+
+    #[test]
+    fn sell_below_mid_is_positive() {
+        let mut es = EffectiveSpread::new();
+        // 2 · (−1) · (99.95 − 100.0) / 100.0 · 10_000 = 10 bps.
+        let out = es.update(quote(99.95, Side::Sell, 100.0)).unwrap();
+        assert!((out - 10.0).abs() < 1e-9);
+    }
+
+    #[test]
+    fn price_improvement_reads_negative() {
+        let mut es = EffectiveSpread::new();
+        // A buy filled below the mid: price improvement -> negative.
+        let out = es.update(quote(99.95, Side::Buy, 100.0)).unwrap();
+        assert!(out < 0.0);
+    }
+
+    #[test]
+    fn trade_at_mid_is_zero() {
+        let mut es = EffectiveSpread::new();
+        assert_eq!(es.update(quote(100.0, Side::Buy, 100.0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let quotes: Vec<TradeQuote> = (0..20)
+            .map(|i| {
+                let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+                let price = 100.0 + f64::from(i % 4) * 0.01;
+                quote(price, side, 100.0)
+            })
+            .collect();
+        let mut a = EffectiveSpread::new();
+        let mut b = EffectiveSpread::new();
+        assert_eq!(
+            a.batch(&quotes),
+            quotes.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut es = EffectiveSpread::new();
+        es.update(quote(100.05, Side::Buy, 100.0));
+        assert!(es.is_ready());
+        es.reset();
+        assert!(!es.is_ready());
+    }
+}

crates/wickra-core/src/indicators/engulfing.rs

@@ -22,6 +22,13 @@ use crate::traits::Indicator;
 /// body exists to engulf. Pattern-shape check only — no trend filter is
 /// applied; combine with a trend indicator for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/footprint.rs

@@ -0,0 +1,259 @@
+//! Footprint — buy/sell volume profile per price bucket within a bar.
+
+use std::collections::BTreeMap;
+
+use crate::error::{Error, Result};
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// One price bucket of a [`Footprint`]: the buy- and sell-initiated volume that
+/// traded there since the last reset.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct FootprintLevel {
+    /// Bucket price (the bucket index times the tick size).
+    pub price: f64,
+    /// Sell-initiated (bid-hitting) volume traded at this bucket.
+    pub bid_vol: f64,
+    /// Buy-initiated (ask-lifting) volume traded at this bucket.
+    pub ask_vol: f64,
+}
+
+/// The full footprint of a bar: one [`FootprintLevel`] per touched price
+/// bucket, sorted ascending by price.
+#[derive(Debug, Clone, PartialEq, Default)]
+pub struct FootprintOutput {
+    /// Touched price buckets, lowest price first.
+    pub levels: Vec<FootprintLevel>,
+}
+
+/// Footprint — the buy/sell volume profile of a bar, bucketed by price.
+///
+/// A footprint (a.k.a. bid/ask or volume cluster chart) decomposes the volume
+/// traded within a bar across the price levels at which it printed, splitting
+/// each level into buy-initiated (ask-lifting) and sell-initiated (bid-hitting)
+/// volume. It exposes *where* inside a bar the activity happened and which side
+/// was the aggressor there — the basis for absorption, imbalance and
+/// point-of-control analysis that a single OHLCV bar hides.
+///
+/// Each trade is assigned to the price bucket `round(price / tick_size)`; its
+/// size is added to that bucket's ask volume for a buy and bid volume for a
+/// sell. Every [`update`] returns the complete footprint accumulated since the
+/// last [`reset`], as a [`FootprintOutput`] whose `levels` are sorted ascending
+/// by price. Call [`reset`] at each bar (or session) boundary to start a fresh
+/// footprint.
+///
+/// `Input = Trade`, `Output = FootprintOutput`. Ready after the first trade.
+///
+/// [`update`]: crate::Indicator::update
+/// [`reset`]: crate::Indicator::reset
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Footprint, Indicator, Side, Trade};
+///
+/// let mut fp = Footprint::new(1.0).unwrap();
+/// fp.update(Trade::new(100.2, 2.0, Side::Buy, 0).unwrap());
+/// let out = fp.update(Trade::new(100.7, 3.0, Side::Sell, 1).unwrap()).unwrap();
+/// // Two buckets: 100 (ask 2) and 101 (bid 3).
+/// assert_eq!(out.levels.len(), 2);
+/// assert_eq!(out.levels[0].price, 100.0);
+/// assert_eq!(out.levels[0].ask_vol, 2.0);
+/// assert_eq!(out.levels[1].price, 101.0);
+/// assert_eq!(out.levels[1].bid_vol, 3.0);
+/// ```
+#[derive(Debug, Clone)]
+pub struct Footprint {
+    tick_size: f64,
+    // bucket index -> (bid_vol = sell-initiated, ask_vol = buy-initiated).
+    buckets: BTreeMap<i64, (f64, f64)>,
+    has_emitted: bool,
+}
+
+impl Footprint {
+    /// Construct a footprint with the given price-bucket `tick_size`.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidTick`] if `tick_size` is not a finite, strictly
+    /// positive number.
+    pub fn new(tick_size: f64) -> Result<Self> {
+        if !tick_size.is_finite() || tick_size <= 0.0 {
+            return Err(Error::InvalidTick {
+                message: "footprint tick_size must be finite and positive",
+            });
+        }
+        Ok(Self {
+            tick_size,
+            buckets: BTreeMap::new(),
+            has_emitted: false,
+        })
+    }
+
+    /// The configured price-bucket size.
+    pub const fn tick_size(&self) -> f64 {
+        self.tick_size
+    }
+
+    fn bucket_index(&self, price: f64) -> i64 {
+        // Float-to-int `as` saturates rather than wrapping, so an extreme
+        // price/tick ratio clamps to i64::MIN/MAX instead of misbehaving;
+        // realistic ratios fit comfortably.
+        #[allow(clippy::cast_possible_truncation)]
+        {
+            (price / self.tick_size).round() as i64
+        }
+    }
+
+    fn snapshot(&self) -> FootprintOutput {
+        let levels = self
+            .buckets
+            .iter()
+            .map(|(&index, &(bid_vol, ask_vol))| FootprintLevel {
+                price: index as f64 * self.tick_size,
+                bid_vol,
+                ask_vol,
+            })
+            .collect();
+        FootprintOutput { levels }
+    }
+}
+
+impl Indicator for Footprint {
+    type Input = Trade;
+    type Output = FootprintOutput;
+
+    fn update(&mut self, trade: Trade) -> Option<FootprintOutput> {
+        self.has_emitted = true;
+        let index = self.bucket_index(trade.price);
+        let entry = self.buckets.entry(index).or_insert((0.0, 0.0));
+        if trade.side.sign() > 0.0 {
+            entry.1 += trade.size;
+        } else {
+            entry.0 += trade.size;
+        }
+        Some(self.snapshot())
+    }
+
+    fn reset(&mut self) {
+        self.buckets.clear();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Footprint"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+
+    fn trade(price: f64, size: f64, side: Side) -> Trade {
+        Trade::new(price, size, side, 0).unwrap()
+    }
+
+    #[test]
+    fn rejects_bad_tick_size() {
+        assert!(matches!(
+            Footprint::new(0.0),
+            Err(Error::InvalidTick { .. })
+        ));
+        assert!(matches!(
+            Footprint::new(-1.0),
+            Err(Error::InvalidTick { .. })
+        ));
+        assert!(matches!(
+            Footprint::new(f64::NAN),
+            Err(Error::InvalidTick { .. })
+        ));
+        assert!(Footprint::new(0.5).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let fp = Footprint::new(0.25).unwrap();
+        assert_eq!(fp.name(), "Footprint");
+        assert_eq!(fp.warmup_period(), 1);
+        assert_eq!(fp.tick_size(), 0.25);
+        assert!(!fp.is_ready());
+    }
+
+    #[test]
+    fn buckets_buy_and_sell_volume() {
+        let mut fp = Footprint::new(1.0).unwrap();
+        fp.update(trade(100.2, 2.0, Side::Buy));
+        fp.update(trade(100.7, 3.0, Side::Sell));
+        let out = fp.update(trade(100.1, 1.0, Side::Buy)).unwrap();
+        assert!(fp.is_ready());
+        // Bucket 100: buy 2 + buy 1 = ask 3, bid 0. Bucket 101: sell 3.
+        assert_eq!(out.levels.len(), 2);
+        assert_eq!(out.levels[0].price, 100.0);
+        assert_eq!(out.levels[0].ask_vol, 3.0);
+        assert_eq!(out.levels[0].bid_vol, 0.0);
+        assert_eq!(out.levels[1].price, 101.0);
+        assert_eq!(out.levels[1].bid_vol, 3.0);
+        assert_eq!(out.levels[1].ask_vol, 0.0);
+    }
+
+    #[test]
+    fn levels_sorted_ascending_by_price() {
+        let mut fp = Footprint::new(1.0).unwrap();
+        fp.update(trade(103.0, 1.0, Side::Buy));
+        fp.update(trade(100.0, 1.0, Side::Sell));
+        let out = fp.update(trade(101.0, 1.0, Side::Buy)).unwrap();
+        let prices: Vec<f64> = out.levels.iter().map(|l| l.price).collect();
+        assert_eq!(prices, vec![100.0, 101.0, 103.0]);
+    }
+
+    #[test]
+    fn sub_tick_prices_share_a_bucket() {
+        let mut fp = Footprint::new(0.5).unwrap();
+        // 100.24 and 100.26 both round to bucket 200 (price 100.0)... check:
+        // 100.24/0.5 = 200.48 -> 200; 100.26/0.5 = 200.52 -> 201. Distinct.
+        fp.update(trade(100.20, 1.0, Side::Buy)); // 200.4 -> 200 -> price 100.0
+        let out = fp.update(trade(100.10, 2.0, Side::Buy)).unwrap(); // 200.2 -> 200
+        assert_eq!(out.levels.len(), 1);
+        assert_eq!(out.levels[0].price, 100.0);
+        assert_eq!(out.levels[0].ask_vol, 3.0);
+    }
+
+    #[test]
+    fn reset_clears_the_footprint() {
+        let mut fp = Footprint::new(1.0).unwrap();
+        fp.update(trade(100.0, 5.0, Side::Buy));
+        assert!(fp.is_ready());
+        fp.reset();
+        assert!(!fp.is_ready());
+        let out = fp.update(trade(200.0, 1.0, Side::Sell)).unwrap();
+        assert_eq!(out.levels.len(), 1);
+        assert_eq!(out.levels[0].price, 200.0);
+        assert_eq!(out.levels[0].bid_vol, 1.0);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..30)
+            .map(|i| {
+                let side = if i % 3 == 0 { Side::Sell } else { Side::Buy };
+                trade(100.0 + f64::from(i % 5), 1.0 + f64::from(i % 4), side)
+            })
+            .collect();
+        let mut a = Footprint::new(1.0).unwrap();
+        let mut b = Footprint::new(1.0).unwrap();
+        assert_eq!(
+            a.batch(&trades),
+            trades.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

crates/wickra-core/src/indicators/hammer.rs

@@ -22,6 +22,14 @@ use crate::traits::Indicator;
 /// check only — no trend filter is applied; combine with a trend indicator
 /// for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// A Hammer is bullish by definition, so under the uniform candlestick sign
+/// convention (`+1.0` bullish, `−1.0` bearish, `0.0` none) it emits `+1.0`
+/// when the shape matches and `0.0` otherwise — it never emits `−1.0`. The
+/// same geometry read at the top of an uptrend is the bearish `HangingMan`,
+/// which carries the opposite sign.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/hanging_man.rs

@@ -22,6 +22,14 @@ use crate::traits::Indicator;
 /// check only — no trend filter is applied; combine with a trend indicator
 /// for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// A Hanging Man is bearish by definition, so under the uniform candlestick
+/// sign convention (`+1.0` bullish, `−1.0` bearish, `0.0` none) it emits
+/// `−1.0` when the shape matches and `0.0` otherwise — it never emits `+1.0`.
+/// The same geometry read at the bottom of a downtrend is the bullish
+/// `Hammer`, which carries the opposite sign.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/harami.rs

@@ -23,6 +23,13 @@ use crate::traits::Indicator;
 /// no trend filter is applied; combine with a trend indicator for actionable
 /// signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/inverted_hammer.rs

@@ -22,6 +22,14 @@ use crate::traits::Indicator;
 /// check only — no trend filter is applied; combine with a trend indicator
 /// for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// An Inverted Hammer is bullish by definition, so under the uniform
+/// candlestick sign convention (`+1.0` bullish, `−1.0` bearish, `0.0` none) it
+/// emits `+1.0` when the shape matches and `0.0` otherwise — it never emits
+/// `−1.0`. The same geometry read at the top of an uptrend is the bearish
+/// `ShootingStar`, which carries the opposite sign.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/kyles_lambda.rs

@@ -0,0 +1,281 @@
+//! Kyle's Lambda — rolling price impact per unit of signed order flow.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::microstructure::TradeQuote;
+use crate::traits::Indicator;
+
+/// Kyle's Lambda — the rolling ordinary-least-squares slope of mid-price changes
+/// on signed trade volume, the canonical measure of market depth / price
+/// impact.
+///
+/// Each `update` receives a [`TradeQuote`] — a trade plus the mid prevailing at
+/// execution. Internally the indicator forms, per trade, the mid change since
+/// the previous trade (`Δmid = midₜ − midₜ₋₁`) and the signed volume
+/// (`q = size · D`, with `D` the aggressor sign), then runs a rolling OLS
+/// regression of `Δmid` on `q` over the trailing window of `window` trades:
+///
+/// ```text
+/// cov = (1/n) · Σ q·Δmid − q̄·Δ̄mid
+/// var = (1/n) · Σ q²      − q̄²
+/// λ   = cov / var
+/// ```
+///
+/// `λ` is the estimated price move per unit of signed volume: a deep, liquid
+/// book absorbs flow with little movement and reads a small `λ`; a thin book
+/// moves sharply per unit traded and reads a large `λ`. It is a direct,
+/// model-light proxy for the slope of the demand curve in Kyle's microstructure
+/// model.
+///
+/// Each `update` is O(1): four running sums (`Σq`, `ΣΔmid`, `Σq²`, `Σq·Δmid`)
+/// are maintained as the window slides. A window of constant signed volume has
+/// zero variance and `λ` is undefined; the indicator returns `0` in that case
+/// rather than producing `NaN`.
+///
+/// `Input = TradeQuote`, `Output = f64`. It warms up for `window + 1`
+/// trade-quotes: one to seed the previous mid, then `window` paired
+/// observations.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, KylesLambda, Side, Trade, TradeQuote};
+///
+/// // A book where each trade moves the mid by exactly 0.5 per unit of signed
+/// // volume gives λ = 0.5.
+/// let mut lambda = KylesLambda::new(8).unwrap();
+/// let mut mid = 100.0;
+/// let mut last = None;
+/// for i in 0..20 {
+///     let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+///     let size = 1.0 + f64::from(i % 3);
+///     let signed = size * side.sign();
+///     mid += 0.5 * signed;
+///     let trade = Trade::new(mid, size, side, 0).unwrap();
+///     last = lambda.update(TradeQuote::new(trade, mid).unwrap());
+/// }
+/// assert!((last.unwrap() - 0.5).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct KylesLambda {
+    window: usize,
+    prev_mid: Option<f64>,
+    pairs: VecDeque<(f64, f64)>,
+    sum_q: f64,
+    sum_dm: f64,
+    sum_qq: f64,
+    sum_qdm: f64,
+}
+
+impl KylesLambda {
+    /// Construct a rolling Kyle's lambda over `window` paired observations.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `window < 2` (the regression
+    /// variance needs at least two observations).
+    pub fn new(window: usize) -> Result<Self> {
+        if window < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "kyle's lambda needs window >= 2",
+            });
+        }
+        Ok(Self {
+            window,
+            prev_mid: None,
+            pairs: VecDeque::with_capacity(window),
+            sum_q: 0.0,
+            sum_dm: 0.0,
+            sum_qq: 0.0,
+            sum_qdm: 0.0,
+        })
+    }
+
+    /// The configured window length, in paired observations.
+    pub const fn window(&self) -> usize {
+        self.window
+    }
+
+    fn push_pair(&mut self, signed_vol: f64, delta_mid: f64) -> Option<f64> {
+        if self.pairs.len() == self.window {
+            let (old_q, old_dm) = self.pairs.pop_front().expect("non-empty");
+            self.sum_q -= old_q;
+            self.sum_dm -= old_dm;
+            self.sum_qq -= old_q * old_q;
+            self.sum_qdm -= old_q * old_dm;
+        }
+        self.pairs.push_back((signed_vol, delta_mid));
+        self.sum_q += signed_vol;
+        self.sum_dm += delta_mid;
+        self.sum_qq += signed_vol * signed_vol;
+        self.sum_qdm += signed_vol * delta_mid;
+        if self.pairs.len() < self.window {
+            return None;
+        }
+        let n = self.window as f64;
+        let mean_q = self.sum_q / n;
+        let mean_dm = self.sum_dm / n;
+        let var_q = (self.sum_qq / n - mean_q * mean_q).max(0.0);
+        let cov = self.sum_qdm / n - mean_q * mean_dm;
+        if var_q == 0.0 {
+            // Constant signed-volume window has no defined slope.
+            return Some(0.0);
+        }
+        Some(cov / var_q)
+    }
+}
+
+impl Indicator for KylesLambda {
+    type Input = TradeQuote;
+    type Output = f64;
+
+    fn update(&mut self, quote: TradeQuote) -> Option<f64> {
+        let mid = quote.mid;
+        let signed_vol = quote.trade.size * quote.trade.side.sign();
+        let Some(prev) = self.prev_mid else {
+            self.prev_mid = Some(mid);
+            return None;
+        };
+        self.prev_mid = Some(mid);
+        self.push_pair(signed_vol, mid - prev)
+    }
+
+    fn reset(&mut self) {
+        self.prev_mid = None;
+        self.pairs.clear();
+        self.sum_q = 0.0;
+        self.sum_dm = 0.0;
+        self.sum_qq = 0.0;
+        self.sum_qdm = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.window + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.pairs.len() == self.window
+    }
+
+    fn name(&self) -> &'static str {
+        "KylesLambda"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::{Side, Trade};
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn quotes_with_impact(n: usize, impact: f64) -> Vec<TradeQuote> {
+        let mut mid = 100.0;
+        (0..n)
+            .map(|i| {
+                let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+                let size = 1.0 + (i % 3) as f64;
+                let signed = size * side.sign();
+                mid += impact * signed;
+                let trade = Trade::new(mid, size, side, 0).unwrap();
+                TradeQuote::new(trade, mid).unwrap()
+            })
+            .collect()
+    }
+
+    #[test]
+    fn rejects_window_below_two() {
+        assert!(KylesLambda::new(0).is_err());
+        assert!(KylesLambda::new(1).is_err());
+        assert!(KylesLambda::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let kl = KylesLambda::new(14).unwrap();
+        assert_eq!(kl.name(), "KylesLambda");
+        assert_eq!(kl.window(), 14);
+        assert_eq!(kl.warmup_period(), 15);
+        assert!(!kl.is_ready());
+    }
+
+    #[test]
+    fn recovers_constant_impact_slope() {
+        // mid moves exactly 0.5 per unit signed volume -> lambda = 0.5.
+        let last = KylesLambda::new(6)
+            .unwrap()
+            .batch(&quotes_with_impact(20, 0.5))
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.5, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn negative_impact_reads_negative() {
+        let last = KylesLambda::new(6)
+            .unwrap()
+            .batch(&quotes_with_impact(20, -0.3))
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, -0.3, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn constant_signed_volume_is_zero() {
+        // Every trade is a buy of size 1: signed volume is constant -> var 0 -> 0.
+        let mut mid = 100.0;
+        let quotes: Vec<TradeQuote> = (0..10)
+            .map(|_| {
+                mid += 0.01;
+                let trade = Trade::new(mid, 1.0, Side::Buy, 0).unwrap();
+                TradeQuote::new(trade, mid).unwrap()
+            })
+            .collect();
+        let last = KylesLambda::new(5)
+            .unwrap()
+            .batch(&quotes)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn warms_up_after_window_plus_one() {
+        let mut kl = KylesLambda::new(3).unwrap();
+        let quotes = quotes_with_impact(4, 0.2);
+        assert_eq!(kl.update(quotes[0]), None); // seeds prev mid
+        assert_eq!(kl.update(quotes[1]), None);
+        assert_eq!(kl.update(quotes[2]), None);
+        assert!(!kl.is_ready());
+        assert!(kl.update(quotes[3]).is_some());
+        assert!(kl.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let quotes = quotes_with_impact(40, 0.15);
+        let batch = KylesLambda::new(10).unwrap().batch(&quotes);
+        let mut kl = KylesLambda::new(10).unwrap();
+        let streamed: Vec<_> = quotes.iter().map(|q| kl.update(*q)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut kl = KylesLambda::new(3).unwrap();
+        for q in quotes_with_impact(6, 0.2) {
+            kl.update(q);
+        }
+        assert!(kl.is_ready());
+        kl.reset();
+        assert!(!kl.is_ready());
+        assert_eq!(kl.update(quotes_with_impact(1, 0.2)[0]), None);
+    }
+}

crates/wickra-core/src/indicators/lead_lag_cross_correlation.rs

@@ -0,0 +1,324 @@
+//! Lead–Lag Cross-Correlation — which of two assets leads the other, and by how much.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Output of [`LeadLagCrossCorrelation`]: the lead/lag offset and its correlation.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct LeadLagCrossCorrelationOutput {
+    /// The offset `k ∈ [−max_lag, max_lag]` that maximises `|corr(a[t], b[t+k])|`.
+    ///
+    /// A **positive** lag means `a` leads `b` by `lag` samples (a's pattern
+    /// shows up in `b` that many steps later); a **negative** lag means `b`
+    /// leads `a`; `0` means the two are most correlated contemporaneously.
+    pub lag: i64,
+    /// The (signed) Pearson correlation at that lag, in `[−1, +1]`.
+    pub correlation: f64,
+}
+
+/// Rolling lead–lag cross-correlation between two synchronised series.
+///
+/// Each `update` receives one `(a, b)` pair. The indicator keeps the most
+/// recent `window + 2·max_lag` samples of each series and, once full, reports
+/// the integer offset `k ∈ [−max_lag, +max_lag]` that maximises the absolute
+/// Pearson correlation between `a` and a copy of `b` shifted by `k`:
+///
+/// ```text
+/// lag = argmax_k | corr( a[t], b[t+k] ) |
+/// ```
+///
+/// This answers "does BTC lead ETH on this timescale, and by how many bars?".
+/// A positive lag means `a` leads `b`; a negative lag means `b` leads `a`. The
+/// reported `correlation` is the signed correlation at that lag, so its sign
+/// tells you whether the lead relationship is positive or inverse.
+///
+/// The comparison is fully causal: `a`'s window is held fixed in the centre of
+/// the buffer and `b`'s window slides across it, so every lag — positive and
+/// negative — is evaluated only against data already seen. The candidate lags
+/// are scanned in order of increasing `|k|`, so ties resolve to the smallest
+/// absolute offset (lag `0` wins an exact tie).
+///
+/// Each `update` is `O(window · max_lag)` — proportional to the fixed
+/// parameters, not the series length. A flat window in either channel makes a
+/// correlation undefined; it is reported as `0` rather than `NaN`.
+///
+/// Feed raw prices or returns depending on your convention; lead–lag on
+/// returns is the more common choice for relating two assets.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, LeadLagCrossCorrelation};
+///
+/// let mut ll = LeadLagCrossCorrelation::new(12, 5).unwrap();
+/// let mut last = None;
+/// for t in 0..60 {
+///     let a = (f64::from(t) * 0.4).sin() + 0.4 * (f64::from(t) * 1.1).sin();
+///     // `b` is `a` delayed by 3 samples, so `a` leads `b` by 3.
+///     let b = (f64::from(t - 3) * 0.4).sin() + 0.4 * (f64::from(t - 3) * 1.1).sin();
+///     last = ll.update((a, b));
+/// }
+/// let out = last.unwrap();
+/// assert_eq!(out.lag, 3);
+/// assert!(out.correlation > 0.99);
+/// ```
+#[derive(Debug, Clone)]
+pub struct LeadLagCrossCorrelation {
+    window: usize,
+    max_lag: usize,
+    len: usize,
+    a_buf: VecDeque<f64>,
+    b_buf: VecDeque<f64>,
+}
+
+impl LeadLagCrossCorrelation {
+    /// Construct a new lead–lag cross-correlation.
+    ///
+    /// `window` is the number of overlapping points each correlation is
+    /// computed over; `max_lag` is the largest offset (in either direction)
+    /// that is searched.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `window < 2` or `max_lag == 0`.
+    pub fn new(window: usize, max_lag: usize) -> Result<Self> {
+        if window < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "lead-lag cross-correlation needs window >= 2",
+            });
+        }
+        if max_lag == 0 {
+            return Err(Error::InvalidPeriod {
+                message: "lead-lag cross-correlation needs max_lag >= 1",
+            });
+        }
+        let len = window + 2 * max_lag;
+        Ok(Self {
+            window,
+            max_lag,
+            len,
+            a_buf: VecDeque::with_capacity(len),
+            b_buf: VecDeque::with_capacity(len),
+        })
+    }
+
+    /// Number of overlapping points per correlation.
+    pub const fn window(&self) -> usize {
+        self.window
+    }
+
+    /// Largest offset searched in either direction.
+    pub const fn max_lag(&self) -> usize {
+        self.max_lag
+    }
+
+    /// Pearson correlation between `a[a_start .. a_start+window]` and
+    /// `b[b_start .. b_start+window]`, clamped to `[−1, 1]`. Returns `0` when
+    /// either window has zero variance.
+    fn corr_at(&self, a_start: usize, b_start: usize) -> f64 {
+        let n = self.window as f64;
+        let mut sa = 0.0;
+        let mut sb = 0.0;
+        let mut saa = 0.0;
+        let mut sbb = 0.0;
+        let mut sab = 0.0;
+        for j in 0..self.window {
+            let x = self.a_buf[a_start + j];
+            let y = self.b_buf[b_start + j];
+            sa += x;
+            sb += y;
+            saa += x * x;
+            sbb += y * y;
+            sab += x * y;
+        }
+        let mean_a = sa / n;
+        let mean_b = sb / n;
+        let var_a = (saa / n - mean_a * mean_a).max(0.0);
+        let var_b = (sbb / n - mean_b * mean_b).max(0.0);
+        let denom = (var_a * var_b).sqrt();
+        if denom == 0.0 {
+            return 0.0;
+        }
+        let cov = sab / n - mean_a * mean_b;
+        (cov / denom).clamp(-1.0, 1.0)
+    }
+}
+
+impl Indicator for LeadLagCrossCorrelation {
+    /// `(a, b)` pair.
+    type Input = (f64, f64);
+    type Output = LeadLagCrossCorrelationOutput;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<LeadLagCrossCorrelationOutput> {
+        let (a, b) = input;
+        if self.a_buf.len() == self.len {
+            self.a_buf.pop_front();
+            self.b_buf.pop_front();
+        }
+        self.a_buf.push_back(a);
+        self.b_buf.push_back(b);
+        if self.a_buf.len() < self.len {
+            return None;
+        }
+        // `a`'s window sits in the centre; `b`'s window slides ±max_lag.
+        let a_start = self.max_lag;
+        // Start at lag 0, then widen outward so ties prefer the smallest |lag|.
+        // The lag is tracked as a signed counter incremented by ±1, so no
+        // unsigned index is ever cast to a signed type.
+        let mut best_lag: i64 = 0;
+        let mut best_corr = self.corr_at(a_start, a_start);
+        let mut best_abs = best_corr.abs();
+        let mut lag_neg: i64 = 0;
+        let mut lag_pos: i64 = 0;
+        for d in 1..=self.max_lag {
+            lag_neg -= 1;
+            lag_pos += 1;
+            // Negative lag: b shifted earlier (b leads a).
+            let c_neg = self.corr_at(a_start, a_start - d);
+            if c_neg.abs() > best_abs {
+                best_abs = c_neg.abs();
+                best_corr = c_neg;
+                best_lag = lag_neg;
+            }
+            // Positive lag: b shifted later (a leads b).
+            let c_pos = self.corr_at(a_start, a_start + d);
+            if c_pos.abs() > best_abs {
+                best_abs = c_pos.abs();
+                best_corr = c_pos;
+                best_lag = lag_pos;
+            }
+        }
+        Some(LeadLagCrossCorrelationOutput {
+            lag: best_lag,
+            correlation: best_corr,
+        })
+    }
+
+    fn reset(&mut self) {
+        self.a_buf.clear();
+        self.b_buf.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.len
+    }
+
+    fn is_ready(&self) -> bool {
+        self.a_buf.len() == self.len
+    }
+
+    fn name(&self) -> &'static str {
+        "LeadLagCrossCorrelation"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn signal(t: i64) -> f64 {
+        let t = t as f64;
+        (t * 0.4).sin() + 0.4 * (t * 1.1).sin() + 0.2 * (t * 0.27).cos()
+    }
+
+    #[test]
+    fn rejects_invalid_params() {
+        assert!(LeadLagCrossCorrelation::new(1, 5).is_err());
+        assert!(LeadLagCrossCorrelation::new(10, 0).is_err());
+        assert!(LeadLagCrossCorrelation::new(10, 5).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ll = LeadLagCrossCorrelation::new(10, 4).unwrap();
+        assert_eq!(ll.window(), 10);
+        assert_eq!(ll.max_lag(), 4);
+        // len = window + 2*max_lag = 10 + 8 = 18.
+        assert_eq!(ll.warmup_period(), 18);
+        assert_eq!(ll.name(), "LeadLagCrossCorrelation");
+    }
+
+    #[test]
+    fn detects_positive_lead() {
+        // b is a delayed by 3 ⇒ a leads b ⇒ lag = +3, correlation ≈ 1.
+        let pairs: Vec<(f64, f64)> = (0..60).map(|t| (signal(t), signal(t - 3))).collect();
+        let out = LeadLagCrossCorrelation::new(12, 5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(out.lag, 3);
+        assert!(out.correlation > 0.99, "corr was {}", out.correlation);
+    }
+
+    #[test]
+    fn detects_negative_lead() {
+        // a is a delayed copy of b ⇒ b leads a ⇒ lag = −2.
+        let pairs: Vec<(f64, f64)> = (0..60).map(|t| (signal(t - 2), signal(t))).collect();
+        let out = LeadLagCrossCorrelation::new(12, 5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(out.lag, -2);
+        assert!(out.correlation > 0.99, "corr was {}", out.correlation);
+    }
+
+    #[test]
+    fn contemporaneous_is_lag_zero() {
+        // Identical streams correlate best at lag 0 with correlation 1.
+        let pairs: Vec<(f64, f64)> = (0..60).map(|t| (signal(t), signal(t))).collect();
+        let out = LeadLagCrossCorrelation::new(12, 5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(out.lag, 0);
+        assert_relative_eq!(out.correlation, 1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn flat_channel_yields_zero_correlation() {
+        // A constant `a` has no variance ⇒ every correlation is 0 ⇒ lag 0.
+        let pairs: Vec<(f64, f64)> = (0..40).map(|t| (5.0, signal(t))).collect();
+        let out = LeadLagCrossCorrelation::new(10, 4)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(out.lag, 0);
+        assert_relative_eq!(out.correlation, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ll = LeadLagCrossCorrelation::new(10, 4).unwrap();
+        for t in 0..40 {
+            ll.update((signal(t), signal(t - 2)));
+        }
+        assert!(ll.is_ready());
+        ll.reset();
+        assert!(!ll.is_ready());
+        assert_eq!(ll.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..80).map(|t| (signal(t), signal(t - 1))).collect();
+        let batch = LeadLagCrossCorrelation::new(12, 5).unwrap().batch(&pairs);
+        let mut ll = LeadLagCrossCorrelation::new(12, 5).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| ll.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/marubozu.rs

@@ -22,6 +22,13 @@ use crate::traits::Indicator;
 /// `shadow_tolerance` defaults to `0.05` (5 % of the bar range allowed on each
 /// side) and must lie in `[0, 1)`.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/microprice.rs

@@ -0,0 +1,170 @@
+//! Microprice — size-weighted fair value of the top of book.
+
+use crate::microstructure::OrderBook;
+use crate::traits::Indicator;
+
+/// Microprice — the size-weighted mid of the top of book.
+///
+/// The microprice tilts the mid toward the side that is *more likely to be
+/// hit*: it weights each touch price by the size resting on the **opposite**
+/// side, so a heavy ask (sell pressure) pulls the fair value down toward the
+/// bid, and vice versa:
+///
+/// ```text
+/// microprice = (bidPrice₁·askSize₁ + askPrice₁·bidSize₁) / (bidSize₁ + askSize₁)
+/// ```
+///
+/// When both top sizes are zero the weighting is undefined and the plain mid
+/// `(bidPrice₁ + askPrice₁) / 2` is returned. An empty book yields `0`.
+///
+/// `Input = OrderBook`, `Output = f64`. Stateless; ready after the first
+/// snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Level, Microprice, OrderBook};
+///
+/// let book = OrderBook::new(
+///     vec![Level::new(100.0, 1.0).unwrap()],
+///     vec![Level::new(101.0, 3.0).unwrap()],
+/// )
+/// .unwrap();
+/// let mut mp = Microprice::new();
+/// // (100·3 + 101·1) / (1 + 3) = 401 / 4 = 100.25 — pulled toward the bid.
+/// assert_eq!(mp.update(book), Some(100.25));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct Microprice {
+    has_emitted: bool,
+}
+
+impl Microprice {
+    /// Construct a new microprice indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for Microprice {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let (Some(bid), Some(ask)) = (book.best_bid(), book.best_ask()) else {
+            return Some(0.0);
+        };
+        let total = bid.size + ask.size;
+        if total <= 0.0 {
+            return Some(f64::midpoint(bid.price, ask.price));
+        }
+        Some((bid.price * ask.size + ask.price * bid.size) / 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 {
+        "Microprice"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Level;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let mp = Microprice::new();
+        assert_eq!(mp.name(), "Microprice");
+        assert_eq!(mp.warmup_period(), 1);
+        assert!(!mp.is_ready());
+    }
+
+    #[test]
+    fn weights_toward_thin_side() {
+        let mut mp = Microprice::new();
+        // Heavy ask -> microprice pulled toward bid.
+        assert_eq!(
+            mp.update(book(&[(100.0, 1.0)], &[(101.0, 3.0)])),
+            Some(100.25)
+        );
+        assert!(mp.is_ready());
+    }
+
+    #[test]
+    fn balanced_top_equals_mid() {
+        let mut mp = Microprice::new();
+        assert_eq!(
+            mp.update(book(&[(100.0, 2.0)], &[(101.0, 2.0)])),
+            Some(100.5)
+        );
+    }
+
+    #[test]
+    fn zero_size_falls_back_to_mid() {
+        let mut mp = Microprice::new();
+        assert_eq!(
+            mp.update(book(&[(100.0, 0.0)], &[(102.0, 0.0)])),
+            Some(101.0)
+        );
+    }
+
+    #[test]
+    fn empty_book_is_zero() {
+        let mut mp = Microprice::new();
+        assert_eq!(
+            mp.update(OrderBook::new_unchecked(vec![], vec![])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let ask = 1.0 + f64::from(i % 4);
+                book(&[(100.0, 2.0)], &[(101.0, ask)])
+            })
+            .collect();
+        let mut a = Microprice::new();
+        let mut b = Microprice::new();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut mp = Microprice::new();
+        mp.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)]));
+        assert!(mp.is_ready());
+        mp.reset();
+        assert!(!mp.is_ready());
+    }
+}

crates/wickra-core/src/indicators/mod.rs

@@ -43,15 +43,18 @@ mod classic_pivots;
 mod cmf;
 mod cmo;
 mod coefficient_of_variation;
+mod cointegration;
 mod conditional_value_at_risk;
 mod connors_rsi;
 mod coppock;
+mod cvd;
 mod cybernetic_cycle;
 mod decycler;
 mod decycler_oscillator;
 mod dema;
 mod demand_index;
 mod demark_pivots;
+mod depth_slope;
 mod detrended_std_dev;
 mod doji;
 mod donchian;
@@ -60,6 +63,7 @@ mod double_bollinger;
 mod dpo;
 mod drawdown_duration;
 mod ease_of_movement;
+mod effective_spread;
 mod ehlers_stochastic;
 mod elder_impulse;
 mod ema;
@@ -69,6 +73,7 @@ mod evwma;
 mod fama;
 mod fibonacci_pivots;
 mod fisher_transform;
+mod footprint;
 mod force_index;
 mod fractal_chaos_bands;
 mod frama;
@@ -98,7 +103,9 @@ mod keltner;
 mod kst;
 mod kurtosis;
 mod kvo;
+mod kyles_lambda;
 mod laguerre_rsi;
+mod lead_lag_cross_correlation;
 mod linreg;
 mod linreg_angle;
 mod linreg_channel;
@@ -114,14 +121,20 @@ mod mcginley_dynamic;
 mod median_absolute_deviation;
 mod median_price;
 mod mfi;
+mod microprice;
 mod mom;
 mod morning_evening_star;
 mod natr;
 mod nvi;
+mod ob_imbalance_full;
+mod ob_imbalance_top1;
+mod ob_imbalance_topn;
 mod obv;
 mod omega_ratio;
 mod opening_range;
 mod pain_index;
+mod pair_spread_zscore;
+mod pairwise_beta;
 mod parkinson;
 mod pearson_correlation;
 mod percent_b;
@@ -133,8 +146,11 @@ mod ppo;
 mod profit_factor;
 mod psar;
 mod pvi;
+mod quoted_spread;
 mod r_squared;
+mod realized_spread;
 mod recovery_factor;
+mod relative_strength_ab;
 mod renko_trailing_stop;
 mod roc;
 mod rogers_satchell;
@@ -145,6 +161,7 @@ mod rvi_volatility;
 mod rwi;
 mod sharpe_ratio;
 mod shooting_star;
+mod signed_volume;
 mod sine_wave;
 mod skewness;
 mod sma;
@@ -181,6 +198,7 @@ mod three_inside;
 mod three_outside;
 mod three_soldiers_or_crows;
 mod tii;
+mod trade_imbalance;
 mod treynor_ratio;
 mod trima;
 mod trix;
@@ -257,15 +275,18 @@ pub use classic_pivots::{ClassicPivots, ClassicPivotsOutput};
 pub use cmf::ChaikinMoneyFlow;
 pub use cmo::Cmo;
 pub use coefficient_of_variation::CoefficientOfVariation;
+pub use cointegration::{Cointegration, CointegrationOutput};
 pub use conditional_value_at_risk::ConditionalValueAtRisk;
 pub use connors_rsi::ConnorsRsi;
 pub use coppock::Coppock;
+pub use cvd::CumulativeVolumeDelta;
 pub use cybernetic_cycle::CyberneticCycle;
 pub use decycler::Decycler;
 pub use decycler_oscillator::DecyclerOscillator;
 pub use dema::Dema;
 pub use demand_index::DemandIndex;
 pub use demark_pivots::{DemarkPivots, DemarkPivotsOutput};
+pub use depth_slope::DepthSlope;
 pub use detrended_std_dev::DetrendedStdDev;
 pub use doji::Doji;
 pub use donchian::{Donchian, DonchianOutput};
@@ -274,6 +295,7 @@ pub use double_bollinger::{DoubleBollinger, DoubleBollingerOutput};
 pub use dpo::Dpo;
 pub use drawdown_duration::DrawdownDuration;
 pub use ease_of_movement::EaseOfMovement;
+pub use effective_spread::EffectiveSpread;
 pub use ehlers_stochastic::EhlersStochastic;
 pub use elder_impulse::ElderImpulse;
 pub use ema::Ema;
@@ -283,6 +305,7 @@ pub use evwma::Evwma;
 pub use fama::Fama;
 pub use fibonacci_pivots::{FibonacciPivots, FibonacciPivotsOutput};
 pub use fisher_transform::FisherTransform;
+pub use footprint::{Footprint, FootprintLevel, FootprintOutput};
 pub use force_index::ForceIndex;
 pub use fractal_chaos_bands::{FractalChaosBands, FractalChaosBandsOutput};
 pub use frama::Frama;
@@ -312,7 +335,9 @@ pub use keltner::{Keltner, KeltnerOutput};
 pub use kst::{Kst, KstOutput};
 pub use kurtosis::Kurtosis;
 pub use kvo::Kvo;
+pub use kyles_lambda::KylesLambda;
 pub use laguerre_rsi::LaguerreRsi;
+pub use lead_lag_cross_correlation::{LeadLagCrossCorrelation, LeadLagCrossCorrelationOutput};
 pub use linreg::LinearRegression;
 pub use linreg_angle::LinRegAngle;
 pub use linreg_channel::{LinRegChannel, LinRegChannelOutput};
@@ -328,14 +353,20 @@ pub use mcginley_dynamic::McGinleyDynamic;
 pub use median_absolute_deviation::MedianAbsoluteDeviation;
 pub use median_price::MedianPrice;
 pub use mfi::Mfi;
+pub use microprice::Microprice;
 pub use mom::Mom;
 pub use morning_evening_star::MorningEveningStar;
 pub use natr::Natr;
 pub use nvi::Nvi;
+pub use ob_imbalance_full::OrderBookImbalanceFull;
+pub use ob_imbalance_top1::OrderBookImbalanceTop1;
+pub use ob_imbalance_topn::OrderBookImbalanceTopN;
 pub use obv::Obv;
 pub use omega_ratio::OmegaRatio;
 pub use opening_range::{OpeningRange, OpeningRangeOutput};
 pub use pain_index::PainIndex;
+pub use pair_spread_zscore::PairSpreadZScore;
+pub use pairwise_beta::PairwiseBeta;
 pub use parkinson::ParkinsonVolatility;
 pub use pearson_correlation::PearsonCorrelation;
 pub use percent_b::PercentB;
@@ -347,8 +378,11 @@ pub use ppo::Ppo;
 pub use profit_factor::ProfitFactor;
 pub use psar::Psar;
 pub use pvi::Pvi;
+pub use quoted_spread::QuotedSpread;
 pub use r_squared::RSquared;
+pub use realized_spread::RealizedSpread;
 pub use recovery_factor::RecoveryFactor;
+pub use relative_strength_ab::{RelativeStrengthAB, RelativeStrengthOutput};
 pub use renko_trailing_stop::RenkoTrailingStop;
 pub use roc::Roc;
 pub use rogers_satchell::RogersSatchellVolatility;
@@ -359,6 +393,7 @@ pub use rvi_volatility::RviVolatility;
 pub use rwi::{Rwi, RwiOutput};
 pub use sharpe_ratio::SharpeRatio;
 pub use shooting_star::ShootingStar;
+pub use signed_volume::SignedVolume;
 pub use sine_wave::SineWave;
 pub use skewness::Skewness;
 pub use sma::Sma;
@@ -395,6 +430,7 @@ pub use three_inside::ThreeInside;
 pub use three_outside::ThreeOutside;
 pub use three_soldiers_or_crows::ThreeSoldiersOrCrows;
 pub use tii::Tii;
+pub use trade_imbalance::TradeImbalance;
 pub use treynor_ratio::TreynorRatio;
 pub use trima::Trima;
 pub use trix::Trix;
@@ -697,6 +733,24 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "ThreeOutside",
         ],
     ),
+    (
+        "Microstructure",
+        &[
+            "OrderBookImbalanceTop1",
+            "OrderBookImbalanceTopN",
+            "OrderBookImbalanceFull",
+            "Microprice",
+            "QuotedSpread",
+            "DepthSlope",
+            "SignedVolume",
+            "CumulativeVolumeDelta",
+            "TradeImbalance",
+            "EffectiveSpread",
+            "RealizedSpread",
+            "KylesLambda",
+            "Footprint",
+        ],
+    ),
     (
         "Market Profile",
         &["ValueArea", "InitialBalance", "OpeningRange"],
@@ -751,6 +805,6 @@ mod family_tests {
         // the actual indicator count is the early-warning signal that an
         // indicator was added without being assigned a family.
         let total: usize = FAMILIES.iter().map(|(_, ns)| ns.len()).sum();
-        assert_eq!(total, 214, "FAMILIES total drifted from indicator count");
+        assert_eq!(total, 227, "FAMILIES total drifted from indicator count");
     }
 }

crates/wickra-core/src/indicators/morning_evening_star.rs

@@ -18,6 +18,13 @@ use crate::traits::Indicator;
 /// trend filter is applied; combine with a trend indicator for actionable
 /// signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/ob_imbalance_full.rs

@@ -0,0 +1,157 @@
+//! Order-Book Imbalance over the full visible depth.
+
+use crate::microstructure::OrderBook;
+use crate::traits::Indicator;
+
+/// Order-Book Imbalance aggregated over the full visible depth of each side.
+///
+/// Sums the resting size of every bid level and every ask level in the
+/// snapshot and compares them:
+///
+/// ```text
+/// bidDepth  = Σ size of all bids
+/// askDepth  = Σ size of all asks
+/// imbalance = (bidDepth − askDepth) / (bidDepth + askDepth)
+/// ```
+///
+/// The output lies in `[−1, +1]`. A book with zero total size yields `0`. Use
+/// [`crate::OrderBookImbalanceTopN`] to bound the depth to the most relevant
+/// near-touch levels instead of the full visible book.
+///
+/// `Input = OrderBook`, `Output = f64`. Stateless; ready after the first
+/// snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Level, OrderBook, OrderBookImbalanceFull};
+///
+/// let book = OrderBook::new(
+///     vec![Level::new(100.0, 2.0).unwrap(), Level::new(99.0, 1.0).unwrap()],
+///     vec![Level::new(101.0, 0.5).unwrap(), Level::new(102.0, 0.5).unwrap()],
+/// )
+/// .unwrap();
+/// let mut obi = OrderBookImbalanceFull::new();
+/// assert_eq!(obi.update(book), Some(0.5)); // (3 − 1) / (3 + 1)
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct OrderBookImbalanceFull {
+    has_emitted: bool,
+}
+
+impl OrderBookImbalanceFull {
+    /// Construct a new full-depth imbalance indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for OrderBookImbalanceFull {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let bid_depth: f64 = book.bids.iter().map(|l| l.size).sum();
+        let ask_depth: f64 = book.asks.iter().map(|l| l.size).sum();
+        let total = bid_depth + ask_depth;
+        if total <= 0.0 {
+            return Some(0.0);
+        }
+        Some((bid_depth - ask_depth) / 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 {
+        "OrderBookImbalanceFull"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Level;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let obi = OrderBookImbalanceFull::new();
+        assert_eq!(obi.name(), "OrderBookImbalanceFull");
+        assert_eq!(obi.warmup_period(), 1);
+        assert!(!obi.is_ready());
+    }
+
+    #[test]
+    fn sums_full_depth() {
+        let mut obi = OrderBookImbalanceFull::new();
+        let b = book(&[(100.0, 2.0), (99.0, 2.0)], &[(101.0, 1.0), (102.0, 1.0)]);
+        // bidDepth 4, askDepth 2 -> (4 - 2) / 6 = 1/3.
+        assert_eq!(obi.update(b), Some(1.0 / 3.0));
+        assert!(obi.is_ready());
+    }
+
+    #[test]
+    fn ask_heavy_full_depth_is_negative() {
+        let mut obi = OrderBookImbalanceFull::new();
+        let b = book(&[(100.0, 1.0)], &[(101.0, 2.0), (102.0, 1.0)]);
+        // (1 - 3) / 4 = -0.5.
+        assert_eq!(obi.update(b), Some(-0.5));
+    }
+
+    #[test]
+    fn zero_size_is_zero() {
+        let mut obi = OrderBookImbalanceFull::new();
+        assert_eq!(
+            obi.update(book(&[(100.0, 0.0)], &[(101.0, 0.0)])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let bid = 1.0 + f64::from(i % 3);
+                book(&[(100.0, bid), (99.0, 1.0)], &[(101.0, 2.0), (102.0, 1.0)])
+            })
+            .collect();
+        let mut a = OrderBookImbalanceFull::new();
+        let mut b = OrderBookImbalanceFull::new();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut obi = OrderBookImbalanceFull::new();
+        obi.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)]));
+        assert!(obi.is_ready());
+        obi.reset();
+        assert!(!obi.is_ready());
+    }
+}

crates/wickra-core/src/indicators/ob_imbalance_top1.rs

@@ -0,0 +1,176 @@
+//! Order-Book Imbalance at the top of book.
+
+use crate::microstructure::OrderBook;
+use crate::traits::Indicator;
+
+/// Order-Book Imbalance (top-of-book).
+///
+/// Measures the pressure between the best bid and best ask by comparing their
+/// resting sizes:
+///
+/// ```text
+/// imbalance = (bidSize₁ − askSize₁) / (bidSize₁ + askSize₁)
+/// ```
+///
+/// The output lies in `[−1, +1]`: `+1` means all size sits on the bid (buy
+/// pressure), `−1` means all size sits on the ask (sell pressure), `0` means a
+/// balanced top of book. A book with zero size on both top levels yields `0`.
+///
+/// `Input = OrderBook`, `Output = f64`. The indicator is stateless and ready
+/// after the first snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Level, OrderBook, OrderBookImbalanceTop1};
+///
+/// let book = OrderBook::new(
+///     vec![Level::new(100.0, 3.0).unwrap()],
+///     vec![Level::new(101.0, 1.0).unwrap()],
+/// )
+/// .unwrap();
+/// let mut obi = OrderBookImbalanceTop1::new();
+/// assert_eq!(obi.update(book), Some(0.5)); // (3 − 1) / (3 + 1)
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct OrderBookImbalanceTop1 {
+    has_emitted: bool,
+}
+
+impl OrderBookImbalanceTop1 {
+    /// Construct a new top-of-book imbalance indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for OrderBookImbalanceTop1 {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let (Some(bid), Some(ask)) = (book.best_bid(), book.best_ask()) else {
+            return Some(0.0);
+        };
+        let total = bid.size + ask.size;
+        if total <= 0.0 {
+            return Some(0.0);
+        }
+        Some((bid.size - ask.size) / 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 {
+        "OrderBookImbalanceTop1"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Level;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let obi = OrderBookImbalanceTop1::new();
+        assert_eq!(obi.name(), "OrderBookImbalanceTop1");
+        assert_eq!(obi.warmup_period(), 1);
+        assert!(!obi.is_ready());
+    }
+
+    #[test]
+    fn balanced_top_is_zero() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            obi.update(book(&[(100.0, 2.0)], &[(101.0, 2.0)])),
+            Some(0.0)
+        );
+        assert!(obi.is_ready());
+    }
+
+    #[test]
+    fn bid_heavy_is_positive() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            obi.update(book(&[(100.0, 3.0)], &[(101.0, 1.0)])),
+            Some(0.5)
+        );
+    }
+
+    #[test]
+    fn ask_heavy_is_negative() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            obi.update(book(&[(100.0, 1.0)], &[(101.0, 3.0)])),
+            Some(-0.5)
+        );
+    }
+
+    #[test]
+    fn zero_size_top_is_zero() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            obi.update(book(&[(100.0, 0.0)], &[(101.0, 0.0)])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn empty_book_is_zero() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            obi.update(OrderBook::new_unchecked(vec![], vec![])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let bid = 1.0 + f64::from(i % 5);
+                book(&[(100.0, bid)], &[(101.0, 2.0)])
+            })
+            .collect();
+        let mut a = OrderBookImbalanceTop1::new();
+        let mut b = OrderBookImbalanceTop1::new();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut obi = OrderBookImbalanceTop1::new();
+        obi.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)]));
+        assert!(obi.is_ready());
+        obi.reset();
+        assert!(!obi.is_ready());
+    }
+}

crates/wickra-core/src/indicators/ob_imbalance_topn.rs

@@ -0,0 +1,186 @@
+//! Order-Book Imbalance over the top-N levels.
+
+use crate::error::{Error, Result};
+use crate::microstructure::OrderBook;
+use crate::traits::Indicator;
+
+/// Order-Book Imbalance aggregated over the top-N levels of each side.
+///
+/// Generalises [`crate::OrderBookImbalanceTop1`] to a configurable depth: it
+/// sums the resting size of the best `levels` bids and the best `levels` asks
+/// and compares them:
+///
+/// ```text
+/// bidDepth  = Σ size of the best `levels` bids
+/// askDepth  = Σ size of the best `levels` asks
+/// imbalance = (bidDepth − askDepth) / (bidDepth + askDepth)
+/// ```
+///
+/// If a side has fewer than `levels` levels, all available levels are summed.
+/// The output lies in `[−1, +1]`; a book with zero size across the summed
+/// levels yields `0`.
+///
+/// `Input = OrderBook`, `Output = f64`. Stateless; ready after the first
+/// snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Level, OrderBook, OrderBookImbalanceTopN};
+///
+/// let book = OrderBook::new(
+///     vec![Level::new(100.0, 2.0).unwrap(), Level::new(99.0, 1.0).unwrap()],
+///     vec![Level::new(101.0, 1.0).unwrap(), Level::new(102.0, 1.0).unwrap()],
+/// )
+/// .unwrap();
+/// let mut obi = OrderBookImbalanceTopN::new(2).unwrap();
+/// assert_eq!(obi.update(book), Some(0.2)); // (3 − 2) / (3 + 2)
+/// ```
+#[derive(Debug, Clone)]
+pub struct OrderBookImbalanceTopN {
+    levels: usize,
+    has_emitted: bool,
+}
+
+impl OrderBookImbalanceTopN {
+    /// Construct a top-N imbalance indicator.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `levels` is zero.
+    pub fn new(levels: usize) -> Result<Self> {
+        if levels == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            levels,
+            has_emitted: false,
+        })
+    }
+
+    /// The configured number of levels summed per side.
+    pub fn levels(&self) -> usize {
+        self.levels
+    }
+}
+
+impl Indicator for OrderBookImbalanceTopN {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let bid_depth: f64 = book.bids.iter().take(self.levels).map(|l| l.size).sum();
+        let ask_depth: f64 = book.asks.iter().take(self.levels).map(|l| l.size).sum();
+        let total = bid_depth + ask_depth;
+        if total <= 0.0 {
+            return Some(0.0);
+        }
+        Some((bid_depth - ask_depth) / 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 {
+        "OrderBookImbalanceTopN"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Level;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_levels() {
+        assert!(matches!(
+            OrderBookImbalanceTopN::new(0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let obi = OrderBookImbalanceTopN::new(3).unwrap();
+        assert_eq!(obi.name(), "OrderBookImbalanceTopN");
+        assert_eq!(obi.warmup_period(), 1);
+        assert_eq!(obi.levels(), 3);
+        assert!(!obi.is_ready());
+    }
+
+    #[test]
+    fn sums_top_two_levels() {
+        let mut obi = OrderBookImbalanceTopN::new(2).unwrap();
+        let b = book(&[(100.0, 2.0), (99.0, 1.0)], &[(101.0, 1.0), (102.0, 1.0)]);
+        // bidDepth 3, askDepth 2 -> (3 - 2) / 5 = 0.2.
+        assert_eq!(obi.update(b), Some(0.2));
+        assert!(obi.is_ready());
+    }
+
+    #[test]
+    fn caps_at_available_depth() {
+        // Only one level per side, N = 5 -> uses what exists.
+        let mut obi = OrderBookImbalanceTopN::new(5).unwrap();
+        assert_eq!(
+            obi.update(book(&[(100.0, 3.0)], &[(101.0, 1.0)])),
+            Some(0.5)
+        );
+    }
+
+    #[test]
+    fn zero_size_is_zero() {
+        let mut obi = OrderBookImbalanceTopN::new(2).unwrap();
+        assert_eq!(
+            obi.update(book(&[(100.0, 0.0)], &[(101.0, 0.0)])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let ask = 1.0 + f64::from(i % 4);
+                book(&[(100.0, 2.0), (99.0, 1.0)], &[(101.0, ask), (102.0, 1.0)])
+            })
+            .collect();
+        let mut a = OrderBookImbalanceTopN::new(2).unwrap();
+        let mut b = OrderBookImbalanceTopN::new(2).unwrap();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut obi = OrderBookImbalanceTopN::new(2).unwrap();
+        obi.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)]));
+        assert!(obi.is_ready());
+        obi.reset();
+        assert!(!obi.is_ready());
+    }
+}

crates/wickra-core/src/indicators/pair_spread_zscore.rs

@@ -0,0 +1,299 @@
+//! Pair Spread Z-Score — the standardised log-spread of two cointegrated assets.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Z-score of the log-spread `ln(a) − β·ln(b)` between two assets.
+///
+/// This is the canonical mean-reversion / statistical-arbitrage signal for a
+/// pair. Each `update` receives one `(a, b)` pair of raw **prices** and the
+/// indicator does two things:
+///
+/// 1. **Hedge ratio.** A rolling ordinary-least-squares regression of
+///    `ln(a)` on `ln(b)` over the trailing `beta_period` samples gives the
+///    slope `β = cov(ln a, ln b) / var(ln b)`. The instantaneous spread is the
+///    residual against the origin, `s = ln(a) − β·ln(b)`.
+/// 2. **Standardisation.** The spread is then z-scored over the trailing
+///    `z_period` spreads: `z = (s − mean_s) / std_s`.
+///
+/// A large positive `z` means `a` is rich relative to `b` (sell the spread); a
+/// large negative `z` means `a` is cheap (buy the spread); `z` near zero means
+/// the pair is at its typical relationship. The two windows are independent:
+/// `beta_period` controls how much history the hedge ratio adapts over, and
+/// `z_period` controls the look-back for the mean and dispersion of the spread.
+///
+/// Each `update` is O(1): five running sums maintain the rolling OLS and two
+/// more maintain the rolling spread mean/variance. A flat `ln(b)` window has
+/// zero variance and the hedge ratio is undefined; `β` is then taken as `0`,
+/// reducing the spread to `ln(a)`. A flat spread window (zero dispersion)
+/// yields a z-score of `0` rather than `NaN`.
+///
+/// Prices must be strictly positive and finite for the logarithm to be
+/// defined; a non-positive or non-finite price is skipped (it does not enter
+/// either window), exactly as a real feed would discard a bad tick.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, PairSpreadZScore};
+///
+/// let mut zs = PairSpreadZScore::new(2, 2).unwrap();
+/// // A flat benchmark gives hedge ratio 0, so the spread is just ln(a); with
+/// // a 2-sample z-window the z-score collapses to the sign of the last move.
+/// let mut last = None;
+/// for a in [100.0, 100.0, 110.0, 120.0] {
+///     last = zs.update((a, 100.0));
+/// }
+/// assert!((last.unwrap() - 1.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct PairSpreadZScore {
+    beta_period: usize,
+    z_period: usize,
+    // Rolling OLS of y = ln(a) on x = ln(b).
+    reg: VecDeque<(f64, f64)>,
+    sum_x: f64,
+    sum_y: f64,
+    sum_xx: f64,
+    sum_xy: f64,
+    // Rolling mean/variance of the spread.
+    spreads: VecDeque<f64>,
+    sum_s: f64,
+    sum_ss: f64,
+}
+
+impl PairSpreadZScore {
+    /// Construct a new pair spread z-score.
+    ///
+    /// `beta_period` is the look-back for the rolling hedge ratio; `z_period`
+    /// is the look-back for standardising the spread.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if either period is below `2`
+    /// (variance needs at least two points).
+    pub fn new(beta_period: usize, z_period: usize) -> Result<Self> {
+        if beta_period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "pair spread z-score needs beta_period >= 2",
+            });
+        }
+        if z_period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "pair spread z-score needs z_period >= 2",
+            });
+        }
+        Ok(Self {
+            beta_period,
+            z_period,
+            reg: VecDeque::with_capacity(beta_period),
+            sum_x: 0.0,
+            sum_y: 0.0,
+            sum_xx: 0.0,
+            sum_xy: 0.0,
+            spreads: VecDeque::with_capacity(z_period),
+            sum_s: 0.0,
+            sum_ss: 0.0,
+        })
+    }
+
+    /// Look-back of the rolling hedge-ratio regression.
+    pub const fn beta_period(&self) -> usize {
+        self.beta_period
+    }
+
+    /// Look-back of the rolling spread standardisation.
+    pub const fn z_period(&self) -> usize {
+        self.z_period
+    }
+
+    /// The current hedge ratio `β`, or `None` while the regression is warming
+    /// up. A flat `ln(b)` window reports `0`.
+    fn hedge_ratio(&self) -> Option<f64> {
+        if self.reg.len() < self.beta_period {
+            return None;
+        }
+        let n = self.beta_period as f64;
+        let mean_x = self.sum_x / n;
+        let mean_y = self.sum_y / n;
+        let var_x = (self.sum_xx / n - mean_x * mean_x).max(0.0);
+        if var_x == 0.0 {
+            return Some(0.0);
+        }
+        let cov = self.sum_xy / n - mean_x * mean_y;
+        Some(cov / var_x)
+    }
+
+    fn push_spread(&mut self, s: f64) -> Option<f64> {
+        if self.spreads.len() == self.z_period {
+            let old = self.spreads.pop_front().expect("non-empty");
+            self.sum_s -= old;
+            self.sum_ss -= old * old;
+        }
+        self.spreads.push_back(s);
+        self.sum_s += s;
+        self.sum_ss += s * s;
+        if self.spreads.len() < self.z_period {
+            return None;
+        }
+        let m = self.z_period as f64;
+        let mean_s = self.sum_s / m;
+        let var_s = (self.sum_ss / m - mean_s * mean_s).max(0.0);
+        let std_s = var_s.sqrt();
+        if std_s == 0.0 {
+            // A flat spread window has no dispersion to standardise against.
+            return Some(0.0);
+        }
+        Some((s - mean_s) / std_s)
+    }
+}
+
+impl Indicator for PairSpreadZScore {
+    /// `(a, b)` price pair.
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        let (a, b) = input;
+        if !(a > 0.0 && b > 0.0 && a.is_finite() && b.is_finite()) {
+            // Bad tick: skip it without disturbing either window.
+            return None;
+        }
+        let x = b.ln();
+        let y = a.ln();
+        if self.reg.len() == self.beta_period {
+            let (ox, oy) = self.reg.pop_front().expect("non-empty");
+            self.sum_x -= ox;
+            self.sum_y -= oy;
+            self.sum_xx -= ox * ox;
+            self.sum_xy -= ox * oy;
+        }
+        self.reg.push_back((x, y));
+        self.sum_x += x;
+        self.sum_y += y;
+        self.sum_xx += x * x;
+        self.sum_xy += x * y;
+        let beta = self.hedge_ratio()?;
+        let spread = y - beta * x;
+        self.push_spread(spread)
+    }
+
+    fn reset(&mut self) {
+        self.reg.clear();
+        self.sum_x = 0.0;
+        self.sum_y = 0.0;
+        self.sum_xx = 0.0;
+        self.sum_xy = 0.0;
+        self.spreads.clear();
+        self.sum_s = 0.0;
+        self.sum_ss = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // `beta_period` samples to define the hedge ratio (and the first
+        // spread), then `z_period − 1` more to fill the spread window.
+        self.beta_period + self.z_period - 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.spreads.len() == self.z_period
+    }
+
+    fn name(&self) -> &'static str {
+        "PairSpreadZScore"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_periods_below_two() {
+        assert!(PairSpreadZScore::new(1, 5).is_err());
+        assert!(PairSpreadZScore::new(5, 1).is_err());
+        assert!(PairSpreadZScore::new(2, 2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let z = PairSpreadZScore::new(10, 20).unwrap();
+        assert_eq!(z.beta_period(), 10);
+        assert_eq!(z.z_period(), 20);
+        assert_eq!(z.warmup_period(), 29);
+        assert_eq!(z.name(), "PairSpreadZScore");
+    }
+
+    #[test]
+    fn flat_benchmark_two_sample_window_is_sign_of_move() {
+        // Flat b ⇒ β = 0 ⇒ spread = ln(a); z_period = 2 ⇒ z = sign of last move.
+        let mut z = PairSpreadZScore::new(2, 2).unwrap();
+        assert_eq!(z.update((100.0, 100.0)), None);
+        assert_eq!(z.update((100.0, 100.0)), None);
+        // The ±1 result is exact in real arithmetic; the variance is computed
+        // via Σs²−mean² so a few ulps of cancellation error remain.
+        assert_relative_eq!(z.update((110.0, 100.0)).unwrap(), 1.0, epsilon = 1e-9);
+        assert_relative_eq!(z.update((105.0, 100.0)).unwrap(), -1.0, epsilon = 1e-9);
+        assert_relative_eq!(z.update((130.0, 100.0)).unwrap(), 1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn constant_spread_yields_zero() {
+        // Both legs flat ⇒ spread constant ⇒ zero dispersion ⇒ z = 0.
+        let pairs: Vec<(f64, f64)> = (0..10).map(|_| (50.0, 100.0)).collect();
+        let last = PairSpreadZScore::new(3, 4)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn bad_tick_is_skipped() {
+        let mut z = PairSpreadZScore::new(2, 2).unwrap();
+        // A non-positive or non-finite price never enters the windows.
+        assert_eq!(z.update((0.0, 100.0)), None);
+        assert_eq!(z.update((100.0, f64::NAN)), None);
+        assert!(!z.is_ready());
+        // Valid ticks then warm the indicator normally.
+        z.update((100.0, 100.0));
+        z.update((100.0, 100.0));
+        z.update((110.0, 100.0));
+        assert!(z.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut z = PairSpreadZScore::new(3, 3).unwrap();
+        for i in 0..10 {
+            let b = 100.0 + 5.0 * f64::from(i).sin();
+            z.update((b * 1.5, b));
+        }
+        assert!(z.is_ready());
+        z.reset();
+        assert!(!z.is_ready());
+        assert_eq!(z.update((100.0, 100.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..80)
+            .map(|i| {
+                let t = f64::from(i);
+                let b = 100.0 + 10.0 * (t * 0.2).sin();
+                let a = b * (1.0 + 0.05 * (t * 0.5).cos());
+                (a, b)
+            })
+            .collect();
+        let batch = PairSpreadZScore::new(14, 10).unwrap().batch(&pairs);
+        let mut z = PairSpreadZScore::new(14, 10).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| z.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/pairwise_beta.rs

@@ -0,0 +1,292 @@
+//! Pairwise Beta — rolling OLS slope of one asset's log-returns on another's.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Rolling Beta of asset `a`'s **log-returns** on asset `b`'s log-returns.
+///
+/// Each `update` receives one `(a, b)` pair of raw **prices**. Internally the
+/// indicator differences consecutive prices into log-returns
+/// `rₜ = ln(pₜ / pₜ₋₁)` and runs a rolling ordinary-least-squares regression of
+/// `a`'s returns on `b`'s returns over the trailing window of `period` return
+/// pairs:
+///
+/// ```text
+/// cov_ab = (1/n) · Σ rₐ·r_b − r̄ₐ·r̄_b
+/// var_b  = (1/n) · Σ r_b²   − r̄_b²
+/// Beta   = cov_ab / var_b
+/// ```
+///
+/// This is the slope of the OLS line and measures how much asset `a` moves, in
+/// return space, for a unit return of asset `b`. A reading of `1.0` means the
+/// two move together one-for-one; `2.0` means `a` typically doubles `b`'s
+/// moves; negative readings signal an inverse relationship and the basis for a
+/// hedge.
+///
+/// This differs from [`crate::Beta`], which regresses the raw inputs it is
+/// fed. `PairwiseBeta` always works in return space: feed it raw price levels
+/// and it computes the returns for you, which is the conventional way to
+/// measure cross-asset Beta (a Beta on price *levels* is dominated by the
+/// shared trend and rarely what you want).
+///
+/// Each `update` is O(1): four running sums (`Σrₐ`, `Σr_b`, `Σr_b²`,
+/// `Σrₐ·r_b`) are maintained as the window of returns slides. A flat `b`
+/// window has zero return variance and Beta is undefined; the indicator
+/// returns `0` in that case rather than producing `NaN`.
+///
+/// Prices must be strictly positive and finite for the log-return to be
+/// defined. A non-positive or non-finite price breaks the return chain: that
+/// sample is dropped and the next valid price re-seeds the previous-price
+/// reference, exactly as a real feed would resume after a bad tick.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, PairwiseBeta};
+///
+/// let mut indicator = PairwiseBeta::new(10).unwrap();
+/// let mut last = None;
+/// for i in 0..30 {
+///     // A varying (non-constant-return) positive price path.
+///     let b = 100.0 + 10.0 * (f64::from(i) * 0.5).sin();
+///     // `a = b²`, so a's log-returns are exactly twice b's.
+///     last = indicator.update((b * b, b));
+/// }
+/// assert!((last.unwrap() - 2.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct PairwiseBeta {
+    period: usize,
+    prev: Option<(f64, f64)>,
+    window: VecDeque<(f64, f64)>,
+    sum_a: f64,
+    sum_b: f64,
+    sum_bb: f64,
+    sum_ab: f64,
+}
+
+impl PairwiseBeta {
+    /// Construct a new rolling pairwise Beta over `period` return pairs.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` (variance needs at
+    /// least two returns).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "pairwise beta needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            prev: None,
+            window: VecDeque::with_capacity(period),
+            sum_a: 0.0,
+            sum_b: 0.0,
+            sum_bb: 0.0,
+            sum_ab: 0.0,
+        })
+    }
+
+    /// Configured period (number of return pairs in the rolling window).
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn push_return(&mut self, ra: f64, rb: f64) -> Option<f64> {
+        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((ra, rb));
+        self.sum_a += ra;
+        self.sum_b += rb;
+        self.sum_bb += rb * rb;
+        self.sum_ab += ra * rb;
+        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 cov = self.sum_ab / n - mean_a * mean_b;
+        if var_b == 0.0 {
+            // A flat benchmark-return window has no defined beta.
+            return Some(0.0);
+        }
+        Some(cov / var_b)
+    }
+}
+
+impl Indicator for PairwiseBeta {
+    /// `(a, b)` price pair.
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        let (a, b) = input;
+        if !(a > 0.0 && b > 0.0 && a.is_finite() && b.is_finite()) {
+            // Bad tick: drop it and restart the return chain.
+            self.prev = None;
+            return None;
+        }
+        let Some((pa, pb)) = self.prev else {
+            self.prev = Some((a, b));
+            return None;
+        };
+        self.prev = Some((a, b));
+        let ra = (a / pa).ln();
+        let rb = (b / pb).ln();
+        self.push_return(ra, rb)
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        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 {
+        // One prior price to seed, then `period` return pairs.
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "PairwiseBeta"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(PairwiseBeta::new(0).is_err());
+        assert!(PairwiseBeta::new(1).is_err());
+        assert!(PairwiseBeta::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let b = PairwiseBeta::new(14).unwrap();
+        assert_eq!(b.period(), 14);
+        assert_eq!(b.warmup_period(), 15);
+        assert_eq!(b.name(), "PairwiseBeta");
+    }
+
+    #[test]
+    fn squared_price_gives_beta_two() {
+        // a = b² ⇒ a's log-returns are exactly 2× b's ⇒ beta = 2.
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|i| {
+                let b = 100.0 + 10.0 * (f64::from(i) * 0.5).sin();
+                (b * b, b)
+            })
+            .collect();
+        let last = PairwiseBeta::new(5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 2.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn inverse_price_gives_beta_minus_one() {
+        // a = 1/b ⇒ a's log-returns are −1× b's ⇒ beta = −1.
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|i| {
+                let b = 100.0 + 10.0 * (f64::from(i) * 0.5).sin();
+                (1.0 / b, b)
+            })
+            .collect();
+        let last = PairwiseBeta::new(5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, -1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn flat_benchmark_returns_zero() {
+        // b constant ⇒ zero return variance ⇒ beta defined as 0.
+        let pairs: Vec<(f64, f64)> = (0..10).map(|i| (100.0 * 1.01_f64.powi(i), 7.0)).collect();
+        let last = PairwiseBeta::new(5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn bad_tick_breaks_return_chain() {
+        let mut b = PairwiseBeta::new(3).unwrap();
+        // Seed, one good return, then a non-positive price drops the chain.
+        assert_eq!(b.update((100.0, 100.0)), None);
+        assert_eq!(b.update((101.0, 101.0)), None);
+        assert_eq!(b.update((0.0, 50.0)), None); // bad tick, prev reset
+        assert!(!b.is_ready());
+        // A non-finite price is rejected the same way.
+        assert_eq!(b.update((f64::NAN, 50.0)), None);
+        assert!(!b.is_ready());
+        // Recovery: subsequent valid prices rebuild the window cleanly.
+        for i in 0..5 {
+            let p = 100.0 * 1.01_f64.powi(i);
+            b.update((p * p, p));
+        }
+        assert!(b.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut b = PairwiseBeta::new(3).unwrap();
+        for i in 0..6 {
+            let p = 100.0 * 1.01_f64.powi(i);
+            b.update((p * p, p));
+        }
+        assert!(b.is_ready());
+        b.reset();
+        assert!(!b.is_ready());
+        assert_eq!(b.update((100.0, 100.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|i| {
+                let t = f64::from(i);
+                let b = 100.0 + 5.0 * t.sin();
+                let a = 100.0 + 3.0 * t.sin() + 0.5 * t.cos();
+                (a, b)
+            })
+            .collect();
+        let batch = PairwiseBeta::new(14).unwrap().batch(&pairs);
+        let mut b = PairwiseBeta::new(14).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| b.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/piercing_dark_cloud.rs

@@ -26,6 +26,13 @@ use crate::traits::Indicator;
 /// only — no trend filter is applied; combine with a trend indicator for
 /// actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/quoted_spread.rs

@@ -0,0 +1,153 @@
+//! Quoted Spread — top-of-book spread in basis points.
+
+use crate::microstructure::OrderBook;
+use crate::traits::Indicator;
+
+/// Quoted Spread — the top-of-book bid-ask spread expressed in basis points of
+/// the mid price.
+///
+/// ```text
+/// mid           = (bidPrice₁ + askPrice₁) / 2
+/// quotedSpread  = (askPrice₁ − bidPrice₁) / mid · 10_000   (bps)
+/// ```
+///
+/// This is the round-trip cost of crossing the spread at the touch, normalised
+/// by price so it is comparable across instruments. For a valid (uncrossed)
+/// book the result is non-negative. An empty book yields `0`.
+///
+/// `Input = OrderBook`, `Output = f64`. Stateless; ready after the first
+/// snapshot.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Level, OrderBook, QuotedSpread};
+///
+/// let book = OrderBook::new(
+///     vec![Level::new(100.0, 1.0).unwrap()],
+///     vec![Level::new(100.5, 1.0).unwrap()],
+/// )
+/// .unwrap();
+/// let mut qs = QuotedSpread::new();
+/// // spread 0.5, mid 100.25 -> 0.5 / 100.25 * 10_000 ≈ 49.875 bps.
+/// let bps = qs.update(book).unwrap();
+/// assert!((bps - 49.875_311_72).abs() < 1e-6);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct QuotedSpread {
+    has_emitted: bool,
+}
+
+impl QuotedSpread {
+    /// Construct a new quoted-spread indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for QuotedSpread {
+    type Input = OrderBook;
+    type Output = f64;
+
+    fn update(&mut self, book: OrderBook) -> Option<f64> {
+        self.has_emitted = true;
+        let (Some(bid), Some(ask)) = (book.best_bid(), book.best_ask()) else {
+            return Some(0.0);
+        };
+        let mid = f64::midpoint(bid.price, ask.price);
+        Some((ask.price - bid.price) / mid * 10_000.0)
+    }
+
+    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 {
+        "QuotedSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Level;
+    use crate::traits::BatchExt;
+
+    fn book(bids: &[(f64, f64)], asks: &[(f64, f64)]) -> OrderBook {
+        let to_levels = |xs: &[(f64, f64)]| {
+            xs.iter()
+                .map(|&(p, s)| Level::new(p, s).unwrap())
+                .collect::<Vec<_>>()
+        };
+        OrderBook::new(to_levels(bids), to_levels(asks)).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let qs = QuotedSpread::new();
+        assert_eq!(qs.name(), "QuotedSpread");
+        assert_eq!(qs.warmup_period(), 1);
+        assert!(!qs.is_ready());
+    }
+
+    #[test]
+    fn known_value_in_bps() {
+        let mut qs = QuotedSpread::new();
+        // spread 1.0, mid 100.5 -> 1 / 100.5 * 10_000 ≈ 99.5025 bps.
+        let bps = qs.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)])).unwrap();
+        assert!((bps - 99.502_487_56).abs() < 1e-6);
+        assert!(qs.is_ready());
+    }
+
+    #[test]
+    fn tight_book_is_small() {
+        let mut qs = QuotedSpread::new();
+        let bps = qs.update(book(&[(100.0, 1.0)], &[(100.01, 1.0)])).unwrap();
+        assert!(bps > 0.0 && bps < 2.0);
+    }
+
+    #[test]
+    fn empty_book_is_zero() {
+        let mut qs = QuotedSpread::new();
+        assert_eq!(
+            qs.update(OrderBook::new_unchecked(vec![], vec![])),
+            Some(0.0)
+        );
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let books: Vec<OrderBook> = (0..20)
+            .map(|i| {
+                let ask = 100.5 + f64::from(i % 4) * 0.1;
+                book(&[(100.0, 1.0)], &[(ask, 1.0)])
+            })
+            .collect();
+        let mut a = QuotedSpread::new();
+        let mut b = QuotedSpread::new();
+        assert_eq!(
+            a.batch(&books),
+            books
+                .iter()
+                .map(|x| b.update(x.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut qs = QuotedSpread::new();
+        qs.update(book(&[(100.0, 1.0)], &[(101.0, 1.0)]));
+        assert!(qs.is_ready());
+        qs.reset();
+        assert!(!qs.is_ready());
+    }
+}

crates/wickra-core/src/indicators/realized_spread.rs

@@ -0,0 +1,204 @@
+//! Realized Spread — the post-trade liquidity revenue of a trade in basis
+//! points.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::microstructure::TradeQuote;
+use crate::traits::Indicator;
+
+/// Realized Spread — twice the signed deviation of a trade price from the mid
+/// that prevails `horizon` trades *later*, expressed in basis points of the
+/// trade's contemporaneous mid.
+///
+/// ```text
+/// realizedSpread = 2 · D · (tradePrice − mid_{t+horizon}) / mid_t · 10_000   (bps)
+/// ```
+///
+/// where `D` is the aggressor sign (`+1` for a buy, `−1` for a sell), `mid_t`
+/// is the mid at the time of the trade, and `mid_{t+horizon}` is the mid
+/// `horizon` trade-quotes later. Where the [effective spread] measures the full
+/// cost paid by the aggressor against the contemporaneous mid, the realized
+/// spread measures the share of that cost a liquidity provider *keeps* after
+/// the mid has moved: it is the effective spread net of the price impact
+/// (`effective = realized + 2 · priceImpact`). A high realized spread means
+/// the quote was not picked off; a low or negative one is the signature of
+/// adverse selection, the trade preceding a move in its own direction.
+///
+/// The indicator buffers each incoming trade-quote and emits the realized
+/// spread for the trade made `horizon` updates ago, once that future mid is
+/// known. It warms up for `horizon + 1` trade-quotes — `update` returns `None`
+/// until the first trade can be resolved — and then emits one value per update
+/// in O(1).
+///
+/// `Input = TradeQuote`, `Output = f64`.
+///
+/// [effective spread]: crate::EffectiveSpread
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, RealizedSpread, Side, Trade, TradeQuote};
+///
+/// let mut rs = RealizedSpread::new(1).unwrap();
+/// let tq = |price: f64, side, mid| TradeQuote::new(Trade::new(price, 1.0, side, 0).unwrap(), mid).unwrap();
+/// // First trade buffered; nothing to resolve yet.
+/// assert_eq!(rs.update(tq(100.10, Side::Buy, 100.0)), None);
+/// // One trade later the mid is 100.20, resolving the first buy:
+/// // 2 · (+1) · (100.10 − 100.20) / 100.0 · 10_000 = −20 bps (adverse selection).
+/// let out = rs.update(tq(99.90, Side::Sell, 100.20)).unwrap();
+/// assert!((out - (-20.0)).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct RealizedSpread {
+    horizon: usize,
+    // Each pending entry is (aggressor sign, trade price, contemporaneous mid).
+    pending: VecDeque<(f64, f64, f64)>,
+    has_emitted: bool,
+}
+
+impl RealizedSpread {
+    /// Construct a realized-spread indicator that resolves each trade against
+    /// the mid `horizon` trade-quotes later.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `horizon` is zero (the realized spread
+    /// is defined against a strictly future mid).
+    pub fn new(horizon: usize) -> Result<Self> {
+        if horizon == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            horizon,
+            pending: VecDeque::with_capacity(horizon + 1),
+            has_emitted: false,
+        })
+    }
+
+    /// The configured horizon, in trade-quotes.
+    pub const fn horizon(&self) -> usize {
+        self.horizon
+    }
+}
+
+impl Indicator for RealizedSpread {
+    type Input = TradeQuote;
+    type Output = f64;
+
+    fn update(&mut self, quote: TradeQuote) -> Option<f64> {
+        let sign = quote.trade.side.sign();
+        self.pending.push_back((sign, quote.trade.price, quote.mid));
+        if self.pending.len() <= self.horizon {
+            return None;
+        }
+        let (old_sign, old_price, old_mid) = self.pending.pop_front().expect("len > horizon >= 1");
+        self.has_emitted = true;
+        // `quote.mid` is the mid prevailing `horizon` trades after the resolved
+        // trade; normalise by that trade's own contemporaneous mid.
+        Some(2.0 * old_sign * (old_price - quote.mid) / old_mid * 10_000.0)
+    }
+
+    fn reset(&mut self) {
+        self.pending.clear();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.horizon + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "RealizedSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::{Side, Trade};
+    use crate::traits::BatchExt;
+
+    fn tq(price: f64, side: Side, mid: f64) -> TradeQuote {
+        TradeQuote::new(Trade::new(price, 1.0, side, 0).unwrap(), mid).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_horizon() {
+        assert!(matches!(RealizedSpread::new(0), Err(Error::PeriodZero)));
+        assert!(RealizedSpread::new(1).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let rs = RealizedSpread::new(3).unwrap();
+        assert_eq!(rs.name(), "RealizedSpread");
+        assert_eq!(rs.horizon(), 3);
+        assert_eq!(rs.warmup_period(), 4);
+        assert!(!rs.is_ready());
+    }
+
+    #[test]
+    fn resolves_against_future_mid() {
+        let mut rs = RealizedSpread::new(1).unwrap();
+        assert_eq!(rs.update(tq(100.10, Side::Buy, 100.0)), None);
+        assert!(!rs.is_ready());
+        // 2 · (+1) · (100.10 − 100.20) / 100.0 · 10_000 = −20 bps.
+        let out = rs.update(tq(99.90, Side::Sell, 100.20)).unwrap();
+        assert!((out - (-20.0)).abs() < 1e-9);
+        assert!(rs.is_ready());
+    }
+
+    #[test]
+    fn no_adverse_move_equals_effective_spread() {
+        // If the mid does not move over the horizon, realized == effective.
+        let mut rs = RealizedSpread::new(1).unwrap();
+        rs.update(tq(100.05, Side::Buy, 100.0));
+        // mid stays at 100.0 -> 2 · (100.05 − 100.0) / 100.0 · 10_000 = 10 bps.
+        let out = rs.update(tq(100.0, Side::Buy, 100.0)).unwrap();
+        assert!((out - 10.0).abs() < 1e-9);
+    }
+
+    #[test]
+    fn longer_horizon_warms_up() {
+        let mut rs = RealizedSpread::new(3).unwrap();
+        for _ in 0..3 {
+            assert_eq!(rs.update(tq(100.0, Side::Buy, 100.0)), None);
+        }
+        assert!(!rs.is_ready());
+        assert!(rs.update(tq(100.0, Side::Buy, 100.0)).is_some());
+        assert!(rs.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let quotes: Vec<TradeQuote> = (0..30)
+            .map(|i| {
+                let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+                let mid = 100.0 + f64::from(i % 5) * 0.05;
+                tq(mid + 0.02, side, mid)
+            })
+            .collect();
+        let mut a = RealizedSpread::new(4).unwrap();
+        let mut b = RealizedSpread::new(4).unwrap();
+        assert_eq!(
+            a.batch(&quotes),
+            quotes.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut rs = RealizedSpread::new(1).unwrap();
+        rs.update(tq(100.05, Side::Buy, 100.0));
+        rs.update(tq(100.0, Side::Buy, 100.0));
+        assert!(rs.is_ready());
+        rs.reset();
+        assert!(!rs.is_ready());
+        assert_eq!(rs.update(tq(100.05, Side::Buy, 100.0)), None);
+    }
+}

crates/wickra-core/src/indicators/relative_strength_ab.rs

@@ -0,0 +1,233 @@
+//! Relative Strength A-vs-B — the price ratio of two assets, plus its MA and RSI.
+
+use crate::error::Result;
+use crate::indicators::{Rsi, Sma};
+use crate::traits::Indicator;
+
+/// Output of [`RelativeStrengthAB`].
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct RelativeStrengthOutput {
+    /// The raw relative-strength ratio `a / b`.
+    pub ratio: f64,
+    /// Simple moving average of the ratio over `ma_period`.
+    pub ratio_ma: f64,
+    /// Relative Strength Index of the ratio over `rsi_period`.
+    pub ratio_rsi: f64,
+}
+
+/// Comparative relative strength of asset `a` against asset `b`.
+///
+/// Each `update` receives one `(a, b)` price pair and forms the **ratio line**
+/// `a / b`. The ratio is then smoothed with a simple moving average and run
+/// through an RSI, so a single indicator gives you the relative-strength level,
+/// its trend, and whether that trend is overbought or oversold:
+///
+/// ```text
+/// ratio     = a / b
+/// ratio_ma  = SMA(ratio, ma_period)
+/// ratio_rsi = RSI(ratio, rsi_period)
+/// ```
+///
+/// A rising ratio means `a` is outperforming `b`; `ratio_ma` shows the trend of
+/// that outperformance and `ratio_rsi` flags exhaustion (e.g. `> 70` after a
+/// strong run of `a` over `b`). This is the classic "asset-vs-asset" or
+/// "asset-vs-index" rotation screen.
+///
+/// The first output appears once both the moving average and the RSI have
+/// warmed up; the ratio itself is computed from the first valid pair. A
+/// non-finite price or a zero denominator (`b == 0`) makes the ratio undefined
+/// and is skipped, leaving the internal averages untouched.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, RelativeStrengthAB};
+///
+/// let mut rs = RelativeStrengthAB::new(5, 5).unwrap();
+/// let mut last = None;
+/// for _ in 0..20 {
+///     last = rs.update((200.0, 100.0)); // ratio is a constant 2.0
+/// }
+/// let out = last.unwrap();
+/// assert!((out.ratio - 2.0).abs() < 1e-12);
+/// assert!((out.ratio_ma - 2.0).abs() < 1e-12);
+/// // A flat ratio has no gains or losses, so its RSI sits at the neutral 50.
+/// assert!((out.ratio_rsi - 50.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct RelativeStrengthAB {
+    ma_period: usize,
+    rsi_period: usize,
+    ma: Sma,
+    rsi: Rsi,
+}
+
+impl RelativeStrengthAB {
+    /// Construct a new comparative relative-strength indicator.
+    ///
+    /// `ma_period` is the moving-average look-back of the ratio; `rsi_period`
+    /// is the RSI look-back of the ratio.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`](crate::Error::PeriodZero) if either period
+    /// is zero.
+    pub fn new(ma_period: usize, rsi_period: usize) -> Result<Self> {
+        Ok(Self {
+            ma_period,
+            rsi_period,
+            ma: Sma::new(ma_period)?,
+            rsi: Rsi::new(rsi_period)?,
+        })
+    }
+
+    /// Moving-average look-back of the ratio.
+    pub const fn ma_period(&self) -> usize {
+        self.ma_period
+    }
+
+    /// RSI look-back of the ratio.
+    pub const fn rsi_period(&self) -> usize {
+        self.rsi_period
+    }
+}
+
+impl Indicator for RelativeStrengthAB {
+    /// `(a, b)` price pair.
+    type Input = (f64, f64);
+    type Output = RelativeStrengthOutput;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<RelativeStrengthOutput> {
+        let (a, b) = input;
+        if b == 0.0 || !a.is_finite() || !b.is_finite() {
+            // Undefined ratio: skip without disturbing the internal averages.
+            return None;
+        }
+        let ratio = a / b;
+        let ma = self.ma.update(ratio);
+        let rsi = self.rsi.update(ratio);
+        match (ma, rsi) {
+            (Some(ratio_ma), Some(ratio_rsi)) => Some(RelativeStrengthOutput {
+                ratio,
+                ratio_ma,
+                ratio_rsi,
+            }),
+            _ => None,
+        }
+    }
+
+    fn reset(&mut self) {
+        self.ma.reset();
+        self.rsi.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.ma.warmup_period().max(self.rsi.warmup_period())
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ma.is_ready() && self.rsi.is_ready()
+    }
+
+    fn name(&self) -> &'static str {
+        "RelativeStrengthAB"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_periods() {
+        assert!(RelativeStrengthAB::new(0, 5).is_err());
+        assert!(RelativeStrengthAB::new(5, 0).is_err());
+        assert!(RelativeStrengthAB::new(5, 5).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let rs = RelativeStrengthAB::new(10, 14).unwrap();
+        assert_eq!(rs.ma_period(), 10);
+        assert_eq!(rs.rsi_period(), 14);
+        // SMA warmup = 10, RSI warmup = 15 ⇒ combined = 15.
+        assert_eq!(rs.warmup_period(), 15);
+        assert_eq!(rs.name(), "RelativeStrengthAB");
+    }
+
+    #[test]
+    fn constant_ratio_is_flat() {
+        // a = 2·b ⇒ ratio is a constant 2 ⇒ MA = 2, RSI = neutral 50.
+        let pairs: Vec<(f64, f64)> = (0..20).map(|_| (200.0, 100.0)).collect();
+        let out = RelativeStrengthAB::new(5, 5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(out.ratio, 2.0, epsilon = 1e-12);
+        assert_relative_eq!(out.ratio_ma, 2.0, epsilon = 1e-12);
+        assert_relative_eq!(out.ratio_rsi, 50.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn rising_ratio_is_overbought() {
+        // a grows while b is flat ⇒ ratio strictly rises ⇒ RSI saturates at 100.
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|t| (100.0 + 2.0 * f64::from(t), 100.0))
+            .collect();
+        let out = RelativeStrengthAB::new(5, 5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(out.ratio > 1.0);
+        assert_relative_eq!(out.ratio_rsi, 100.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn zero_denominator_is_skipped() {
+        let mut rs = RelativeStrengthAB::new(3, 3).unwrap();
+        // b == 0 and non-finite inputs never reach the internal averages.
+        assert_eq!(rs.update((100.0, 0.0)), None);
+        assert_eq!(rs.update((f64::NAN, 100.0)), None);
+        assert!(!rs.is_ready());
+        for _ in 0..8 {
+            rs.update((150.0, 100.0));
+        }
+        assert!(rs.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut rs = RelativeStrengthAB::new(3, 3).unwrap();
+        for t in 0..10 {
+            rs.update((100.0 + f64::from(t), 100.0));
+        }
+        assert!(rs.is_ready());
+        rs.reset();
+        assert!(!rs.is_ready());
+        assert_eq!(rs.update((100.0, 100.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|t| {
+                let tt = f64::from(t);
+                (
+                    100.0 + 5.0 * (tt * 0.3).sin(),
+                    100.0 + 2.0 * (tt * 0.2).cos(),
+                )
+            })
+            .collect();
+        let batch = RelativeStrengthAB::new(10, 14).unwrap().batch(&pairs);
+        let mut rs = RelativeStrengthAB::new(10, 14).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| rs.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/shooting_star.rs

@@ -22,6 +22,14 @@ use crate::traits::Indicator;
 /// check only — no trend filter is applied; combine with a trend indicator
 /// for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// A Shooting Star is bearish by definition, so under the uniform candlestick
+/// sign convention (`+1.0` bullish, `−1.0` bearish, `0.0` none) it emits
+/// `−1.0` when the shape matches and `0.0` otherwise — it never emits `+1.0`.
+/// The same geometry read at the bottom of a downtrend is the bullish
+/// `InvertedHammer`, which carries the opposite sign.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/signed_volume.rs

@@ -0,0 +1,128 @@
+//! Signed Volume — per-trade volume signed by aggressor side.
+
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// Signed Volume — the size of each trade signed by its aggressor side.
+///
+/// ```text
+/// signedVolume = size · (+1 if buy, −1 if sell)
+/// ```
+///
+/// A positive value is buyer-initiated flow, a negative value seller-initiated.
+/// It is the per-trade building block of [`crate::CumulativeVolumeDelta`] and
+/// trade-flow imbalance.
+///
+/// `Input = Trade`, `Output = f64`. Stateless; ready after the first trade.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, SignedVolume, Side, Trade};
+///
+/// let mut sv = SignedVolume::new();
+/// let buy = Trade::new(100.0, 2.0, Side::Buy, 0).unwrap();
+/// assert_eq!(sv.update(buy), Some(2.0));
+/// let sell = Trade::new(100.0, 3.0, Side::Sell, 1).unwrap();
+/// assert_eq!(sv.update(sell), Some(-3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct SignedVolume {
+    has_emitted: bool,
+}
+
+impl SignedVolume {
+    /// Construct a new signed-volume indicator.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for SignedVolume {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        self.has_emitted = true;
+        Some(trade.size * trade.side.sign())
+    }
+
+    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 {
+        "SignedVolume"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+
+    fn trade(size: f64, side: Side, ts: i64) -> Trade {
+        Trade::new(100.0, size, side, ts).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let sv = SignedVolume::new();
+        assert_eq!(sv.name(), "SignedVolume");
+        assert_eq!(sv.warmup_period(), 1);
+        assert!(!sv.is_ready());
+    }
+
+    #[test]
+    fn buy_is_positive() {
+        let mut sv = SignedVolume::new();
+        assert_eq!(sv.update(trade(2.0, Side::Buy, 0)), Some(2.0));
+        assert!(sv.is_ready());
+    }
+
+    #[test]
+    fn sell_is_negative() {
+        let mut sv = SignedVolume::new();
+        assert_eq!(sv.update(trade(3.0, Side::Sell, 0)), Some(-3.0));
+    }
+
+    #[test]
+    fn zero_size_is_zero() {
+        let mut sv = SignedVolume::new();
+        assert_eq!(sv.update(trade(0.0, Side::Buy, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..20)
+            .map(|i| {
+                let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+                trade(1.0 + (i % 4) as f64, side, i)
+            })
+            .collect();
+        let mut a = SignedVolume::new();
+        let mut b = SignedVolume::new();
+        assert_eq!(
+            a.batch(&trades),
+            trades.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut sv = SignedVolume::new();
+        sv.update(trade(1.0, Side::Buy, 0));
+        assert!(sv.is_ready());
+        sv.reset();
+        assert!(!sv.is_ready());
+    }
+}

crates/wickra-core/src/indicators/spinning_top.rs

@@ -24,6 +24,13 @@ use crate::traits::Indicator;
 ///
 /// `body_threshold` defaults to `0.3` and must lie in `(0, 1]`.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/three_inside.rs

@@ -18,6 +18,13 @@ use crate::traits::Indicator;
 /// Pattern-shape check only — no trend filter is applied; combine with a trend
 /// indicator for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/three_outside.rs

@@ -17,6 +17,13 @@ use crate::traits::Indicator;
 /// Pattern-shape check only — no trend filter is applied; combine with a trend
 /// indicator for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/three_soldiers_or_crows.rs

@@ -20,6 +20,13 @@ use crate::traits::Indicator;
 /// Pattern-shape check only — no trend filter is applied; combine with a trend
 /// indicator for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/indicators/trade_imbalance.rs

@@ -0,0 +1,193 @@
+//! Trade Imbalance — rolling buy/sell volume imbalance over a trade window.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// Trade Imbalance — the signed buy/sell volume imbalance over the trailing
+/// window of `window` trades.
+///
+/// ```text
+/// buyVol  = Σ size of buyer-initiated trades in the window
+/// sellVol = Σ size of seller-initiated trades in the window
+/// imbalance = (buyVol − sellVol) / (buyVol + sellVol)
+/// ```
+///
+/// The output lies in `[−1, +1]`: `+1` means the window was all aggressive
+/// buying, `−1` all aggressive selling, `0` balanced (or no volume). The
+/// indicator warms up for `window` trades — `update` returns `None` until the
+/// window is full — then emits the rolling imbalance, maintained in O(1) per
+/// trade.
+///
+/// `Input = Trade`, `Output = f64`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Side, Trade, TradeImbalance};
+///
+/// let mut ti = TradeImbalance::new(2).unwrap();
+/// assert_eq!(ti.update(Trade::new(100.0, 3.0, Side::Buy, 0).unwrap()), None);
+/// // Window full: buyVol 3, sellVol 1 -> (3 - 1) / 4 = 0.5.
+/// let out = ti.update(Trade::new(100.0, 1.0, Side::Sell, 1).unwrap());
+/// assert_eq!(out, Some(0.5));
+/// ```
+#[derive(Debug, Clone)]
+pub struct TradeImbalance {
+    window: usize,
+    history: VecDeque<(f64, f64)>,
+    buy_sum: f64,
+    sell_sum: f64,
+}
+
+impl TradeImbalance {
+    /// Construct a trade-imbalance indicator over a window of `window` trades.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `window` is zero.
+    pub fn new(window: usize) -> Result<Self> {
+        if window == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            window,
+            history: VecDeque::with_capacity(window),
+            buy_sum: 0.0,
+            sell_sum: 0.0,
+        })
+    }
+
+    /// The configured window length, in trades.
+    pub fn window(&self) -> usize {
+        self.window
+    }
+}
+
+impl Indicator for TradeImbalance {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        let (buy, sell) = if trade.side.sign() > 0.0 {
+            (trade.size, 0.0)
+        } else {
+            (0.0, trade.size)
+        };
+        self.history.push_back((buy, sell));
+        self.buy_sum += buy;
+        self.sell_sum += sell;
+        if self.history.len() > self.window {
+            let (old_buy, old_sell) = self.history.pop_front().expect("window >= 1, len > window");
+            self.buy_sum -= old_buy;
+            self.sell_sum -= old_sell;
+        }
+        if self.history.len() < self.window {
+            return None;
+        }
+        let total = self.buy_sum + self.sell_sum;
+        if total <= 0.0 {
+            return Some(0.0);
+        }
+        Some((self.buy_sum - self.sell_sum) / total)
+    }
+
+    fn reset(&mut self) {
+        self.history.clear();
+        self.buy_sum = 0.0;
+        self.sell_sum = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.window
+    }
+
+    fn is_ready(&self) -> bool {
+        self.history.len() >= self.window
+    }
+
+    fn name(&self) -> &'static str {
+        "TradeImbalance"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+
+    fn trade(size: f64, side: Side, ts: i64) -> Trade {
+        Trade::new(100.0, size, side, ts).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_window() {
+        assert!(matches!(TradeImbalance::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ti = TradeImbalance::new(5).unwrap();
+        assert_eq!(ti.name(), "TradeImbalance");
+        assert_eq!(ti.warmup_period(), 5);
+        assert_eq!(ti.window(), 5);
+        assert!(!ti.is_ready());
+    }
+
+    #[test]
+    fn warms_up_then_emits() {
+        let mut ti = TradeImbalance::new(2).unwrap();
+        assert_eq!(ti.update(trade(3.0, Side::Buy, 0)), None);
+        assert!(!ti.is_ready());
+        // Window full: buyVol 3, sellVol 1 -> 0.5.
+        assert_eq!(ti.update(trade(1.0, Side::Sell, 1)), Some(0.5));
+        assert!(ti.is_ready());
+    }
+
+    #[test]
+    fn rolls_off_old_trades() {
+        let mut ti = TradeImbalance::new(2).unwrap();
+        ti.update(trade(3.0, Side::Buy, 0));
+        ti.update(trade(1.0, Side::Sell, 1)); // [buy 3, sell 1] -> 0.5
+                                              // Third trade drops the first: window now [sell 1, buy 5] -> (5-1)/6.
+        let out = ti.update(trade(5.0, Side::Buy, 2)).unwrap();
+        assert!((out - (4.0 / 6.0)).abs() < 1e-12);
+    }
+
+    #[test]
+    fn zero_volume_window_is_zero() {
+        let mut ti = TradeImbalance::new(2).unwrap();
+        ti.update(trade(0.0, Side::Buy, 0));
+        assert_eq!(ti.update(trade(0.0, Side::Sell, 1)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..30)
+            .map(|i| {
+                let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+                trade(1.0 + (i % 5) as f64, side, i)
+            })
+            .collect();
+        let mut a = TradeImbalance::new(5).unwrap();
+        let mut b = TradeImbalance::new(5).unwrap();
+        assert_eq!(
+            a.batch(&trades),
+            trades.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ti = TradeImbalance::new(2).unwrap();
+        ti.update(trade(3.0, Side::Buy, 0));
+        ti.update(trade(1.0, Side::Sell, 1));
+        assert!(ti.is_ready());
+        ti.reset();
+        assert!(!ti.is_ready());
+        assert_eq!(ti.update(trade(2.0, Side::Buy, 2)), None);
+    }
+}

crates/wickra-core/src/indicators/tweezer.rs

@@ -22,6 +22,13 @@ use crate::traits::Indicator;
 /// Pattern-shape check only — no trend filter is applied; combine with a trend
 /// indicator for actionable signals.
 ///
+/// # Signed ±1 encoding
+///
+/// This detector already 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 of the pattern occupy a single dimension.
+///
 /// # Example
 ///
 /// ```

crates/wickra-core/src/lib.rs

@@ -37,6 +37,7 @@
 #![cfg_attr(docsrs, feature(doc_cfg))]
 
 mod error;
+mod microstructure;
 mod ohlcv;
 mod traits;
 
@@ -52,38 +53,48 @@ pub use indicators::{
     CamarillaPivotsOutput, Cci, CenterOfGravity, Cfo, ChaikinMoneyFlow, ChaikinOscillator,
     ChaikinVolatility, ChandeKrollStop, ChandeKrollStopOutput, ChandelierExit,
     ChandelierExitOutput, ChoppinessIndex, ClassicPivots, ClassicPivotsOutput, Cmo,
-    CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CyberneticCycle, Decycler,
-    DecyclerOscillator, Dema, DemandIndex, DemarkPivots, DemarkPivotsOutput, DetrendedStdDev, Doji,
-    Donchian, DonchianOutput, DonchianStop, DonchianStopOutput, DoubleBollinger,
-    DoubleBollingerOutput, Dpo, DrawdownDuration, EaseOfMovement, EhlersStochastic, ElderImpulse,
-    Ema, EmpiricalModeDecomposition, Engulfing, Evwma, Fama, FibonacciPivots,
-    FibonacciPivotsOutput, FisherTransform, ForceIndex, FractalChaosBands, FractalChaosBandsOutput,
-    Frama, GainLossRatio, GarmanKlassVolatility, Hammer, HangingMan, Harami, HeikinAshi,
-    HeikinAshiOutput, HiLoActivator, HilbertDominantCycle, HistoricalVolatility, Hma, HurstChannel,
-    HurstChannelOutput, HurstExponent, Ichimoku, IchimokuOutput, Inertia, InformationRatio,
-    InitialBalance, InitialBalanceOutput, InstantaneousTrendline, InverseFisherTransform,
-    InvertedHammer, Jma, Kama, KellyCriterion, Keltner, KeltnerOutput, Kst, KstOutput, Kurtosis,
-    Kvo, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegChannelOutput, LinRegSlope,
-    LinearRegression, MaEnvelope, MaEnvelopeOutput, MacdIndicator, MacdOutput, Mama, MamaOutput,
-    MarketFacilitationIndex, Marubozu, MassIndex, MaxDrawdown, McGinleyDynamic,
-    MedianAbsoluteDeviation, MedianPrice, Mfi, Mom, MorningEveningStar, Natr, Nvi, Obv, OmegaRatio,
-    OpeningRange, OpeningRangeOutput, PainIndex, ParkinsonVolatility, PearsonCorrelation, PercentB,
-    PercentageTrailingStop, Pgo, PiercingDarkCloud, Pmo, Ppo, ProfitFactor, Psar, Pvi, RSquared,
-    RecoveryFactor, RenkoTrailingStop, Roc, RogersSatchellVolatility, RollingVwap, RoofingFilter,
-    Rsi, Rvi, RviVolatility, Rwi, RwiOutput, SharpeRatio, ShootingStar, SineWave, Skewness, Sma,
-    Smi, Smma, SortinoRatio, SpearmanCorrelation, SpinningTop, StandardError, StandardErrorBands,
-    StandardErrorBandsOutput, StarcBands, StarcBandsOutput, Stc, StdDev, StepTrailingStop,
-    StochRsi, Stochastic, StochasticOutput, SuperSmoother, SuperTrend, SuperTrendOutput, TdCombo,
-    TdCountdown, TdDeMarker, TdDifferential, TdLines, TdLinesOutput, TdOpen, TdPressure,
-    TdRangeProjection, TdRangeProjectionOutput, TdRei, TdRiskLevel, TdRiskLevelOutput,
-    TdSequential, TdSequentialOutput, TdSetup, Tema, ThreeInside, ThreeOutside,
-    ThreeSoldiersOrCrows, Tii, TreynorRatio, Trima, Trix, TrueRange, Tsi, Tsv, TtmSqueeze,
-    TtmSqueezeOutput, Tweezer, TypicalPrice, UlcerIndex, UltimateOscillator, ValueArea,
-    ValueAreaOutput, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, VoltyStop,
+    CoefficientOfVariation, Cointegration, CointegrationOutput, ConditionalValueAtRisk, ConnorsRsi,
+    Coppock, CumulativeVolumeDelta, CyberneticCycle, Decycler, DecyclerOscillator, Dema,
+    DemandIndex, DemarkPivots, DemarkPivotsOutput, DepthSlope, DetrendedStdDev, Doji, Donchian,
+    DonchianOutput, DonchianStop, DonchianStopOutput, DoubleBollinger, DoubleBollingerOutput, Dpo,
+    DrawdownDuration, EaseOfMovement, EffectiveSpread, EhlersStochastic, ElderImpulse, Ema,
+    EmpiricalModeDecomposition, Engulfing, Evwma, Fama, FibonacciPivots, FibonacciPivotsOutput,
+    FisherTransform, Footprint, FootprintOutput, ForceIndex, FractalChaosBands,
+    FractalChaosBandsOutput, Frama, GainLossRatio, GarmanKlassVolatility, Hammer, HangingMan,
+    Harami, HeikinAshi, HeikinAshiOutput, HiLoActivator, HilbertDominantCycle,
+    HistoricalVolatility, Hma, HurstChannel, HurstChannelOutput, HurstExponent, Ichimoku,
+    IchimokuOutput, Inertia, InformationRatio, InitialBalance, InitialBalanceOutput,
+    InstantaneousTrendline, InverseFisherTransform, InvertedHammer, Jma, Kama, KellyCriterion,
+    Keltner, KeltnerOutput, Kst, KstOutput, Kurtosis, Kvo, KylesLambda, LaguerreRsi,
+    LeadLagCrossCorrelation, LeadLagCrossCorrelationOutput, LinRegAngle, LinRegChannel,
+    LinRegChannelOutput, LinRegSlope, LinearRegression, MaEnvelope, MaEnvelopeOutput,
+    MacdIndicator, MacdOutput, Mama, MamaOutput, MarketFacilitationIndex, Marubozu, MassIndex,
+    MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MedianPrice, Mfi, Microprice, Mom,
+    MorningEveningStar, Natr, Nvi, Obv, OmegaRatio, OpeningRange, OpeningRangeOutput,
+    OrderBookImbalanceFull, OrderBookImbalanceTop1, OrderBookImbalanceTopN, PainIndex,
+    PairSpreadZScore, PairwiseBeta, ParkinsonVolatility, PearsonCorrelation, PercentB,
+    PercentageTrailingStop, Pgo, PiercingDarkCloud, Pmo, Ppo, ProfitFactor, Psar, Pvi,
+    QuotedSpread, RSquared, RealizedSpread, RecoveryFactor, RelativeStrengthAB,
+    RelativeStrengthOutput, RenkoTrailingStop, Roc, RogersSatchellVolatility, RollingVwap,
+    RoofingFilter, Rsi, Rvi, RviVolatility, Rwi, RwiOutput, SharpeRatio, ShootingStar,
+    SignedVolume, SineWave, Skewness, Sma, Smi, Smma, SortinoRatio, SpearmanCorrelation,
+    SpinningTop, StandardError, StandardErrorBands, StandardErrorBandsOutput, StarcBands,
+    StarcBandsOutput, Stc, StdDev, StepTrailingStop, StochRsi, Stochastic, StochasticOutput,
+    SuperSmoother, SuperTrend, SuperTrendOutput, TdCombo, TdCountdown, TdDeMarker, TdDifferential,
+    TdLines, TdLinesOutput, TdOpen, TdPressure, TdRangeProjection, TdRangeProjectionOutput, TdRei,
+    TdRiskLevel, TdRiskLevelOutput, TdSequential, TdSequentialOutput, TdSetup, Tema, ThreeInside,
+    ThreeOutside, ThreeSoldiersOrCrows, Tii, TradeImbalance, TreynorRatio, Trima, Trix, TrueRange,
+    Tsi, Tsv, TtmSqueeze, TtmSqueezeOutput, Tweezer, TypicalPrice, UlcerIndex, UltimateOscillator,
+    ValueArea, ValueAreaOutput, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, VoltyStop,
     VolumeOscillator, VolumePriceTrend, Vortex, VortexOutput, Vwap, VwapStdDevBands,
     VwapStdDevBandsOutput, Vwma, Vzo, WaveTrend, WaveTrendOutput, WeightedClose, WilliamsFractals,
     WilliamsFractalsOutput, WilliamsR, Wma, WoodiePivots, WoodiePivotsOutput, YangZhangVolatility,
     YoyoExit, ZScore, ZeroLagMacd, ZeroLagMacdOutput, ZigZag, ZigZagOutput, Zlema, FAMILIES, T3,
 };
+// `FootprintLevel` is a row element of `FootprintOutput`, re-exported on its own
+// line so the indicator-count tooling (which scans the braced block above and
+// strips only `*Output` companions) does not count it as a separate indicator.
+pub use indicators::FootprintLevel;
+pub use microstructure::{Level, OrderBook, Side, Trade, TradeQuote};
 pub use ohlcv::{Candle, Tick};
 pub use traits::{BatchExt, Chain, Indicator};

crates/wickra-core/src/microstructure.rs

@@ -0,0 +1,467 @@
+//! Microstructure value types: order-book snapshots and trades.
+//!
+//! These are the non-OHLCV inputs consumed by the order-book / trade-flow
+//! indicator family. An [`OrderBook`] is a depth snapshot (sorted bid and ask
+//! levels); a [`Trade`] is a single executed trade with an aggressor [`Side`];
+//! a [`TradeQuote`] pairs a trade with the mid-price prevailing at execution,
+//! the input for spread- and price-impact measures.
+
+use crate::error::{Error, Result};
+
+/// A single order-book price level: a resting quantity at a price.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct Level {
+    /// Price of the level (strictly positive).
+    pub price: f64,
+    /// Resting size / quantity at this price (non-negative).
+    pub size: f64,
+}
+
+impl Level {
+    /// Construct a level, validating that `price` is finite and strictly
+    /// positive and `size` is finite and non-negative.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidOrderBook`] if the price is not a finite
+    /// positive number, or the size is not a finite non-negative number.
+    pub fn new(price: f64, size: f64) -> Result<Self> {
+        if !price.is_finite() || price <= 0.0 {
+            return Err(Error::InvalidOrderBook {
+                message: "level price must be finite and positive",
+            });
+        }
+        if !size.is_finite() || size < 0.0 {
+            return Err(Error::InvalidOrderBook {
+                message: "level size must be finite and non-negative",
+            });
+        }
+        Ok(Self { price, size })
+    }
+
+    /// Construct a level without validation. The caller asserts that `price`
+    /// is finite and positive and `size` is finite and non-negative.
+    pub const fn new_unchecked(price: f64, size: f64) -> Self {
+        Self { price, size }
+    }
+}
+
+/// An order-book depth snapshot.
+///
+/// Bids are stored best-first (strictly descending price); asks are stored
+/// best-first (strictly ascending price). A valid book is non-empty on both
+/// sides and uncrossed (`best_bid < best_ask`).
+#[derive(Debug, Clone, PartialEq)]
+pub struct OrderBook {
+    /// Bid levels, best (highest price) first.
+    pub bids: Vec<Level>,
+    /// Ask levels, best (lowest price) first.
+    pub asks: Vec<Level>,
+}
+
+impl OrderBook {
+    /// Construct an order book, validating the level and ordering invariants.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidOrderBook`] if either side is empty, any level
+    /// has a non-finite/non-positive price or non-finite/negative size, the
+    /// bids are not strictly descending in price, the asks are not strictly
+    /// ascending in price, or the book is crossed/locked (`best_bid >=
+    /// best_ask`).
+    pub fn new(bids: Vec<Level>, asks: Vec<Level>) -> Result<Self> {
+        if bids.is_empty() || asks.is_empty() {
+            return Err(Error::InvalidOrderBook {
+                message: "order book must have at least one bid and one ask",
+            });
+        }
+        for level in bids.iter().chain(asks.iter()) {
+            if !level.price.is_finite() || level.price <= 0.0 {
+                return Err(Error::InvalidOrderBook {
+                    message: "level price must be finite and positive",
+                });
+            }
+            if !level.size.is_finite() || level.size < 0.0 {
+                return Err(Error::InvalidOrderBook {
+                    message: "level size must be finite and non-negative",
+                });
+            }
+        }
+        for pair in bids.windows(2) {
+            if pair[0].price <= pair[1].price {
+                return Err(Error::InvalidOrderBook {
+                    message: "bids must be strictly descending in price",
+                });
+            }
+        }
+        for pair in asks.windows(2) {
+            if pair[0].price >= pair[1].price {
+                return Err(Error::InvalidOrderBook {
+                    message: "asks must be strictly ascending in price",
+                });
+            }
+        }
+        if bids[0].price >= asks[0].price {
+            return Err(Error::InvalidOrderBook {
+                message: "order book must be uncrossed (best_bid < best_ask)",
+            });
+        }
+        Ok(Self { bids, asks })
+    }
+
+    /// Construct an order book without validation. The caller asserts that all
+    /// level and ordering invariants hold.
+    pub const fn new_unchecked(bids: Vec<Level>, asks: Vec<Level>) -> Self {
+        Self { bids, asks }
+    }
+
+    /// The best (highest-price) bid level, or `None` if the bid side is empty.
+    pub fn best_bid(&self) -> Option<Level> {
+        self.bids.first().copied()
+    }
+
+    /// The best (lowest-price) ask level, or `None` if the ask side is empty.
+    pub fn best_ask(&self) -> Option<Level> {
+        self.asks.first().copied()
+    }
+
+    /// The mid price `(best_bid + best_ask) / 2`, or `None` if either side is
+    /// empty.
+    pub fn mid(&self) -> Option<f64> {
+        match (self.best_bid(), self.best_ask()) {
+            (Some(bid), Some(ask)) => Some(f64::midpoint(bid.price, ask.price)),
+            _ => None,
+        }
+    }
+}
+
+/// The aggressor side of a trade: the side that crossed the spread.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum Side {
+    /// A buyer-initiated (aggressive buy) trade.
+    Buy,
+    /// A seller-initiated (aggressive sell) trade.
+    Sell,
+}
+
+impl Side {
+    /// The signed multiplier for this side: `+1.0` for a buy, `−1.0` for a
+    /// sell.
+    pub const fn sign(self) -> f64 {
+        match self {
+            Side::Buy => 1.0,
+            Side::Sell => -1.0,
+        }
+    }
+}
+
+/// A single executed trade with an aggressor side.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct Trade {
+    /// Execution price (strictly positive).
+    pub price: f64,
+    /// Executed size / quantity (non-negative).
+    pub size: f64,
+    /// Aggressor side.
+    pub side: Side,
+    /// Trade timestamp (caller-defined epoch / resolution).
+    pub timestamp: i64,
+}
+
+impl Trade {
+    /// Construct a trade, validating that `price` is finite and strictly
+    /// positive and `size` is finite and non-negative.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidTrade`] if the price is not a finite positive
+    /// number, or the size is not a finite non-negative number.
+    pub fn new(price: f64, size: f64, side: Side, timestamp: i64) -> Result<Self> {
+        if !price.is_finite() || price <= 0.0 {
+            return Err(Error::InvalidTrade {
+                message: "trade price must be finite and positive",
+            });
+        }
+        if !size.is_finite() || size < 0.0 {
+            return Err(Error::InvalidTrade {
+                message: "trade size must be finite and non-negative",
+            });
+        }
+        Ok(Self {
+            price,
+            size,
+            side,
+            timestamp,
+        })
+    }
+
+    /// Construct a trade without validation. The caller asserts that `price`
+    /// is finite and positive and `size` is finite and non-negative.
+    pub const fn new_unchecked(price: f64, size: f64, side: Side, timestamp: i64) -> Self {
+        Self {
+            price,
+            size,
+            side,
+            timestamp,
+        }
+    }
+}
+
+/// A trade paired with the mid-price prevailing at execution.
+///
+/// This is the input for spread- and price-impact measures (effective spread,
+/// realized spread, Kyle's lambda), which relate an executed trade to the
+/// quote it traded against.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct TradeQuote {
+    /// The executed trade.
+    pub trade: Trade,
+    /// The mid-price prevailing at execution (strictly positive).
+    pub mid: f64,
+}
+
+impl TradeQuote {
+    /// Construct a trade-quote, validating that `mid` is finite and strictly
+    /// positive. The `trade` is assumed already valid.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidTrade`] if `mid` is not a finite positive
+    /// number.
+    pub fn new(trade: Trade, mid: f64) -> Result<Self> {
+        if !mid.is_finite() || mid <= 0.0 {
+            return Err(Error::InvalidTrade {
+                message: "trade-quote mid must be finite and positive",
+            });
+        }
+        Ok(Self { trade, mid })
+    }
+
+    /// Construct a trade-quote without validation. The caller asserts that
+    /// `mid` is finite and positive.
+    pub const fn new_unchecked(trade: Trade, mid: f64) -> Self {
+        Self { trade, mid }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn level_new_accepts_valid() {
+        let level = Level::new(100.5, 2.0).unwrap();
+        assert_eq!(level.price, 100.5);
+        assert_eq!(level.size, 2.0);
+    }
+
+    #[test]
+    fn level_new_accepts_zero_size() {
+        assert!(Level::new(100.0, 0.0).is_ok());
+    }
+
+    #[test]
+    fn level_new_rejects_non_finite_price() {
+        assert!(matches!(
+            Level::new(f64::NAN, 1.0),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            Level::new(f64::INFINITY, 1.0),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn level_new_rejects_non_positive_price() {
+        assert!(matches!(
+            Level::new(0.0, 1.0),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            Level::new(-1.0, 1.0),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn level_new_rejects_bad_size() {
+        assert!(matches!(
+            Level::new(100.0, -1.0),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            Level::new(100.0, f64::NAN),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn level_new_unchecked_preserves_fields() {
+        let level = Level::new_unchecked(-5.0, -2.0);
+        assert_eq!(level.price, -5.0);
+        assert_eq!(level.size, -2.0);
+    }
+
+    fn lvl(price: f64, size: f64) -> Level {
+        Level::new(price, size).unwrap()
+    }
+
+    #[test]
+    fn order_book_new_accepts_valid() {
+        let book = OrderBook::new(
+            vec![lvl(100.0, 2.0), lvl(99.0, 3.0)],
+            vec![lvl(101.0, 1.0), lvl(102.0, 4.0)],
+        )
+        .unwrap();
+        assert_eq!(book.best_bid(), Some(lvl(100.0, 2.0)));
+        assert_eq!(book.best_ask(), Some(lvl(101.0, 1.0)));
+        assert_eq!(book.mid(), Some(100.5));
+    }
+
+    #[test]
+    fn order_book_new_rejects_empty_side() {
+        assert!(matches!(
+            OrderBook::new(vec![], vec![lvl(101.0, 1.0)]),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            OrderBook::new(vec![lvl(100.0, 1.0)], vec![]),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn order_book_new_rejects_bad_level() {
+        assert!(matches!(
+            OrderBook::new(
+                vec![Level::new_unchecked(100.0, -1.0)],
+                vec![lvl(101.0, 1.0)]
+            ),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            OrderBook::new(
+                vec![lvl(100.0, 1.0)],
+                vec![Level::new_unchecked(f64::NAN, 1.0)]
+            ),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn order_book_new_rejects_misordered_bids() {
+        assert!(matches!(
+            OrderBook::new(vec![lvl(99.0, 1.0), lvl(100.0, 1.0)], vec![lvl(101.0, 1.0)]),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn order_book_new_rejects_misordered_asks() {
+        assert!(matches!(
+            OrderBook::new(
+                vec![lvl(100.0, 1.0)],
+                vec![lvl(102.0, 1.0), lvl(101.0, 1.0)]
+            ),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn order_book_new_rejects_crossed() {
+        assert!(matches!(
+            OrderBook::new(vec![lvl(101.0, 1.0)], vec![lvl(101.0, 1.0)]),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+        assert!(matches!(
+            OrderBook::new(vec![lvl(102.0, 1.0)], vec![lvl(101.0, 1.0)]),
+            Err(Error::InvalidOrderBook { .. })
+        ));
+    }
+
+    #[test]
+    fn order_book_new_unchecked_allows_empty() {
+        let book = OrderBook::new_unchecked(vec![], vec![]);
+        assert_eq!(book.best_bid(), None);
+        assert_eq!(book.best_ask(), None);
+        assert_eq!(book.mid(), None);
+    }
+
+    #[test]
+    fn side_sign() {
+        assert_eq!(Side::Buy.sign(), 1.0);
+        assert_eq!(Side::Sell.sign(), -1.0);
+    }
+
+    #[test]
+    fn trade_new_accepts_valid() {
+        let trade = Trade::new(100.0, 1.5, Side::Buy, 42).unwrap();
+        assert_eq!(trade.price, 100.0);
+        assert_eq!(trade.size, 1.5);
+        assert_eq!(trade.side, Side::Buy);
+        assert_eq!(trade.timestamp, 42);
+    }
+
+    #[test]
+    fn trade_new_rejects_bad_price() {
+        assert!(matches!(
+            Trade::new(0.0, 1.0, Side::Buy, 0),
+            Err(Error::InvalidTrade { .. })
+        ));
+        assert!(matches!(
+            Trade::new(f64::NAN, 1.0, Side::Sell, 0),
+            Err(Error::InvalidTrade { .. })
+        ));
+    }
+
+    #[test]
+    fn trade_new_rejects_bad_size() {
+        assert!(matches!(
+            Trade::new(100.0, -1.0, Side::Buy, 0),
+            Err(Error::InvalidTrade { .. })
+        ));
+        assert!(matches!(
+            Trade::new(100.0, f64::INFINITY, Side::Buy, 0),
+            Err(Error::InvalidTrade { .. })
+        ));
+    }
+
+    #[test]
+    fn trade_new_unchecked_preserves_fields() {
+        let trade = Trade::new_unchecked(-1.0, -2.0, Side::Sell, 7);
+        assert_eq!(trade.price, -1.0);
+        assert_eq!(trade.size, -2.0);
+        assert_eq!(trade.side, Side::Sell);
+        assert_eq!(trade.timestamp, 7);
+    }
+
+    #[test]
+    fn trade_quote_new_accepts_valid() {
+        let trade = Trade::new(100.0, 1.0, Side::Buy, 0).unwrap();
+        let tq = TradeQuote::new(trade, 99.5).unwrap();
+        assert_eq!(tq.trade, trade);
+        assert_eq!(tq.mid, 99.5);
+    }
+
+    #[test]
+    fn trade_quote_new_rejects_bad_mid() {
+        let trade = Trade::new(100.0, 1.0, Side::Buy, 0).unwrap();
+        assert!(matches!(
+            TradeQuote::new(trade, 0.0),
+            Err(Error::InvalidTrade { .. })
+        ));
+        assert!(matches!(
+            TradeQuote::new(trade, f64::NAN),
+            Err(Error::InvalidTrade { .. })
+        ));
+    }
+
+    #[test]
+    fn trade_quote_new_unchecked_preserves_fields() {
+        let trade = Trade::new_unchecked(100.0, 1.0, Side::Buy, 0);
+        let tq = TradeQuote::new_unchecked(trade, -1.0);
+        assert_eq!(tq.mid, -1.0);
+        assert_eq!(tq.trade, trade);
+    }
+}

crates/wickra-data/Cargo.toml

@@ -5,7 +5,7 @@ version.workspace = true
 authors.workspace = true
 edition.workspace = true
 rust-version.workspace = true
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

crates/wickra/Cargo.toml

@@ -5,7 +5,7 @@ version.workspace = true
 authors.workspace = true
 edition.workspace = true
 rust-version.workspace = true
-license.workspace = true
+license-file.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

crates/wickra/benches/indicators.rs

@@ -33,13 +33,14 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use std::hint::black_box;
 use wickra::{
     Adx, Atr, Autocorrelation, BatchExt, BollingerBands, BollingerOutput, CalmarRatio, Candle, Cci,
-    ClassicPivots, ConnorsRsi, Ema, EmpiricalModeDecomposition, Engulfing, Frama,
-    HilbertDominantCycle, HurstExponent, Ichimoku, IchimokuOutput, Indicator, Jma,
-    LinearRegression, MacdIndicator, MacdOutput, Mama, MamaOutput, MaxDrawdown, Obv,
-    ParkinsonVolatility, Ppo, Psar, RollingVwap, Rsi, SharpeRatio, Sma, Stc, SuperTrend,
-    SuperTrendOutput, TdSequential, TdSequentialOutput, TtmSqueeze, TtmSqueezeOutput, ValueArea,
-    ValueAreaOutput, ValueAtRisk, Vwap, VwapStdDevBands, VwapStdDevBandsOutput, WaveTrend,
-    YangZhangVolatility, T3,
+    ClassicPivots, ConnorsRsi, DepthSlope, EffectiveSpread, Ema, EmpiricalModeDecomposition,
+    Engulfing, Frama, HilbertDominantCycle, HurstExponent, Ichimoku, IchimokuOutput, Indicator,
+    Jma, KylesLambda, Level, LinearRegression, MacdIndicator, MacdOutput, Mama, MamaOutput,
+    MaxDrawdown, Microprice, Obv, OrderBook, OrderBookImbalanceFull, OrderBookImbalanceTop1,
+    ParkinsonVolatility, Ppo, Psar, RollingVwap, Rsi, SharpeRatio, Side, SignedVolume, Sma, Stc,
+    SuperTrend, SuperTrendOutput, TdSequential, TdSequentialOutput, Trade, TradeImbalance,
+    TradeQuote, TtmSqueeze, TtmSqueezeOutput, ValueArea, ValueAreaOutput, ValueAtRisk, Vwap,
+    VwapStdDevBands, VwapStdDevBandsOutput, WaveTrend, YangZhangVolatility, T3,
 };
 use wickra_data::csv::CandleReader;
 
@@ -114,6 +115,72 @@ where
     group.finish();
 }
 
+fn bench_orderbook_input<I, F, O>(c: &mut Criterion, name: &str, books: &[OrderBook], make: F)
+where
+    F: Fn() -> I,
+    I: Indicator<Input = OrderBook, Output = O>,
+{
+    let mut group = c.benchmark_group(name);
+    for &n in SIZES {
+        let n = n.min(books.len());
+        let series = &books[..n];
+        group.throughput(Throughput::Elements(n as u64));
+        group.bench_with_input(BenchmarkId::new("streaming", n), series, |b, books| {
+            b.iter(|| {
+                let mut ind = make();
+                for book in books {
+                    black_box(ind.update(book.clone()));
+                }
+            });
+        });
+    }
+    group.finish();
+}
+
+fn bench_trade_input<I, F, O>(c: &mut Criterion, name: &str, trades: &[Trade], make: F)
+where
+    F: Fn() -> I,
+    I: Indicator<Input = Trade, Output = O>,
+{
+    let mut group = c.benchmark_group(name);
+    for &n in SIZES {
+        let n = n.min(trades.len());
+        let series = &trades[..n];
+        group.throughput(Throughput::Elements(n as u64));
+        group.bench_with_input(BenchmarkId::new("streaming", n), series, |b, trades| {
+            b.iter(|| {
+                let mut ind = make();
+                for t in trades {
+                    black_box(ind.update(*t));
+                }
+            });
+        });
+    }
+    group.finish();
+}
+
+fn bench_tradequote_input<I, F, O>(c: &mut Criterion, name: &str, quotes: &[TradeQuote], make: F)
+where
+    F: Fn() -> I,
+    I: Indicator<Input = TradeQuote, Output = O>,
+{
+    let mut group = c.benchmark_group(name);
+    for &n in SIZES {
+        let n = n.min(quotes.len());
+        let series = &quotes[..n];
+        group.throughput(Throughput::Elements(n as u64));
+        group.bench_with_input(BenchmarkId::new("streaming", n), series, |b, quotes| {
+            b.iter(|| {
+                let mut ind = make();
+                for q in quotes {
+                    black_box(ind.update(*q));
+                }
+            });
+        });
+    }
+    group.finish();
+}
+
 fn bench_scalar_multi<I, F, O>(c: &mut Criterion, name: &str, prices: &[f64], make: F)
 where
     F: Fn() -> I,
@@ -265,6 +332,58 @@ fn benches(c: &mut Criterion) {
     bench_scalar(c, "value_at_risk", &closes, || {
         ValueAtRisk::new(50, 0.95).unwrap()
     });
+
+    // === Family — Microstructure ===
+    // No order-book dataset ships with the repo, so synthesise a five-level
+    // book around each candle close. Benches the cheapest (top-of-book) and the
+    // most-expensive (full-depth sum) representatives of the family.
+    let books: Vec<OrderBook> = candles
+        .iter()
+        .map(|candle| {
+            let mid = candle.close;
+            let tick = (mid * 0.0001).max(0.01);
+            let bids = (0..5u32)
+                .map(|i| Level::new_unchecked(mid - tick * f64::from(i + 1), 1.0 + f64::from(i)))
+                .collect();
+            let asks = (0..5u32)
+                .map(|i| Level::new_unchecked(mid + tick * f64::from(i + 1), 1.0 + f64::from(i)))
+                .collect();
+            OrderBook::new_unchecked(bids, asks)
+        })
+        .collect();
+    bench_orderbook_input(c, "ob_imbalance_top1", &books, OrderBookImbalanceTop1::new);
+    bench_orderbook_input(c, "ob_imbalance_full", &books, OrderBookImbalanceFull::new);
+    bench_orderbook_input(c, "microprice", &books, Microprice::new);
+    bench_orderbook_input(c, "depth_slope", &books, DepthSlope::new);
+
+    // Synthesise a trade tape from candles: one trade per bar, sided by the
+    // candle's direction. SignedVolume is the cheapest; TradeImbalance carries
+    // a rolling window and is the most expensive.
+    let trades: Vec<Trade> = candles
+        .iter()
+        .map(|candle| {
+            let side = if candle.close >= candle.open {
+                Side::Buy
+            } else {
+                Side::Sell
+            };
+            Trade::new_unchecked(candle.close, candle.volume, side, candle.timestamp)
+        })
+        .collect();
+    bench_trade_input(c, "signed_volume", &trades, SignedVolume::new);
+    bench_trade_input(c, "trade_imbalance", &trades, || {
+        TradeImbalance::new(50).unwrap()
+    });
+
+    // Pair each synthetic trade with the candle close as the prevailing mid to
+    // exercise the price-impact family. EffectiveSpread is the stateless
+    // representative.
+    let quotes: Vec<TradeQuote> = trades
+        .iter()
+        .map(|trade| TradeQuote::new_unchecked(*trade, trade.price))
+        .collect();
+    bench_tradequote_input(c, "effective_spread", &quotes, EffectiveSpread::new);
+    bench_tradequote_input(c, "kyles_lambda", &quotes, || KylesLambda::new(50).unwrap());
 }
 
 criterion_group!(name = wickra_benches; config = Criterion::default(); targets = benches);