release: bump 0.6.0 -> 0.6.1 (#192)

Version bump for the v0.6.1 release shipping the B6 Bands & Channels family (#191): 429 -> 434 indicators.

.github/PULL_REQUEST_TEMPLATE/detailed.md

@@ -60,7 +60,7 @@ Closes #
 - [ ] Public API changes are reflected in `CHANGELOG.md`
 - [ ] Public API changes are reflected in rustdoc / README / examples
 - [ ] No `todo*.md` or other local-only notes are staged
-- [ ] License header / `LICENSE` reference unchanged (PolyForm-NC-1.0.0)
+- [ ] License header / `LICENSE` reference unchanged (MIT OR Apache-2.0)
 
 ## Notes for reviewers
 

.github/requirements/bench.in

@@ -5,5 +5,7 @@
 maturin
 numpy
 pandas
+TA-Lib
+tulipy
 talipp
 finta

.github/requirements/bench.txt

@@ -1,5 +1,13 @@
 # This file was autogenerated by uv via the following command:
 #    ./scripts/update-lockfiles.sh
+build==1.5.0 \
+    --hash=sha256:13f3eecb844759ab66efec90ca17639bbf14dc06cb2fdf37a9010322d9c50a6f \
+    --hash=sha256:302c22c3ba2a0fd5f3911918651341ebb3896176cbdec15bd421f80b1afc7647
+    # via ta-lib
+colorama==0.4.6 \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via build
 finta==1.3 \
     --hash=sha256:b94b94df311c18bf5402eb2fe8fd2db5e1bdaff08baf58a7367d05c7abdd10d3 \
     --hash=sha256:f2fa0673748f4be8f57e57cf6d5c00a4d44bc6071ea69dbb9a1d329d045cbba2
@@ -97,6 +105,12 @@ numpy==2.4.6 \
     #   -r .github/requirements/bench.in
     #   finta
     #   pandas
+    #   ta-lib
+    #   tulipy
+packaging==26.2 \
+    --hash=sha256:5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e \
+    --hash=sha256:ff452ff5a3e828ce110190feff1178bb1f2ea2281fa2075aadb987c2fb221661
+    # via build
 pandas==3.0.3 \
     --hash=sha256:0383c72c75cdcca61a9e116e611143902dbfd08bff356829c2f6d1cf40a9ca8c \
     --hash=sha256:05f1f1752b8533ea03f7f39a9c15b1a058d067bb48f4748948e7a8691e0510f2 \
@@ -149,6 +163,10 @@ pandas==3.0.3 \
     # via
     #   -r .github/requirements/bench.in
     #   finta
+pyproject-hooks==1.2.0 \
+    --hash=sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8 \
+    --hash=sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913
+    # via build
 python-dateutil==2.9.0.post0 \
     --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
     --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
@@ -157,10 +175,72 @@ six==1.17.0 \
     --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
     --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
     # via python-dateutil
+ta-lib==0.6.8 \
+    --hash=sha256:02388054c059945e5f02625f5075bac20a1803573cb43e7d096091027511961f \
+    --hash=sha256:094677b279a59c3f01c3aca8a889fda3523fd641a3805f69a2d642121b72e55e \
+    --hash=sha256:0a08a29690a922ba92a6cf42902a8a93c6fbda4cfed62c3c5b0471560ef60135 \
+    --hash=sha256:0ccd478ff5735831bf2a61d653466bfda8afadc26ad58ca6b1edb9e7521cc674 \
+    --hash=sha256:0e371d14b49e70caa973a234c8823341dd446f5c5d7acc826868bb42b272bdc0 \
+    --hash=sha256:11a373c9308eae3bac2d56d37017f9ab63968cc074a8b95be879aae3d13133aa \
+    --hash=sha256:128ec92e6a0e9ff7a38edef80e3b74f15bb2ed1c531d5d3252c8dca22677651b \
+    --hash=sha256:1fb4028437201e19014e4e374272b739867c8a3eb655da46675ef4c2ff14b616 \
+    --hash=sha256:282e49c766b5952dd8796f77d7ed3ae412cdd88e31f845b1fbbb86ac6cb7bebf \
+    --hash=sha256:2b369cabb48485fbf444beb3f5a878075367b99c2c86db2f796afeabebc749e0 \
+    --hash=sha256:2bf714333788bf5175f2512b86d2ed129e89ae6f6c2923e8a297a1e3395e13b5 \
+    --hash=sha256:30de46b55873b51be945a09edf486afcc190dc47eff9fb5d2b12c9f7e3d743da \
+    --hash=sha256:34e3b12407ddf99f6627435aa8a165f094339bb7dc33de92e1d7472e9f237304 \
+    --hash=sha256:36b2a516fce57309840f5ef3fa2fd0c4449293fc72536a0400d2e1e26b414da8 \
+    --hash=sha256:3a9195299df9d7d2a6e9d16bebd6b706b0ea99e4b871864c4b034c2577e21a77 \
+    --hash=sha256:3c32fc0f546ceecc47dd45f33d72ab4a1e341b80d9081c2d77b100add5d49104 \
+    --hash=sha256:3d7333e907bff3e3997e54f89733ffa8d619842a3e1cd962bca34bdc11944c28 \
+    --hash=sha256:4795e93d130c9b7fb661f0cead49752ae6a980437df74b99d5918026c212443e \
+    --hash=sha256:490e19a45cd3cdd6dfe6b46019f7ffe1103500750b41b51996a870e7c1c5f066 \
+    --hash=sha256:4aa0fe08383f3e5fc7d2f8cf9b42ac778f4d53fd75bcd2799a858225954eab89 \
+    --hash=sha256:559326d8f3d904cd4aa61f6a392d5626f35eec6a9f6cc83bcddb0abf88c40516 \
+    --hash=sha256:5929c83bd8cb7572d1c17ffdbf0eac235bf3c4d53cde1950cf89d944eaf97525 \
+    --hash=sha256:5bfd21b6acb32e20d4e279c34405a34e63da345be4b2b6eabd683e1a88857406 \
+    --hash=sha256:613cf06313331f49dd7b85a5a24fbddb1156c9723b6921a231906241726e5aee \
+    --hash=sha256:66a8e1c1e899d15a2f7510e43527fba22d895e7f6058d027db3e3837d88a69de \
+    --hash=sha256:691a62926ba09f2653ec0908554b3635497efb7751c5d46b916cd1ebbb1d3c25 \
+    --hash=sha256:6c1fd18e45c39d5a4be4b0d6a20c141e43fe46daeb1b2e2f304ebae7015ab6e6 \
+    --hash=sha256:6c6a1e8f98de92e817491b50aa4d01d69a1b41a4ed3173747e8f16f0d4cf81cc \
+    --hash=sha256:6cf029b886cfb28a2701503b7c602b811f2daa45276bd6459b0c71e051deb497 \
+    --hash=sha256:71506116eac0d3e3598d6325b4b818c3a0f6acb3222b24d30ad726e8c4bf7ea8 \
+    --hash=sha256:7993164e8e9f78ec31d38c47850ca6ba5451788b5b49a8a2dbb3322b36b5693b \
+    --hash=sha256:7a5cc6bf60791d8274edfdfe2dd7cec3f00f656dcc92e2b0a9af06c8b18ce6a6 \
+    --hash=sha256:87c1cc1057d903b78a8257a7c5f497db6fd5284f5080392bd57b66031d7389a3 \
+    --hash=sha256:98376c75bd6c103c74396953084a5e0798ffe476aecbfcc51ec6d100a685ac38 \
+    --hash=sha256:a395524b0fafa10446d11e11acb4742e919523de58aac03b791f26d7a783bcf0 \
+    --hash=sha256:a5100a4be91b7d4b7c8fe16a3600bd0951e10205eb1066b6873afd3996b51ee4 \
+    --hash=sha256:a63a52221f8c73f82f4e00493351d987f594931198589287aee96f8da673cfd5 \
+    --hash=sha256:a89734a7bcb2ea3b6fd600a74d6fbcdb8d3fa3f7917dbd978e039710b5509c9c \
+    --hash=sha256:b165f5e6de1ccc964e863bd2035807a4d3bad3e0481f9db2dc52034d6ad4f9de \
+    --hash=sha256:b3845e4c2fa32963fb7f384ebbaa2761b0e6b96145239bf80e956d4aff4b071c \
+    --hash=sha256:b3b017d9103e7a7372a146773be32b184ff7330bd708d40b1f56f06a686756ed \
+    --hash=sha256:b6c6e4858d8c3f88e19b7aa94b6a7619108f0bee51da9fa67b0785a8b59955f9 \
+    --hash=sha256:bfad1202fb1f9140e3810cc607058395f59032d9128cc0d716900c78bea5f337 \
+    --hash=sha256:c01809fb602e2fefc8cbfb3b603bb59d2a2eaee8708410896d48a835ba00e7c5 \
+    --hash=sha256:cce8de9d48289927ed18aaa420740efd52b2cd9289da32e3799afbb3a02822e8 \
+    --hash=sha256:ce2bc1ea01200b6d8130ab917296d05d77a1a571ec6c1ee25cfca6d55cd5db4a \
+    --hash=sha256:d4601e2a8b46ffbf540601a4926fd6cc5aae8a13b36fdd467f1040f01f9edaed \
+    --hash=sha256:d556d1c256b3700b60b6b061664a667b2e49d599c2772d46a9f2348f2dc4ab5c \
+    --hash=sha256:ddf7453acd03b966624ebefdb38169b5bbbeea1a1a58c90b095667247f9de327 \
+    --hash=sha256:e781eeb65b2007af553389c8a7fb7bc53cb856118b0fcffb2c26b0f49561c686 \
+    --hash=sha256:e920c272cd9e70a6b10eae9203cc96845da142e1dd4482de9343dda3738a9862 \
+    --hash=sha256:f5b6174bf4bf9152e368561dff410203c6921e4dd2afbcda3283a95957158112 \
+    --hash=sha256:f69bd42fd2515060af69b120668213121264bb7976b113954b6f9db327727c65 \
+    --hash=sha256:f823d0f6b04a6797fbe253bcf91666e71a6b63c290683819650c68b2468ebe64 \
+    --hash=sha256:fa7e9f2e80a9535f9692e113d02b4268b5f88675a730d1b0ef0abeb74c9a4e80
+    # via -r .github/requirements/bench.in
 talipp==2.7.0 \
     --hash=sha256:567f59ad74366cb59a14a00d350f35fd9d22e6924d6228bad581e6dcf1de2205 \
     --hash=sha256:f749f22b9ad615605e71faf26457bb7f5e3fe16f04d3287f4ca54fd16bc3d4eb
     # via -r .github/requirements/bench.in
+tulipy==0.4.0 \
+    --hash=sha256:540704956b5b940a5f6306aa393a37536a6d7c3cbc07efe47512f3496e5203ab \
+    --hash=sha256:95542e40537afdd345d875baf37485eac993c6a819d00c51432e9de8df21eba8 \
+    --hash=sha256:fbc31727ef7657c93ad910bfdce65fecc6aaa7a5e961fe00240718e7a3fc79d8
+    # via -r .github/requirements/bench.in
 tzdata==2026.2 \
     --hash=sha256:9173fde7d80d9018e02a662e168e5a2d04f87c41ea174b139fbef642eda62d10 \
     --hash=sha256:bbe9af844f658da81a5f95019480da3a89415801f6cc966806612cc7169bffe7

.github/workflows/bench.yml

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

.github/workflows/release.yml

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

.github/workflows/scorecard.yml

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

.github/workflows/sync-about.yml

@@ -41,17 +41,17 @@ name: Sync indicator count
 # `RollingVwap`, so the mod-count under-reports by one. lib.rs is the
 # single source of truth for what the bindings reach.
 #
-# Design: keep README in sync *before* a PR is merged, by pushing a
-# fix-up commit to the PR head branch. After squash-merge into main
-# the bot commit is folded into the single signed merge commit, so
-# main's history never shows an unsigned "sync indicator count" entry.
+# Design: on PRs this workflow is a READ-ONLY check. The indicator wiring
+# (ScriptHelpers/_common.py wire_readme_counter) bumps both README.md and
+# docs/README.md inside the author's code commit, so the counter is already
+# correct by the time CI runs. If it is not, the check below fails loud and
+# asks the author to re-run the wiring — it never pushes a fix-up commit.
 #
-# The push to PR head uses the default `GITHUB_TOKEN`, whose pushes
-# explicitly do NOT trigger downstream workflows (anti-recursion
-# policy). So a counter fix-up does not re-trigger ci.yml on the PR
-# — it does, however, re-trigger sync-about.yml on the next PR
-# `synchronize` event, which is what we want (a no-op if the counter
-# is now correct).
+# (An earlier version pushed a GITHUB_TOKEN "sync indicator count" commit to
+# the PR head. Because GITHUB_TOKEN pushes trigger no workflows, that commit
+# moved the PR head onto a commit with no CI run, which hid the Codecov patch
+# status — keyed to the PR head sha — from the PR. Keeping the counter in the
+# code commit avoids that entirely.)
 on:
   push:
     branches: [main]
@@ -73,53 +73,24 @@ permissions:
 jobs:
   sync:
     runs-on: ubuntu-latest
-    # The only GITHUB_TOKEN write in this workflow: pushing the counter fix-up
-    # commit onto a same-repo PR head branch (git push origin HEAD:<ref>).
+    # This workflow never writes to wickra-lib/wickra with GITHUB_TOKEN: the PR
+    # flow is a read-only check, and the main/tag flow writes only to other
+    # repos (About metadata, docs, webpage, wiki, org) through the fine-grained
+    # ABOUT_SYNC_TOKEN PAT. So GITHUB_TOKEN stays read-only (OpenSSF Scorecard:
+    # Token-Permissions).
     permissions:
-      contents: write
+      contents: read
       pull-requests: read
     steps:
-      # On PRs from forks the head ref lives in another repo; pushing
-      # back to it from this workflow is blocked by GitHub. We still
-      # want the PR to surface the missing counter, so the check below
-      # falls back to a hard failure when push isn't possible.
-      - name: Determine if push to PR head is possible
-        id: ctx
-        # Untrusted PR contexts (head.ref / head.repo.full_name are attacker
-        # controlled on fork PRs) are passed through the environment, never
-        # interpolated straight into the shell, so a crafted branch name cannot
-        # inject commands (OpenSSF Scorecard: Dangerous-Workflow).
-        env:
-          EVENT_NAME: ${{ github.event_name }}
-          HEAD_REPO: ${{ github.event.pull_request.head.repo.full_name }}
-          BASE_REPO: ${{ github.repository }}
-          HEAD_REF: ${{ github.event.pull_request.head.ref }}
-        run: |
-          if [ "$EVENT_NAME" = "pull_request" ]; then
-            if [ "$HEAD_REPO" = "$BASE_REPO" ]; then
-              echo "can_push=true" >> "$GITHUB_OUTPUT"
-              echo "head_ref=$HEAD_REF" >> "$GITHUB_OUTPUT"
-            else
-              echo "can_push=false" >> "$GITHUB_OUTPUT"
-              echo "head_ref=" >> "$GITHUB_OUTPUT"
-            fi
-          else
-            echo "can_push=false" >> "$GITHUB_OUTPUT"
-            echo "head_ref=" >> "$GITHUB_OUTPUT"
-          fi
-
-      # On PRs we check out the *head* commit (not the merge ref) so
-      # any fix-up commit we make goes onto the PR branch itself. On
-      # push events we check out the default ref. fetch-depth: 0 lets
-      # us push back without "shallow update not allowed".
+      # On PRs we check out the PR *head* commit (the author's code, not the
+      # merge ref) so the counter check validates exactly what will land. On
+      # push events we check out the default ref. No push is made, so a shallow
+      # checkout is enough.
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
         with:
-          fetch-depth: 0
+          fetch-depth: 1
           ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.ref || github.ref }}
           repository: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name || github.repository }}
-          # Default GITHUB_TOKEN is fine for the same-repo PR-branch
-          # push; the About / Wiki steps re-authenticate with the PAT
-          # below where needed.
 
       - name: Count indicators
         id: count
@@ -139,69 +110,33 @@ jobs:
 
       # ----- PR flow ---------------------------------------------------
 
-      - name: Check README counter (PR)
+      - name: Check README counter (PR, read-only)
         if: github.event_name == 'pull_request'
-        id: pr_check
         run: |
           n="${{ steps.count.outputs.count }}"
-          if grep -qE "^${n} streaming-first indicators" README.md \
-            && grep -qE "\*\*${n} indicators\*\*" docs/README.md; then
-            echo "matches=true" >> "$GITHUB_OUTPUT"
-            echo "README + docs/README counter already at ${n}; nothing to do."
-          else
-            echo "matches=false" >> "$GITHUB_OUTPUT"
-            echo "README/docs counter does not match ${n}; will fix up."
+          ok=true
+          if ! grep -qE "^${n} streaming-first indicators" README.md; then
+            echo "::error::README.md does not say '${n} streaming-first indicators' — lib.rs exports ${n}. Re-run the indicator wiring (it bumps README.md), then push again."
+            ok=false
           fi
-
-      - name: Fix counter on fork PR head (read-only, fail loud)
-        if: github.event_name == 'pull_request' && steps.pr_check.outputs.matches == 'false' && steps.ctx.outputs.can_push == 'false'
-        run: |
-          n="${{ steps.count.outputs.count }}"
-          echo "::error::README.md / docs/README.md say a different indicator count than lib.rs (${n}). This PR is from a fork, so the workflow cannot push the fix; please set README.md to '${n} streaming-first indicators' and docs/README.md to '**${n} indicators**', then push again."
-          exit 1
-
-      - name: Patch README on PR head
-        if: github.event_name == 'pull_request' && steps.pr_check.outputs.matches == 'false' && steps.ctx.outputs.can_push == 'true'
-        id: pr_patch
-        run: |
-          n="${{ steps.count.outputs.count }}"
-          # docs/README.md carries the count in its docs.wickra.org pointer prose
-          # ("**N indicators**"); keep it in sync with README's prose count.
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" README.md docs/README.md
-          # Bump the banner cache-buster so GitHub's Camo proxy refetches the org
-          # profile image (regenerated with the new count by .github/banner.yml)
-          # instead of serving a stale cached copy. (README only — docs has no banner.)
-          sed -i -E "s|(wickra-banner\.webp\?v=)[0-9]+|\1${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" >> "$GITHUB_OUTPUT"
-          else
-            echo "changed=true" >> "$GITHUB_OUTPUT"
+          if ! grep -qE "\*\*${n} indicators\*\*" docs/README.md; then
+            echo "::error::docs/README.md does not say '**${n} indicators**' — lib.rs exports ${n}. Re-run the indicator wiring (it bumps docs/README.md), then push again."
+            ok=false
+          fi
+          if [ "$ok" = "true" ]; then
+            echo "README.md + docs/README.md counter already at ${n}; nothing to do."
+          else
+            exit 1
           fi
-
-      - name: Commit & push counter fix to PR head
-        if: github.event_name == 'pull_request' && steps.pr_patch.outputs.changed == 'true'
-        # head_ref still carries the (untrusted) PR branch name forwarded by the
-        # ctx step; pass it through the environment so the push refspec cannot be
-        # used to inject shell commands (OpenSSF Scorecard: Dangerous-Workflow).
-        env:
-          COUNT: ${{ steps.count.outputs.count }}
-          HEAD_REF: ${{ steps.ctx.outputs.head_ref }}
-        run: |
-          git config user.name "wickra-bot"
-          git config user.email "wickra-bot@users.noreply.github.com"
-          git add README.md docs/README.md
-          git commit -m "chore: sync indicator count to ${COUNT}"
-          git push origin "HEAD:${HEAD_REF}"
 
       # ----- main / tag flow ------------------------------------------
       #
-      # After a PR squash-merges, this workflow runs again on the push
-      # to main. README is already correct (it was fixed on the PR
-      # branch before the merge); the only outward syncs left are the
-      # GitHub About description (repo metadata, not a commit) and the
-      # wiki repo (separate repo, no main history pollution). README is
-      # not touched on main any more.
+      # After a PR squash-merges, this workflow runs again on the push to main.
+      # README.md / docs/README.md are already correct (the indicator wiring
+      # bumped them in the merged code commit); the only outward syncs left are
+      # the GitHub About description (repo metadata, not a commit) and the docs /
+      # webpage / wiki / org repos (separate repos, no main history pollution).
+      # The wickra repo's own README is not touched on main any more.
 
       - name: Update GitHub About (description + homepage)
         if: github.event_name != 'pull_request'
@@ -245,14 +180,14 @@ jobs:
             exit 0
           fi
           cd docs-count
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md .vitepress/config.ts
           if git diff --quiet; then
             echo "Docs indicator count unchanged."
             exit 0
           fi
           git config user.name "wickra-bot"
           git config user.email "wickra-bot@users.noreply.github.com"
-          git add index.md overview.md Indicators-Overview.md
+          git add index.md overview.md Indicators-Overview.md .vitepress/config.ts
           git commit -m "chore: sync indicator count to ${n}"
           if ! git push 2>/dev/null; then
             echo "::warning::push to wickra-lib/wickra-docs failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."

CHANGELOG.md

@@ -7,6 +7,230 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.6.1] - 2026-06-07
+- **Projection Oscillator** — Widner projection oscillator: close position inside the projection bands, scaled 0..100 (`ProjectionOscillator`).
+- **Projection Bands** — Widner projection bands: forward-projected high/low regression envelope (`ProjectionBands`).
+- **Median Channel** — robust median +/- multiplier*MAD envelope (`MedianChannel`).
+- **Bomar Bands** — adaptive percentage bands containing a target coverage fraction of recent closes (`BomarBands`).
+- **Quartile Bands** — rolling 25th/50th/75th-percentile (Q1/median/Q3) envelope (`QuartileBands`).
+
+## [0.6.0] - 2026-06-06
+- **Volatility Cone** — volatility cone: current realized volatility within its historical min/median/max envelope (`VolatilityCone`).
+- **VolatilityRatio** — Schwager's volatility ratio: true range over the EMA of prior true ranges (`VolatilityRatio`).
+- **BipowerVariation** — jump-robust realized bipower variation (pi/2 sum of adjacent absolute log-return products) (`BipowerVariation`).
+- **VolatilityOfVolatility** — vol-of-vol: sample stddev of a rolling realized-volatility series (`VolatilityOfVolatility`).
+- **Garch11** — GARCH(1,1) conditional volatility with a long-run-variance anchor (`Garch11`).
+- **EwmaVolatility** — RiskMetrics exponentially-weighted volatility of log returns (lambda decay) (`EwmaVolatility`).
+
+## [0.5.9] - 2026-06-06
+
+### Added
+
+- Internal Rust cross-library benchmark harness (`crates/wickra-bench`, not
+  published) comparing Wickra against `kand`, `ta-rs` and `yata` on an identical
+  candle series in both streaming and batch modes; wired into the nightly
+  `cross-library-bench` workflow.
+- `tulipy` runners and expanded per-tick streaming coverage (SMA, EMA, RSI,
+  MACD, Bollinger) in the Python `compare_libraries` benchmark.
+
+### Changed
+
+- Faster streaming and batch updates for SMA, Bollinger Bands, RSI, EMA and ATR
+  (flat ring buffers replacing `VecDeque`, hoisted reciprocals in the Wilder
+  smoothing, leaner hot state) — indicator outputs are unchanged.
+- Rewrote the README benchmark section into honest, tiered tables (Rust core vs
+  the other Rust crates, and Python vs the Python ecosystem) that show where
+  Wickra wins and where it loses, not only the favourable comparisons.
+
+## [0.5.8] - 2026-06-04
+- **TSF Oscillator** — the percentage gap of the close to the one-bar-ahead time-series forecast, a close-relative companion to CFO (`TsfOscillator`).
+- **MACD Histogram** — the standalone macd-minus-signal bar of MACD as a scalar series (`MacdHistogram`).
+- **PPO Histogram** — the Percentage Price Oscillator with its signal EMA and the resulting zero-centered histogram (`PpoHistogram`).
+
+## [0.5.7] - 2026-06-04
+- **Qstick** — Qstick (Chande), the SMA of the candle body (close − open) as a net buying/selling pressure gauge (`QSTICK`).
+- **TTM Trend** — TTM Trend (John Carter), +1/−1 by whether the close sits above the SMA of recent median prices (`TTM_TREND`).
+- **Trend Strength Index** — trend strength index, the signed r² of a linear regression of price against time (`TREND_STRENGTH_INDEX`).
+- **Polarized Fractal Efficiency** — polarized fractal efficiency (Hannula), directional trend efficiency over a fractal lookback (`POLARIZED_FRACTAL_EFFICIENCY`).
+- **Wave PM** — Wave PM (Kase), a variance-normalised peak-momentum statistic (`WAVE_PM`).
+- **Gator Oscillator** — Gator Oscillator (Bill Williams), the Alligator convergence/divergence histogram (`GATOR_OSCILLATOR`).
+- **Kase Permission Stochastic** — Kase Permission Stochastic, a double-smoothed stochastic used as a trade-permission filter (`KASE_PERMISSION_STOCHASTIC`).
+
+## [0.5.6] - 2026-06-04
+- **QQE** — quantitative qualitative estimation, a smoothed RSI with an ATR-of-RSI trailing line (`QQE`).
+- **Intraday Momentum Index** — intraday momentum index (Chande), RSI on the open-to-close body (`IMI`).
+- **Elder Ray** — Elder Ray bull power and bear power around an EMA of close (`ElderRay`).
+- **Derivative Oscillator** — derivative oscillator (Constance Brown), a double-smoothed RSI histogram (`DerivativeOscillator`).
+- **RMI** — relative momentum index (RMI), RSI over a multi-bar momentum lookback (`RMI`).
+- **Stochastic CCI** — stochastic CCI, a stochastic oscillator over the CCI (`StochasticCCI`).
+- **Dynamic Momentum Index** — dynamic momentum index (Chande), a volatility-adaptive RSI (`DynamicMomentumIndex`).
+- **RSX** — RSX, a Jurik-style three-stage smoothed RSI (`RSX`).
+- **Fisher RSI** — Fisher RSI, the Fisher transform of a normalised RSI (`FisherRSI`).
+- **Disparity Index** — disparity index, the percent gap between price and its moving average (`DisparityIndex`).
+
+## [0.5.5] - 2026-06-04
+- **GD** — generalized DEMA (GD), Tillson's volume-factor double EMA and the building block of T3 (`GD`).
+- **GMA** — geometric moving average (GMA), the rolling geometric mean of prices (`GMA`).
+- **Holt-Winters** — Holt's linear (double exponential) smoothing with level and trend components (`HoltWinters`).
+- **Adaptive Laguerre** — Ehlers adaptive Laguerre filter with median-error-adaptive gamma (`AdaptiveLaguerre`).
+- **Median MA** — median moving average, the rolling median of prices (`MedianMA`).
+- **EHMA** — exponential Hull moving average (EHMA), the Hull construction built from EMAs (`EHMA`).
+- **SWMA** — sine-weighted moving average (SWMA), a symmetric half-cycle sine window (`SWMA`).
+
+## [0.5.4] - 2026-06-04
+- **Roll Measure** — effective spread implied by the negative serial covariance of trade-price changes (Roll 1984) (`RollMeasure`).
+- **Amihud Illiquidity** — average absolute log return per unit of traded value (price-impact liquidity proxy, Amihud 2002) (`AmihudIlliquidity`).
+- **VPIN** — volume-synchronised probability of informed trading (volume-bucketed order-flow toxicity) (`Vpin`).
+- **Order Flow Imbalance** — rolling sum of best-level order-flow events (Cont-Kukanov-Stoikov OFI) (`OrderFlowImbalance`).
+- **Expectancy** — expected return per unit of average loss (R-multiple) over a rolling window of returns (`Expectancy`).
+- **Win Rate** — fraction of strictly-positive returns over a rolling window (`WinRate`).
+- **Regime Label** — volatility-quantile regime classification: −1 calm / 0 normal / +1 stressed, by where the rolling volatility sits in its own recent distribution (`RegimeLabel`).
+- **Jump Indicator** — flags return outliers beyond `threshold ×` trailing return volatility (−1 down / 0 / +1 up) (`JumpIndicator`).
+- **Trend Label** — discrete trend state from the sign of the rolling least-squares slope (−1 / 0 / +1) (`TrendLabel`).
+- **High-Low Range** — bar high-low range as a fraction of close (scale-free per-bar volatility) (`HighLowRange`).
+- **Wick Ratio** — signed upper-vs-lower shadow imbalance as a fraction of the range (`WickRatio`).
+- **Body Size Percent** — absolute candle body as a fraction of the bar range (`BodySizePct`).
+- **Close vs Open** — signed body as a fraction of the open price, `(close − open) / open` (`CloseVsOpen`).
+- **Spread AR(1) Coefficient** — first-order autoregression coefficient of the spread `a − b` (direct cointegration / mean-reversion strength) (`SpreadAr1Coefficient`).
+- **Rolling Quantile** — interpolated q-th quantile over a trailing window (type-7 / NumPy default) (`RollingQuantile`).
+- **Rolling Percentile Rank** — percentile rank of the latest value within its trailing window (`RollingPercentileRank`).
+- **Rolling IQR** — interquartile range (Q3 − Q1) over a trailing window (robust dispersion) (`RollingIqr`).
+- **Realized Volatility** — square root of the summed squared log returns (raw, un-annualised quadratic variation) (`RealizedVolatility`).
+- **Log Return** — logarithmic return over a fixed lag, `ln(price_t / price_{t−period})` (`LogReturn`).
+
+## [0.5.3] - 2026-06-04
+- **Fibonacci Time Zones** — vertical markers at Fibonacci bar-distances (1/2/3/5/8/...) from the latest swing pivot (`FIB_TIME_ZONES`).
+- **Fibonacci Channel** — a sloped base trendline plus parallel lines at Fibonacci multiples of the channel width (`FIB_CHANNEL`).
+- **Fibonacci Arcs** — semicircular retracement levels centred on the swing end, normalised by leg bar-width (`FIB_ARCS`).
+- **Fibonacci Fan** — three trendlines fanning from a swing start through its 38.2/50/61.8% retracement levels (`FIB_FAN`).
+- **Fibonacci Confluence** — densest cluster of retracement levels across recent swing legs (price + strength) (`FIB_CONFLUENCE`).
+- **Golden Pocket** — the 0.618-0.65 optimal-trade-entry band of the most recent swing leg (`GOLDEN_POCKET`).
+- **Auto-Fibonacci** — retracement anchored on the dominant (largest-magnitude) leg among recent swings (`AUTO_FIB`).
+- **Fibonacci Projection** — measured-move target zone from the last three pivots (A-B-C), projecting A->B from C (`FIB_PROJECTION`).
+- **Fibonacci Extension** — projects the latest swing leg to the canonical extension ratios (127.2/141.4/161.8/200/261.8%) (`FIB_EXTENSION`).
+- **Fibonacci Retracement** — seven retracement levels (0/23.6/38.2/50/61.8/78.6/100%) of the most recent confirmed swing leg (`FIB_RETRACEMENT`).
+
+## [0.5.2] - 2026-06-03
+
+### Added
+- **Three Drives** — three symmetric drives with extension legs; bullish +1, bearish -1 (`THREE_DRIVES`).
+- **Cypher** — five-point harmonic whose D retraces XC by 0.786; bullish +1, bearish -1 (`CYPHER`).
+- **Shark** — five-point harmonic with an expansion leg and 0.886-1.13 D; bullish +1, bearish -1 (`SHARK`).
+- **Crab** — five-point harmonic with the deepest (1.618 XA) D completion; bullish +1, bearish -1 (`CRAB`).
+- **Bat** — five-point harmonic with a shallow B and 0.886 D completion; bullish +1, bearish -1 (`BAT`).
+- **Butterfly** — five-point harmonic with an extended (1.27-1.618 XA) D; bullish +1, bearish -1 (`BUTTERFLY`).
+- **Gartley** — five-point harmonic with a 0.786 D completion; bullish +1, bearish -1 (`GARTLEY`).
+- **AB=CD** — four-point AB=CD harmonic: BC retraces AB, CD mirrors AB; bullish +1, bearish -1 (`ABCD`).
+- **Cup and Handle** — rounded base with a shallow handle near the rim; bullish +1, inverse -1 (`CUP_AND_HANDLE`).
+- **Rectangle / Range** — flat support and resistance; mean-reversion signal off the just-touched boundary; support +1, resistance -1 (`RECTANGLE_RANGE`).
+- **Flag / Pennant** — shallow consolidation against a sharp pole; continuation in the pole direction; bull +1, bear -1 (`FLAG_PENNANT`).
+- **Wedge (rising/falling)** — both trendlines slope the same way but converge; rising wedge -1, falling wedge +1 (`WEDGE`).
+- **Triangle (asc/desc/sym)** — converging trendlines; ascending +1, descending -1, symmetrical follows the last swing (`TRIANGLE`).
+- **Head and Shoulders** — central head flanked by two matching shoulders over a flat neckline; top -1, inverse +1 (`HEAD_AND_SHOULDERS`).
+- **Triple Top / Bottom** — three matching peaks / troughs; a stronger reversal than the double; bearish -1, bullish +1 (`TRIPLE_TOP_BOTTOM`).
+- **Double Top / Bottom** — twin-peak / twin-trough reversal confirmed on the second matching swing extreme; bearish -1, bullish +1 (`DOUBLE_TOP_BOTTOM`).
+
+## [0.5.1] - 2026-06-03
+
+### Added — Seasonality & Session family (12 indicators)
+
+- **Volume-by-Time Profile** — mean traded volume bucketed by intraday time (`VOLUME_BY_TIME_PROFILE`).
+- **Intraday Volatility Profile** — return standard deviation bucketed by intraday time (`INTRADAY_VOLATILITY_PROFILE`).
+- **Day-of-Week Profile** — mean bar return bucketed by weekday (`DAY_OF_WEEK_PROFILE`).
+- **Time-of-Day Return Profile** — mean bar return bucketed by intraday time (`TIME_OF_DAY_RETURN_PROFILE`).
+- **Seasonal Z-Score** — z-score of the current return versus the same hour-of-day history (`SEASONAL_Z_SCORE`).
+- **Turn-of-Month** — mean daily return inside the turn-of-month window (`TURN_OF_MONTH`).
+- **Overnight/Intraday Return** — decomposition of session return into overnight and intraday legs (`OVERNIGHT_INTRADAY_RETURN`).
+- **Overnight Gap** — close-to-open return across the session boundary (`OVERNIGHT_GAP`).
+- **Average Daily Range** — mean high-low range of the last N completed sessions (`AVERAGE_DAILY_RANGE`).
+- **Session Range** — per-session (Asia/EU/US) high-low range (`SESSION_RANGE`).
+- **Session High/Low** — running high and low of the current session (`SESSION_HIGH_LOW`).
+- **Session VWAP** — session-anchored volume-weighted average price (`SESSION_VWAP`).
+
+## [0.5.0] - 2026-06-03
+
+### Added
+- **TICK Index** — instantaneous net advancing-minus-declining issues (`TICK_INDEX`).
+- **Absolute Breadth Index** — absolute value of net advancing-minus-declining issues (`ABSOLUTE_BREADTH_INDEX`).
+- **Cumulative Volume Index** — running total of volume-normalised net advancing volume (`CUMULATIVE_VOLUME_INDEX`).
+- **Bullish Percent Index** — percentage of the universe on a point-and-figure buy signal (`BULLISH_PERCENT_INDEX`).
+- **Up/Down Volume Ratio** — advancing volume divided by declining volume (`UP_DOWN_VOLUME_RATIO`).
+- **Percent Above Moving Average** — percentage of the universe trading above its reference moving average (`PERCENT_ABOVE_MA`).
+- **High-Low Index** — moving average of the record-high percentage (`HIGH_LOW_INDEX`).
+- **New Highs - New Lows** — net count of new period highs minus new period lows (`NEW_HIGHS_NEW_LOWS`).
+- **Breadth Thrust** — moving average of the advancing-issues share (Zweig) (`BREADTH_THRUST`).
+- **TRIN / Arms Index** — advance-decline ratio divided by the up-down volume ratio (`TRIN`).
+- **McClellan Summation Index** — running cumulative total of the McClellan Oscillator (`MCCLELLAN_SUMMATION_INDEX`).
+- **McClellan Oscillator** — spread between a 19- and 39-period EMA of ratio-adjusted net advances (`MCCLELLAN_OSCILLATOR`).
+- **Advance/Decline Volume Line** — cumulative net advancing-minus-declining volume across the universe (`AD_VOLUME_LINE`).
+- **Advance/Decline Ratio** — advancing issues divided by declining issues across the universe (`ADVANCE_DECLINE_RATIO`).
+
+### Changed
+- **Relicensed** from PolyForm Noncommercial 1.0.0 to dual **MIT OR Apache-2.0**. Wickra is now OSI-approved, permissive open source; commercial use is permitted under either license. See [`LICENSE-MIT`](LICENSE-MIT) and [`LICENSE-APACHE`](LICENSE-APACHE).
+
+## [0.4.7] - 2026-06-03
+
+### Added
+- **Spread Bollinger Bands** — Bollinger bands on the spread of two series for pairs mean-reversion (`SPREAD_BOLLINGER_BANDS`).
+- **Kalman Hedge Ratio** — Kalman-filter dynamic hedge ratio and spread between two series (`KALMAN_HEDGE_RATIO`).
+- **Granger Causality** — Granger causality F-statistic measuring whether one series predicts another (`GRANGER_CAUSALITY`).
+- **Variance Ratio** — Lo-MacKinlay variance-ratio test on the spread of two series (`VARIANCE_RATIO`).
+- **Beta-Neutral Spread** — beta-neutral spread: the rolling OLS regression residual of two series (`BETA_NEUTRAL_SPREAD`).
+- **Distance SSD** — Gatev sum-of-squared-deviations distance between two normalised series (`DISTANCE_SSD`).
+- **Spread Hurst** — Hurst exponent of the spread of two series for regime detection (`SPREAD_HURST`).
+- **OU Half-Life** — Ornstein-Uhlenbeck half-life of mean reversion for the spread of two series (`OU_HALF_LIFE`).
+- **Rolling Covariance** — rolling covariance of the period-over-period returns of two series (`ROLLING_COVARIANCE`).
+- **Rolling Correlation** — rolling Pearson correlation of the period-over-period returns of two series (`ROLLING_CORRELATION`).
+
+- **Market Breadth family** — a new indicator family built on a new
+  `CrossSection` input type that carries the per-symbol state of an entire
+  universe in one tick (each `Member` holds a signed `change`, a `volume`, and
+  `new_high` / `new_low` flags). `CrossSection::new` validates the universe
+  (non-empty, finite changes, finite non-negative volumes); `new_unchecked`
+  skips validation for hot paths.
+  - `AdvanceDecline` (`ADVANCE_DECLINE`) — the Advance/Decline Line, the running
+    cumulative sum of net advancing-minus-declining issues across the universe.
+
+## [0.4.6] - 2026-06-03
+
+### Added
+
+- **TA-Lib parity — Directional Movement components** — the ADX building blocks,
+  previously available only bundled inside `Adx`, as standalone single-output
+  indicators:
+  - `PlusDm` (`PLUS_DM`) — Wilder-smoothed plus directional movement.
+  - `MinusDm` (`MINUS_DM`) — Wilder-smoothed minus directional movement.
+  - `PlusDi` (`PLUS_DI`) — plus directional indicator, `100 · smoothed(+DM) / ATR`.
+  - `MinusDi` (`MINUS_DI`) — minus directional indicator, `100 · smoothed(-DM) / ATR`.
+  - `Dx` (`DX`) — directional movement index, `100 · |+DI − −DI| / (+DI + −DI)`.
+- **TA-Lib parity — price transforms** — window and per-bar price aggregates:
+  - `MidPrice` (`MIDPRICE`) — `(highest high + lowest low) / 2` over a window.
+  - `MidPoint` (`MIDPOINT`) — `(max + min) / 2` of a scalar series over a window.
+  - `AvgPrice` (`AVGPRICE`) — per-bar `(open + high + low + close) / 4`.
+- **TA-Lib parity — rate-of-change variants** — the ratio forms of `Roc`:
+  - `Rocp` (`ROCP`) — `(close − close[period]) / close[period]` (fraction).
+  - `Rocr` (`ROCR`) — `close / close[period]` (ratio).
+  - `Rocr100` (`ROCR100`) — `close / close[period] · 100`.
+- **TA-Lib parity — linear-regression outputs** — the remaining OLS endpoints:
+  - `LinRegIntercept` (`LINEARREG_INTERCEPT`) — the OLS intercept `a`.
+  - `Tsf` (`TSF`) — time series forecast, `a + b·period` (one bar ahead).
+- **TA-Lib parity — `MacdFix` (`MACDFIX`)** — MACD with fast/slow fixed at 12/26
+  and only the signal period configurable; output is the usual `{macd, signal,
+  histogram}` triple.
+- **TA-Lib parity — `SarExt` (`SAREXT`)** — Parabolic SAR with a start value,
+  reversal offset, independent long/short acceleration, and a signed output
+  (positive in long phases, negative in short phases).
+- **TA-Lib parity — `MacdExt` (`MACDEXT`)** — MACD with an independently
+  selectable moving-average type (new `MaType` enum: SMA/EMA/WMA/DEMA/TEMA/TRIMA)
+  for each of the fast, slow and signal lines.
+- **TA-Lib parity — `HtPhasor` (`HT_PHASOR`)** — the in-phase and quadrature
+  components of the Hilbert-transform analytic signal, as a `{inphase,
+  quadrature}` pair.
+- **TA-Lib parity — `HtDcPhase` (`HT_DCPHASE`)** — the phase angle (in degrees)
+  of the Hilbert-transform dominant cycle.
+- **TA-Lib parity — `HtTrendMode` (`HT_TRENDMODE`)** — Ehlers' trend (`1`) vs
+  cycle (`0`) classification from the Hilbert-transform dominant cycle.
+
 ## [0.4.5] - 2026-06-02
 
 ### Added
@@ -1084,7 +1308,21 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   optional Binance live feed.
 - Bindings for Python, Node.js, and WebAssembly.
 
-[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.4.5...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.6.1...HEAD
+[0.6.1]: https://github.com/wickra-lib/wickra/compare/v0.6.0...v0.6.1
+[0.6.0]: https://github.com/wickra-lib/wickra/compare/v0.5.9...v0.6.0
+[0.5.9]: https://github.com/wickra-lib/wickra/compare/v0.5.8...v0.5.9
+[0.5.8]: https://github.com/wickra-lib/wickra/compare/v0.5.7...v0.5.8
+[0.5.7]: https://github.com/wickra-lib/wickra/compare/v0.5.6...v0.5.7
+[0.5.6]: https://github.com/wickra-lib/wickra/compare/v0.5.5...v0.5.6
+[0.5.5]: https://github.com/wickra-lib/wickra/compare/v0.5.4...v0.5.5
+[0.5.4]: https://github.com/wickra-lib/wickra/compare/v0.5.3...v0.5.4
+[0.5.3]: https://github.com/wickra-lib/wickra/compare/v0.5.2...v0.5.3
+[0.5.2]: https://github.com/wickra-lib/wickra/compare/v0.5.1...v0.5.2
+[0.5.1]: https://github.com/wickra-lib/wickra/compare/v0.5.0...v0.5.1
+[0.5.0]: https://github.com/wickra-lib/wickra/compare/v0.4.7...v0.5.0
+[0.4.7]: https://github.com/wickra-lib/wickra/compare/v0.4.6...v0.4.7
+[0.4.6]: https://github.com/wickra-lib/wickra/compare/v0.4.5...v0.4.6
 [0.4.5]: https://github.com/wickra-lib/wickra/compare/v0.4.4...v0.4.5
 [0.4.4]: https://github.com/wickra-lib/wickra/compare/v0.4.3...v0.4.4
 [0.4.3]: https://github.com/wickra-lib/wickra/compare/v0.4.2...v0.4.3

CITATION.cff

@@ -26,4 +26,6 @@ keywords:
   - quantitative-finance
   - rust
   - time-series
-license: PolyForm-Noncommercial-1.0.0
+license:
+  - MIT
+  - Apache-2.0

CONTRIBUTING.md

@@ -5,11 +5,11 @@ build the project, the standards a change must meet, and how to get it merged.
 
 ## License of contributions
 
-Wickra is licensed under the **PolyForm Noncommercial License 1.0.0** (see
-[`LICENSE`](LICENSE)). By submitting a contribution you agree that it is
-licensed to the project under those same terms. The Noncommercial license
-permits use for any purpose **other than** a commercial one; keep that in mind
-when proposing features or depending on Wickra elsewhere.
+Wickra is dual-licensed under the [MIT](LICENSE-MIT) and
+[Apache-2.0](LICENSE-APACHE) licenses; users may choose either. Unless you
+explicitly state otherwise, any contribution you intentionally submit for
+inclusion in the work, as defined in the Apache-2.0 license, shall be dual
+licensed as above, without any additional terms or conditions.
 
 ## Project layout
 
@@ -122,3 +122,33 @@ installed. Dependabot also keeps the `.github/requirements` pins current.
 Use the issue templates under
 [`.github/ISSUE_TEMPLATE`](.github/ISSUE_TEMPLATE). For security-sensitive
 reports, follow [`SECURITY.md`](SECURITY.md) instead of opening a public issue.
+
+## Developer Certificate of Origin (DCO)
+
+All contributions to Wickra are made under the [Developer Certificate of
+Origin (DCO) 1.1](DCO). By signing off on your commits you certify that you
+wrote the patch, or otherwise have the right to submit it under the project's
+`MIT OR Apache-2.0` license.
+
+Sign off every commit by adding a `Signed-off-by` trailer with your real name
+and email — Git adds it automatically with the `-s` flag:
+
+```bash
+git commit -s -m "your message"
+```
+
+This produces a trailer of the form:
+
+```
+Signed-off-by: Your Name <you@example.com>
+```
+
+The name and email must match the commit author. Commits without a valid
+sign-off line cannot be merged. To sign off a commit you already made, amend it
+with `git commit -s --amend`, or sign off a range with an interactive rebase.
+
+## Governance
+
+Wickra's decision-making and maintainership are described in
+[`GOVERNANCE.md`](GOVERNANCE.md); the current maintainers are listed in
+[`MAINTAINERS.md`](MAINTAINERS.md).

Cargo.lock

@@ -702,6 +702,16 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "kand"
+version = "0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "af1f41590bd014ef6c3dd815b45f07deb4c3198e355a4319bb7521b6a3a6aeb5"
+dependencies = [
+ "num_enum",
+ "thiserror",
+]
+
 [[package]]
 name = "leb128fmt"
 version = "0.1.0"
@@ -911,6 +921,28 @@ dependencies = [
  "libm",
 ]
 
+[[package]]
+name = "num_enum"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5d0bca838442ec211fa11de3a8b0e0e8f3a4522575b5c4c06ed722e005036f26"
+dependencies = [
+ "num_enum_derive",
+ "rustversion",
+]
+
+[[package]]
+name = "num_enum_derive"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "680998035259dcfcafe653688bf2aa6d3e2dc05e98be6ab46afb089dc84f1df8"
+dependencies = [
+ "proc-macro-crate",
+ "proc-macro2",
+ "quote",
+ "syn",
+]
+
 [[package]]
 name = "numpy"
 version = "0.28.0"
@@ -1081,6 +1113,15 @@ dependencies = [
  "syn",
 ]
 
+[[package]]
+name = "proc-macro-crate"
+version = "3.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f"
+dependencies = [
+ "toml_edit",
+]
+
 [[package]]
 name = "proc-macro2"
 version = "1.0.106"
@@ -1498,6 +1539,12 @@ dependencies = [
  "syn",
 ]
 
+[[package]]
+name = "ta"
+version = "0.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "609409d472a0a7d8d4dd9e19891bbdef546b9dce670c3057d0e02192dc541226"
+
 [[package]]
 name = "target-lexicon"
 version = "0.13.5"
@@ -1607,6 +1654,36 @@ dependencies = [
  "tungstenite",
 ]
 
+[[package]]
+name = "toml_datetime"
+version = "1.1.1+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7"
+dependencies = [
+ "serde_core",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.25.12+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d2153edc6955a6c354fad8f5efd38b6a8769bdccf9fe50f8e1329f81b0baa5d7"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "toml_parser",
+ "winnow",
+]
+
+[[package]]
+name = "toml_parser"
+version = "1.1.2+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a2abe9b86193656635d2411dc43050282ca48aa31c2451210f4202550afb7526"
+dependencies = [
+ "winnow",
+]
+
 [[package]]
 name = "tungstenite"
 version = "0.29.0"
@@ -1867,7 +1944,7 @@ dependencies = [
 
 [[package]]
 name = "wickra"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "approx",
  "criterion",
@@ -1876,9 +1953,21 @@ dependencies = [
  "wickra-data",
 ]
 
+[[package]]
+name = "wickra-bench"
+version = "0.6.1"
+dependencies = [
+ "criterion",
+ "kand",
+ "ta",
+ "wickra",
+ "wickra-data",
+ "yata",
+]
+
 [[package]]
 name = "wickra-core"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "approx",
  "proptest",
@@ -1888,7 +1977,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-data"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "approx",
  "csv",
@@ -1905,7 +1994,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-examples"
-version = "0.0.0"
+version = "0.6.1"
 dependencies = [
  "serde_json",
  "tokio",
@@ -1915,7 +2004,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-node"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "napi",
  "napi-build",
@@ -1925,7 +2014,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-python"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "numpy",
  "pyo3",
@@ -1934,7 +2023,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-wasm"
-version = "0.4.5"
+version = "0.6.1"
 dependencies = [
  "console_error_panic_hook",
  "js-sys",
@@ -1991,6 +2080,15 @@ dependencies = [
  "windows-link",
 ]
 
+[[package]]
+name = "winnow"
+version = "1.0.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0592e1c9d151f854e6fd382574c3a0855250e1d9b2f99d9281c6e6391af352f1"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "wit-bindgen"
 version = "0.51.0"
@@ -2091,6 +2189,15 @@ version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "1ffae5123b2d3fc086436f8834ae3ab053a283cfac8fe0a0b8eaae044768a4c4"
 
+[[package]]
+name = "yata"
+version = "0.7.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6b4ef8ddfa3ccd93454262c0e60a43a2bbf403d404174e1815f7581d5028229f"
+dependencies = [
+ "serde",
+]
+
 [[package]]
 name = "yoke"
 version = "0.8.2"

Cargo.toml

@@ -8,15 +8,16 @@ members = [
     "bindings/wasm",
     "bindings/node",
     "examples/rust",
+    "crates/wickra-bench",
 ]
 exclude = ["fuzz"]
 
 [workspace.package]
-version = "0.4.5"
+version = "0.6.1"
 authors = ["kingchenc <support@wickra.org>"]
 edition = "2021"
 rust-version = "1.86"
-license-file = "LICENSE"
+license = "MIT OR Apache-2.0"
 repository = "https://github.com/wickra-lib/wickra"
 homepage = "https://github.com/wickra-lib/wickra"
 readme = "README.md"
@@ -24,7 +25,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
 categories = ["finance", "mathematics", "science"]
 
 [workspace.dependencies]
-wickra-core = { path = "crates/wickra-core", version = "0.4.5" }
+wickra-core = { path = "crates/wickra-core", version = "0.6.1" }
 
 thiserror = "2"
 rayon = "1.10"

DCO

@@ -0,0 +1,34 @@
+Developer Certificate of Origin
+Version 1.1
+
+Copyright (C) 2004, 2006 The Linux Foundation and its contributors.
+
+Everyone is permitted to copy and distribute verbatim copies of this
+license document, but changing it is not allowed.
+
+
+Developer's Certificate of Origin 1.1
+
+By making a contribution to this project, I certify that:
+
+(a) The contribution was created in whole or in part by me and I
+    have the right to submit it under the open source license
+    indicated in the file; or
+
+(b) The contribution is based upon previous work that, to the best
+    of my knowledge, is covered under an appropriate open source
+    license and I have the right under that license to submit that
+    work with modifications, whether created in whole or in part
+    by me, under the same open source license (unless I am
+    permitted to submit under a different license), as indicated
+    in the file; or
+
+(c) The contribution was provided directly to me by some other
+    person who certified (a), (b) or (c) and I have not modified
+    it.
+
+(d) I understand and agree that this project and the contribution
+    are public and that a record of the contribution (including all
+    personal information I submit with it, including my sign-off) is
+    maintained indefinitely and may be redistributed consistent with
+    this project or the open source license(s) involved.

GOVERNANCE.md

@@ -0,0 +1,71 @@
+# Governance
+
+Wickra is an open-source project maintained under a **single-maintainer
+("BDFL") model**. This document describes how decisions are made and how the
+project is run, so contributors know what to expect.
+
+## Roles
+
+- **Maintainer.** The maintainer (see [`MAINTAINERS.md`](MAINTAINERS.md)) is
+  responsible for the project's direction, reviews and merges changes, cuts
+  releases, and has final say on all technical and project decisions.
+- **Contributors.** Anyone who proposes changes via pull requests, files
+  issues, improves documentation, or otherwise participates. Contributors do
+  not need any special status to take part.
+
+## Decision-making
+
+- Day-to-day technical decisions (APIs, indicator implementations, refactors)
+  are made by the maintainer, informed by discussion on issues and pull
+  requests.
+- Proposals are raised as GitHub issues or pull requests. Significant or
+  breaking changes should be opened as an issue first to agree on the approach
+  before implementation.
+- The maintainer aims to act transparently: rationale for non-trivial decisions
+  is recorded in the relevant issue, pull request, or commit message.
+
+## Contribution flow
+
+All changes — including the maintainer's own — go through pull requests so that
+CI (tests, linting, static analysis) runs against them, and so the change
+history is reviewable. Contribution requirements are documented in
+[`CONTRIBUTING.md`](CONTRIBUTING.md), including the Developer Certificate of
+Origin sign-off that every commit must carry.
+
+## Becoming a maintainer
+
+The project currently has one maintainer. Maintainership may be extended to
+contributors who have demonstrated sustained, high-quality involvement, at the
+current maintainer's discretion. If the project grows to multiple maintainers,
+this document will be updated to describe shared decision-making.
+
+## Continuity and succession
+
+The project is designed to survive the loss of any single individual, so that
+issues can be triaged, proposed changes accepted, and releases published within
+one week of confirmed loss of the maintainer:
+
+- **Credentials.** All credentials required to operate the project — the
+  `wickra-lib` GitHub organization, the publishing tokens for crates.io, PyPI
+  and npm, and the `wickra.org` domain registrar — are stored in a password
+  manager. A trusted contact (a family member) holds **emergency access** to
+  that password manager and can obtain these credentials if the maintainer can
+  no longer continue.
+- **Continuity actions.** With that access, the trusted contact (or a delegate
+  they appoint) can create and close issues, accept pull requests, and publish
+  releases through the existing CI/CD workflows.
+- **Account recovery.** The maintainer's GitHub account has recovery configured,
+  and ownership of the `wickra-lib` organization can be transferred to a new
+  maintainer.
+- **Legal rights.** Legal rights to the project name and DNS are covered by the
+  maintainer's estate arrangements.
+
+## Code of conduct
+
+All participants are expected to follow the
+[Code of Conduct](CODE_OF_CONDUCT.md).
+
+## Changes to this document
+
+This governance model may evolve as the project grows. Changes are made via
+pull request and take effect once merged.

LICENSE

@@ -1,161 +0,0 @@
-# PolyForm Noncommercial License 1.0.0
-
-<https://polyformproject.org/licenses/noncommercial/1.0.0>
-
-## Acceptance
-
-In order to get any license under these terms, you must agree
-to them as both strict obligations and conditions to all
-your licenses.
-
-## Copyright License
-
-The licensor grants you a copyright license for the
-software to do everything you might do with the software
-that would otherwise infringe the licensor's copyright
-in it for any permitted purpose. However, you may
-only distribute the software according to [Distribution
-License](#distribution-license) and make changes or new works
-based on the software according to [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Distribution License
-
-The licensor grants you an additional copyright license
-to distribute copies of the software. Your license to
-distribute covers distributing the software with changes
-and new works permitted by [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Notices
-
-You must ensure that anyone who gets a copy of any part of
-the software from you also gets a copy of these terms or the
-URL for them above, as well as copies of any plain-text lines
-beginning with `Required Notice:` that the licensor provided
-with the software. For example:
-
-> Required Notice: Copyright 2026 kingchenc (https://github.com/wickra-lib/wickra)
-
-## Changes and New Works License
-
-The licensor grants you an additional copyright license
-to make changes and new works based on the software for any
-permitted purpose.
-
-## Patent License
-
-The licensor grants you a patent license for the software that
-covers patent claims the licensor can license, or becomes able
-to license, that you would infringe by using the software.
-
-## Noncommercial Purposes
-
-Any noncommercial purpose is a permitted purpose.
-
-## Personal Uses
-
-Personal use for research, experiment, and testing for
-the benefit of public knowledge, personal study, private
-entertainment, hobby projects, amateur pursuits, or religious
-observance, without any anticipated commercial application,
-is use for a permitted purpose.
-
-## Noncommercial Organizations
-
-Use by any charitable organization, educational institution,
-public research organization, public safety or health
-organization, environmental protection organization, or
-government institution is use for a permitted purpose regardless
-of the source of funding or obligations resulting from the
-funding.
-
-## Fair Use
-
-You may have "fair use" rights for the software under the
-law. These terms do not limit them.
-
-## No Other Rights
-
-These terms do not allow you to sublicense or transfer any of
-your licenses to anyone else, or prevent the licensor from
-granting licenses to anyone else.  These terms do not imply
-any other licenses.
-
-## Patent Defense
-
-If you make any written claim that the software infringes or
-contributes to infringement of any patent, your patent license
-for the software granted under these terms ends immediately. If
-your company makes such a claim, your patent license ends
-immediately for work on behalf of your company.
-
-## Violations
-
-The first time you are notified in writing that you have
-violated any of these terms, or done anything with the software
-not covered by your licenses, your licenses can nonetheless
-continue if you come into full compliance with these terms,
-and take practical steps to correct past violations, within 32
-days of receiving notice.  Otherwise, all your licenses end
-immediately.
-
-## No Liability
-
-***As far as the law allows, the software comes as is, without
-any warranty or condition, and the licensor will not be liable
-to you for any damages arising out of these terms or the use
-or nature of the software, under any kind of legal claim.***
-
-## Definitions
-
-The **licensor** is the individual or entity offering these
-terms, and the **software** is the software the licensor makes
-available under these terms.
-
-**You** refers to the individual or entity agreeing to these
-terms.
-
-**Your company** is any legal entity, sole proprietorship,
-or other kind of organization that you work for, plus all
-organizations that have control over, are under the control
-of, or are under common control with that organization.
-**Control** means ownership of substantially all the assets
-of an entity, or the power to direct its management and
-policies by vote, contract, or otherwise.  Control can be
-direct or indirect.
-
-**Your licenses** are all the licenses granted to you for the
-software under these terms.
-
-**Use** means anything you do with the software requiring one
-of your licenses.
-
-## 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)

LICENSE-APACHE

@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+
+      "You" (or "Your") shall mean an individual or Legal Entity
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+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright 2026 kingchenc and the Wickra contributors
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

LICENSE-MIT

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 kingchenc and the Wickra contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSES/Apache-2.0.txt

@@ -0,0 +1,201 @@
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+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
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+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
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+
+   Copyright 2026 kingchenc and the Wickra contributors
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
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+   See the License for the specific language governing permissions and
+   limitations under the License.

LICENSES/MIT.txt

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 kingchenc and the Wickra contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

MAINTAINERS.md

@@ -0,0 +1,17 @@
+# Maintainers
+
+This file lists the current maintainers of Wickra. See
+[`GOVERNANCE.md`](GOVERNANCE.md) for what the role entails and how the project
+is run.
+
+| Maintainer | GitHub | Areas |
+| --- | --- | --- |
+| kingchenc | [@kingchenc](https://github.com/kingchenc) | All (core, bindings, CI/release, docs) |
+
+## Contacting the maintainers
+
+- General questions and support: see [`SUPPORT.md`](SUPPORT.md).
+- Bug reports and feature requests: open an issue using the
+  [issue templates](.github/ISSUE_TEMPLATE).
+- Security reports: follow [`SECURITY.md`](SECURITY.md) — do **not** open a
+  public issue.

README.md

@@ -1,5 +1,5 @@
 <p align="center">
-  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=295" alt="Wickra — streaming-first technical indicators" width="100%"></a>
+  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=434" alt="Wickra — streaming-first technical indicators" width="100%"></a>
 </p>
 
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
@@ -9,8 +9,9 @@
 [![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
 [![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
 [![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](#license)
 [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/wickra-lib/wickra/badge)](https://scorecard.dev/viewer/?uri=github.com/wickra-lib/wickra)
+[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/13094/badge)](https://www.bestpractices.dev/projects/13094)
 [![Build provenance](https://img.shields.io/badge/provenance-attested-brightgreen?logo=github)](https://github.com/wickra-lib/wickra/attestations)
 [![Docs](https://img.shields.io/badge/docs-docs.wickra.org-0ea5e9?logo=readthedocs&logoColor=white)](https://docs.wickra.org)
 
@@ -47,7 +48,7 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
   [Node](https://docs.wickra.org/Quickstart-Node),
   [WASM](https://docs.wickra.org/Quickstart-WASM).
 - **Indicators** — a per-indicator deep dive (formula, parameters, warmup) for
-  every one of the 295 indicators; start at the
+  every one of the 434 indicators; start at the
   [indicators overview](https://docs.wickra.org/Indicators-Overview).
 - **Reference** — [warmup periods](https://docs.wickra.org/Warmup-Periods),
   [streaming vs batch](https://docs.wickra.org/Streaming-vs-Batch),
@@ -59,108 +60,165 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
 
 ## Why Wickra exists
 
-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
+Wickra started as a personal itch. The existing TA libraries never quite fit the
+projects I was building, so I decided to build one from the ground up — partly to
+learn, partly because I genuinely enjoy taking something that already exists and
+trying to do it differently (and, ideally, better). It's open source because the
+useful version of that itch is the one other people can build on too.
 
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★&nbsp;Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
+Plenty of TA libraries are fast. Each one forces a trade-off Wickra does not:
 
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
+| Library          | Install     | Streaming   | Languages                   | Indicators | Active |
+|------------------|-------------|-------------|-----------------------------|-----------:|--------|
+| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Python · Node · WASM · Rust** | **423** | **yes** |
+| kand             | clean       | yes         | Python · WASM · Rust        |       ~60  | yes    |
+| ta-rs            | clean       | yes         | Rust only                   |       ~30  | stale  |
+| yata             | clean       | partial     | Rust only                   |       ~35  | yes    |
+| TA-Lib           | yes (C deps)| no          | many bindings               |      ~150  | barely |
+| pandas-ta        | clean       | no          | Python                      |      ~130  | slow   |
+| finta            | clean       | no          | Python                      |       ~80  | stale  |
+| talipp           | clean       | yes         | Python                      |       ~40  | yes    |
 
-## Benchmark: how much faster is "streaming-first"?
+Wickra's edge is **breadth with reach**: 434 indicators that all update in O(1)
+per tick and ship natively to Python, Node.js, WebAssembly and Rust from a
+single engine.
 
-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
+**On speed — and why Wickra isn't the fastest.** It deliberately isn't. The
+leaner Rust crates (kand, ta-rs) win several of the micro-benchmarks below, and
+those losses are shown rather than hidden. The gap is a *choice*, not a ceiling:
+every `update` validates its input, runs a real warmup before it emits a value,
+and returns an `Option` so a single bad tick can't silently poison the state.
+ta-rs, by contrast, hands back a bare `f64` from the first tick with no
+validation. If Wickra threw all of that away — raw `f64` out, no checks, no
+warmup contract — it would match or beat the leanest crate on every row. It
+keeps the guarantees instead, and still wins RSI, Bollinger and ATR against kand.
+What no other library matches is the *combination*: catalogue size, native O(1)
+streaming, NaN-safety, and four first-class language targets at once.
+
+## Benchmarks
+
+Three comparisons, split by layer and mode. Read them as **relative** speedups
+on identical input — absolute µs depend on CPU, memory clock and OS scheduler,
+not a universal contract.
 
 - **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
-- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
+  Rust 1.92 (release: `lto = "fat"`, `codegen-units = 1`), Python 3.12.
+- **Reproduce yourself:**
+  - Rust core vs Rust crates: `cargo bench -p wickra-bench`
+  - Python vs Python libs: `pip install -e bindings/python[bench]` then
+    `python -m benchmarks.compare_libraries` (auto-detects installed peers).
 
-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
+### 1. Rust core vs the other Rust TA crates
 
-### Batch — single full pass over a 20 000-bar series
+Like-for-like, no language-binding overhead, over a 50 000-bar series (µs for
+the whole series, lower = faster). This is the honest engine comparison —
+Wickra wins some and loses some, and both are shown.
 
-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
+**Streaming** (one value fed per `update`):
 
-| Indicator           | **★&nbsp;Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
+| Indicator        | **★&nbsp;Wickra** | kand | ta-rs | yata |
+|------------------|------------------:|-----:|------:|-----:|
+| SMA(20)          | 50                | 38   | 47    | 38   |
+| EMA(20)          | 154               | 69   | 56    | 69   |
+| RSI(14)          | 164               | 216  | 74    | —    |
+| MACD(12, 26, 9)  | 275               | 143  | 66    | —    |
+| Bollinger(20, 2) | **128 ★**         | 248  | 168   | —    |
+| ATR(14)          | 152               | 166  | 61    | —    |
 
-### Streaming — per-tick latency after seeding with 5 000 historical bars
+**Batch** (whole series at once). Only Wickra and kand expose a batch API;
+ta-rs and yata are streaming-only.
 
-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
+| Indicator        | **★&nbsp;Wickra** | kand |
+|------------------|------------------:|-----:|
+| SMA(20)          | 82                | 42   |
+| EMA(20)          | 159               | 74   |
+| RSI(14)          | **253 ★**         | 274  |
+| MACD(12, 26, 9)  | 681               | 283  |
+| Bollinger(20, 2) | **445 ★**         | 462  |
+| ATR(14)          | 175               | 173  |
 
-| Indicator | **★&nbsp;Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
+ta-rs is the per-indicator speed champion on almost every row — it returns a
+bare `f64` with no warmup state and no input validation, trading away the
+`None`-warmup and NaN-safety semantics Wickra keeps. Against kand, Wickra wins
+streaming RSI, Bollinger and ATR (and batch RSI + Bollinger); Bollinger is the
+one row where Wickra is the outright fastest of all four. The leaner crates
+still win the pure recurrences (EMA, MACD) and SMA. yata exposes only SMA/EMA as
+raw-value methods, so its other rows are omitted rather than faked.
 
-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
+### 2. Python vs the Python TA ecosystem — batch
+
+Full pass over a 20 000-bar series, µs/op (lower = faster). **★** per row.
+
+| Indicator        | **★&nbsp;Wickra** | finta               | TA-Lib | tulipy |
+|------------------|------------------:|---------------------|--------|--------|
+| SMA(20)          | **59.6 ★**        | 354.2 (5.9× slower) | ⧗      | ⧗      |
+| EMA(20)          | **88.4 ★**        | 309.3 (3.5× slower) | ⧗      | ⧗      |
+| RSI(14)          | **77.3 ★**        | 1 283 (16.6× slower)| ⧗      | ⧗      |
+| MACD(12, 26, 9)  | **116.4 ★**       | 529.5 (4.6× slower) | ⧗      | ⧗      |
+| Bollinger(20, 2) | **146.0 ★**       | 1 246 (8.5× slower) | ⧗      | ⧗      |
+| ATR(14)          | **135.8 ★**       | 3 812 (28× slower)  | ⧗      | ⧗      |
+
+> ⧗ = published by the CI Linux job. TA-Lib and tulipy ship C extensions that
+> don't build cleanly on every desktop, so their canonical numbers come from the
+> `cross-library-bench` workflow rather than this local table. pandas-ta needs
+> Python ≥ 3.12 and isn't in the 3.11 CI matrix. The script auto-detects
+> whichever peers are installed in your environment.
+
+### 3. Python — streaming (per-tick latency)
+
+Seed 5 000 bars, then feed ticks one at a time. talipp is the only Python peer
+with a true incremental API; batch-only libraries like TA-Lib must recompute the
+entire history on every tick — Wickra updates in O(1).
+
+| Indicator        | **★&nbsp;Wickra (per tick)** | talipp (per tick)       |
+|------------------|------------------------------:|-------------------------|
+| SMA(20)          | **0.067 µs ★**                | 0.63 µs (9.4× slower)   |
+| EMA(20)          | **0.051 µs ★**                | 0.63 µs (12.2× slower)  |
+| RSI(14)          | **0.053 µs ★**                | 1.00 µs (19.1× slower)  |
+| MACD(12, 26, 9)  | **0.071 µs ★**                | 3.64 µs (51.5× slower)  |
+| Bollinger(20, 2) | **0.085 µs ★**                | 4.87 µs (57.2× slower)  |
 
 Run the suite yourself:
 
 ```bash
-pip install -e bindings/python[bench]
+cargo bench -p wickra-bench            # Rust core vs kand / ta-rs / yata
+pip install -e bindings/python[bench]  # Python peers
 python -m benchmarks.compare_libraries
 ```
 
 ## Indicators
 
-295 streaming-first indicators across nineteen families. Every one passes the
+434 streaming-first indicators across twenty-four families. Every one passes the
 `batch == streaming` equivalence test, reference-value tests, and reset
 semantics tests. Each has a per-indicator deep dive (formula, parameters,
 warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
 
 | Family | Indicators |
 |--------|-----------|
-| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA |
-| Momentum Oscillators | RSI (Wilder), Anchored RSI, Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia |
-| Trend & Directional  | MACD, ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
+| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA, SWMA, GMA, EHMA, Median MA, Adaptive Laguerre, GD, Holt-Winters |
+| Momentum Oscillators | RSI (Wilder), Anchored RSI, Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia, ROC Percentage (ROCP), ROC Ratio (ROCR), ROC Ratio 100 (ROCR100), Disparity Index, Fisher RSI, RSX, Dynamic Momentum Index, Stochastic CCI, RMI, Derivative Oscillator, Elder Ray, Intraday Momentum Index, QQE |
+| Trend & Directional  | MACD, MACD Fixed (MACDFIX), MACD Extended (MACDEXT), ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter, Plus DM, Minus DM, Plus DI, Minus DI, DX, TTM Trend, Trend Strength Index, Qstick, Polarized Fractal Efficiency, Wave PM, Gator Oscillator, Kase Permission Stochastic |
+| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC, TSF Oscillator, MACD Histogram, PPO Histogram |
+| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Volatility Cone |
+| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands, Quartile Bands, Bomar Bands, Median Channel, Projection Bands, Projection Oscillator |
+| Trailing Stops       | Parabolic SAR, Parabolic SAR Extended (SAREXT), SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
 | Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
+| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation, Mid Price, Mid Point, Average Price, Linear Regression Intercept, Time Series Forecast, Rolling Correlation, Rolling Covariance, OU Half-Life, Spread Hurst, Distance SSD, Beta-Neutral Spread, Variance Ratio, Granger Causality, Kalman Hedge Ratio, Spread Bollinger Bands, Spread AR(1) Coefficient |
+| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Hilbert Phasor, Hilbert DC Phase, Hilbert Trend Mode, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
 | Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
 | DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
 | Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
 | Alt-Chart Bars       | Renko (box-size bricks), Kagi (reversal-amount lines), Point & Figure (X/O columns) |
 | Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down, Two Crows, Upside Gap Two Crows, Identical Three Crows, Three Line Strike, Three Stars in the South, Abandoned Baby, Advance Block, Belt-hold, Breakaway, Counterattack, Doji Star, Dragonfly Doji, Gravestone Doji, Long-Legged Doji, Rickshaw Man, Evening Doji Star, Morning Doji Star, Gap Side-by-Side White, High-Wave, Hikkake, Modified Hikkake, Homing Pigeon, On-Neck, In-Neck, Thrusting, Separating Lines, Kicking, Kicking by Length, Ladder Bottom, Mat Hold, Matching Low, Long Line, Short Line, Rising Three Methods, Falling Three Methods, Upside Gap Three Methods, Downside Gap Three Methods, Stalled Pattern, Stick Sandwich, Takuri, Closing Marubozu, Opening Marubozu, Tasuki Gap, Unique Three River, Concealing Baby Swallow |
-| 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 |
+| Chart Patterns       | Double Top / Bottom, Triple Top / Bottom, Head and Shoulders, Triangle (asc/desc/sym), Wedge (rising/falling), Flag / Pennant, Rectangle / Range, Cup and Handle |
+| Harmonic Patterns    | AB=CD, Gartley, Butterfly, Bat, Crab, Shark, Cypher, Three Drives |
+| Fibonacci            | Fibonacci Retracement, Fibonacci Extension, Fibonacci Projection, Auto-Fibonacci, Golden Pocket, Fibonacci Confluence, Fibonacci Fan, Fibonacci Arcs, Fibonacci Channel, Fibonacci Time Zones |
+| Microstructure       | Order-Book Imbalance (Top-1 / Top-N / Full), Microprice, Quoted Spread, Depth Slope, Signed Volume, Cumulative Volume Delta, Trade Imbalance, Effective Spread, Realized Spread, Kyle's Lambda, Footprint, Order Flow Imbalance, VPIN, Amihud Illiquidity, Roll Measure |
 | Derivatives          | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread |
 | Market Profile       | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range |
+| Market Breadth       | Advance/Decline Line, Advance/Decline Ratio, Advance/Decline Volume Line, McClellan Oscillator, McClellan Summation Index, TRIN / Arms Index, Breadth Thrust, New Highs - New Lows, High-Low Index, Percent Above Moving Average, Up/Down Volume Ratio, Bullish Percent Index, Cumulative Volume Index, Absolute Breadth Index, TICK Index |
 | Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
+| Seasonality & Session | Session VWAP, Session High/Low, Session Range, Average Daily Range, Overnight Gap, Overnight/Intraday Return, Turn-of-Month, Seasonal Z-Score, Time-of-Day Return Profile, Day-of-Week Profile, Intraday Volatility Profile, Volume-by-Time Profile |
 
 Every candlestick pattern emits a signed per-bar value — `+1.0` bullish,
 `−1.0` bearish, `0.0` none — so the family drops straight into a feature matrix
@@ -239,9 +297,10 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 295 indicators
+│   ├── wickra-core/         core engine + all 434 indicators
 │   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   ├── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   └── wickra-bench/        internal cross-library benchmark harness (not published)
 ├── bindings/
 │   ├── python/              PyO3 + maturin (publishes on PyPI)
 │   ├── node/                napi-rs (publishes on npm)
@@ -255,9 +314,10 @@ wickra/
 └── .github/workflows/       CI and release pipelines
 ```
 
-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
+Wickra's own regression benchmarks live in `crates/wickra/benches/`; the
+cross-library comparison against kand, ta-rs and yata lives in the internal
+`crates/wickra-bench/` crate. Runnable Rust examples live in the workspace member
+crate at `examples/rust/`. There is no top-level `benches/` directory.
 
 ## Building everything from source
 
@@ -265,7 +325,8 @@ in the workspace member crate at `examples/rust/`. There is no top-level
 # Rust core + tests
 cargo test --workspace
 cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+cargo bench -p wickra           # Wickra's own regression benchmarks
+cargo bench -p wickra-bench     # cross-library comparison (kand, ta-rs, yata)
 
 # Python binding (requires Rust toolchain + maturin)
 cd bindings/python
@@ -323,13 +384,20 @@ shape together before you invest the time.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
+Licensed under either of
 
-In plain English: use it, fork it, modify it, redistribute it, file issues, send
-pull requests — all welcome. Personal projects, research, education, non-profits,
-government, hobby trading bots: all fine. The one thing that's not allowed is
-commercial sale of the software or of services built around it. If you want to
-use Wickra commercially, get in touch about a license.
+- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or
+  <http://www.apache.org/licenses/LICENSE-2.0>)
+- MIT license ([LICENSE-MIT](LICENSE-MIT) or <http://opensource.org/licenses/MIT>)
+
+at your option. Use it, fork it, modify it, redistribute it — commercially or
+not — file issues, send pull requests; all welcome.
+
+### Contribution
+
+Unless you explicitly state otherwise, any contribution intentionally submitted
+for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
+dual licensed as above, without any additional terms or conditions.
 
 ## Disclaimer
 
@@ -358,3 +426,10 @@ The library is provided **as is**, without warranty of any kind; see
 <p align="center">
   If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
 </p>
+
+<p align="center">
+  <a href="https://star-history.com/#wickra-lib/wickra&Date">
+    <img alt="Wickra star history" width="640"
+         src="https://api.star-history.com/svg?repos=wickra-lib/wickra&type=Date&theme=dark">
+  </a>
+</p>

ROADMAP.md

@@ -0,0 +1,36 @@
+# Roadmap
+
+This roadmap describes the project's direction at a high level. It is
+intentionally non-binding: priorities shift with feedback and available time,
+and the authoritative, up-to-date view of planned work is the
+[issue tracker](https://github.com/wickra-lib/wickra/issues). Shipped changes
+are recorded in [`CHANGELOG.md`](CHANGELOG.md).
+
+## Status
+
+Wickra is **pre-1.0**. The public API is largely stable but may still change in
+minor releases; breaking changes are called out in the changelog.
+
+## Themes
+
+- **Indicator coverage.** Continue broadening the indicator catalogue across
+  families (trend, momentum, volatility, volume, statistics, market profile,
+  and more), each with the same streaming/batch parity and test guarantees.
+- **API stabilization toward 1.0.** Settle the public `Indicator` and
+  `BarBuilder` traits and the binding surfaces, then commit to semantic
+  versioning stability for a 1.0 release.
+- **Performance.** Keep per-tick updates O(1) and maintain the benchmark suite;
+  investigate further allocation and cache improvements.
+- **Bindings parity.** Keep the Python, Node.js and WebAssembly bindings in
+  lockstep with the Rust core, including type stubs and platform coverage.
+- **Documentation.** Maintain a deep-dive page per indicator on
+  <https://docs.wickra.org>, plus quickstarts and cookbook material.
+- **Project health.** Maintain test coverage, static and dynamic analysis,
+  signed releases, and supply-chain monitoring.
+
+## How to influence the roadmap
+
+Open or comment on an issue, or start with the
+[feature-request template](.github/ISSUE_TEMPLATE/feature_request.md).
+Well-scoped proposals and pull requests are the most effective way to move an
+item forward.

SECURITY.md

@@ -2,13 +2,13 @@
 
 ## Supported versions
 
-Wickra is pre-1.0. Security fixes are applied to the latest released `0.1.x`
+Wickra is pre-1.0. Security fixes are applied to the latest released `0.5.x`
 version only; please upgrade to the newest release before reporting an issue.
 
 | Version | Supported |
 | --- | --- |
-| 0.1.x (latest) | :white_check_mark: |
-| older 0.1.x | :x: |
+| 0.5.x (latest) | :white_check_mark: |
+| older 0.5.x | :x: |
 
 ## Reporting a vulnerability
 
@@ -41,3 +41,99 @@ PyPI/npm packages, and the build/release workflows in `.github/workflows/`.
 
 Out of scope: vulnerabilities in third-party dependencies (report those
 upstream; we track them via Dependabot and `cargo-deny`).
+
+## Security assurance case
+
+This is a short, evidence-backed argument for why Wickra can be used safely.
+
+**Security requirements.** Wickra is a computational library: it ingests
+numeric market data and produces indicator values. It stores no user
+credentials, authenticates no external users, and implements no cryptography of
+its own. The requirements are therefore: (1) memory safety and freedom from
+undefined behaviour, (2) robust handling of untrusted/degenerate numeric input
+without panics or unbounded resource use, (3) integrity of the published
+artifacts, and (4) a healthy dependency supply chain.
+
+**How the requirements are met.**
+
+- *Memory safety* — the core and all bindings are written in Rust. The crates
+  forbid or minimise `unsafe`, so the compiler guarantees memory and thread
+  safety for the indicator logic.
+- *Input robustness* — every indicator validates its parameters and rejects
+  non-finite inputs at construction; behaviour on edge cases (flat markets,
+  warmup, reset) is pinned by unit tests, and the public update paths are
+  exercised by coverage-guided fuzzing (`cargo-fuzz` / libFuzzer) in CI.
+- *Static and dynamic analysis* — every push and pull request runs Clippy
+  (`clippy::pedantic`, warnings-as-errors), CodeQL, fuzzing, and the full test
+  suite, with 100% line coverage on the core crate tracked by Codecov.
+- *Artifact integrity* — releases are built in CI, commits and tags are signed,
+  the `main` branch requires signed commits, and release artifacts carry build
+  provenance attestations.
+- *Supply chain* — dependencies are pinned and monitored with Dependabot and
+  audited with `cargo-deny` (license + advisory checks) on every change.
+
+**Residual risk.** The optional `live-binance` feature opens a TLS WebSocket to
+an exchange using the platform TLS library; transport security therefore
+depends on that library, not on Wickra. Wickra is not a trading system and is
+provided "as is" — see the disclaimers in `README.md` and the licenses.
+
+## Secrets management
+
+The project stores **no** secrets or credentials in the version control system.
+Secrets required by automation (publishing tokens, the about-sync PAT) are kept
+exclusively as **GitHub Actions encrypted secrets** and referenced via the
+`secrets.*` context; they are never written to the repository, logs, or build
+artifacts. GitHub **secret scanning with push protection** is enabled to block
+accidental commits of credentials. Secrets follow least privilege (the narrowest
+scope that works) and are rotated when a holder changes or on suspected
+exposure.
+
+## Verifying releases
+
+Released artifacts can be verified for integrity and authenticity:
+
+- **Build provenance.** Release assets carry GitHub build provenance
+  attestations. Verify a downloaded asset with the GitHub CLI:
+  `gh attestation verify <file> --repo wickra-lib/wickra`.
+- **Signed tags.** Each release corresponds to a signed git tag (`vX.Y.Z`);
+  the tag signature identifies the maintainer who authorised the release.
+- **Registry integrity.** Packages are distributed over HTTPS from crates.io,
+  PyPI and npm, which serve package checksums that package managers verify on
+  install.
+
+The release is published only by the maintainer through the tag-triggered
+release workflow, so a verified tag signature establishes the expected
+publisher identity.
+
+## Support timeline and end of support
+
+Wickra is **pre-1.0**: only the **latest released `0.y.z`** version receives
+security fixes. When a newer release is published, the previous version
+**immediately reaches end of support** and will not receive further fixes;
+users should upgrade to the latest release. The supported-versions table above
+is authoritative. After the `1.0.0` release this policy will be revised to
+support a defined window of releases.
+
+## Remediation policy (dependencies and code scanning)
+
+- **Severity threshold.** Vulnerabilities of **medium severity or higher** in
+  the project's own code or its dependencies are remediated promptly and before
+  the next release; lower-severity findings are addressed on a best-effort
+  basis.
+- **Automated enforcement (SCA).** Every change is evaluated by `cargo-deny`
+  (RUSTSEC advisories + license policy) and Dependabot; a known-vulnerable
+  dependency fails CI and **blocks the change** until resolved or explicitly
+  waived with justification.
+- **Automated enforcement (SAST).** Every change is evaluated by CodeQL and
+  Clippy (`-D warnings`); findings **block the change** in CI until fixed.
+- **Pre-release gate.** A release is not cut while an unresolved medium-or-higher
+  SCA/SAST finding is outstanding.
+
+## Vulnerability exploitability (VEX)
+
+Advisories reported by `cargo-deny`/Dependabot for third-party dependencies that
+do **not** affect Wickra (e.g. the vulnerable code path is not reachable, or the
+affected feature is not enabled) are triaged and recorded — with the
+not-affected justification — in the `cargo-deny` configuration (`deny.toml`) and
+the relevant pull request, rather than forcing an unnecessary dependency bump.
+This serves as the project's exploitability (VEX) record.

SUPPORT.md

@@ -0,0 +1,37 @@
+# Support
+
+Thanks for using Wickra! Here is where to get help, depending on what you need.
+
+## Documentation first
+
+Most questions are answered in the documentation:
+
+- **Docs site:** <https://docs.wickra.org> — quickstarts for Rust, Python,
+  Node.js and WebAssembly, a per-indicator reference, warmup periods, the data
+  layer, and an FAQ.
+- **README:** <https://github.com/wickra-lib/wickra#readme> — installation and a
+  quick overview.
+- **API docs (Rust):** <https://docs.rs/wickra>.
+
+## Questions and help
+
+- Ask a question with the
+  [question issue template](.github/ISSUE_TEMPLATE/question.md).
+- Browse [existing issues](https://github.com/wickra-lib/wickra/issues) — your
+  question may already be answered.
+
+## Bugs and feature requests
+
+- **Bugs:** use the bug-report issue template.
+- **Feature requests / new indicators:** use the feature-request template.
+
+## Security issues
+
+Please do **not** report security vulnerabilities through public issues. Follow
+the process in [`SECURITY.md`](SECURITY.md) (private GitHub advisory or email).
+
+## Support expectations
+
+Wickra is maintained by a single maintainer on a best-effort basis. Issues are
+triaged and acknowledged as time allows; there is no commercial support or SLA.
+Clear, reproducible reports get help fastest.

THREAT_MODEL.md

@@ -0,0 +1,54 @@
+# Threat model
+
+This document describes Wickra's attack surface and the threats considered,
+together with their mitigations. It complements the security assurance case in
+[`SECURITY.md`](SECURITY.md). Wickra is a computational technical-analysis
+library (a Rust core with Python, Node.js and WebAssembly bindings), not a
+network service or trading system; the attack surface is correspondingly small.
+
+## Assets
+
+- **Integrity of computed indicator values** — consumers may use them in
+  automated decisions, so silently wrong output is the primary concern.
+- **Availability of the calling process** — a library must not crash or hang
+  its host on malformed input.
+- **Integrity of published artifacts** — the crates, wheels and npm packages
+  users install.
+- **The build and release pipeline** and its secrets (publishing tokens).
+
+## Actors / trust boundaries
+
+- **Library consumer** (trusted) — calls the API with numeric data. Data may
+  originate from untrusted sources (e.g. a market feed), so *input values* are
+  treated as untrusted even though the caller is trusted.
+- **Optional live feed** — with the `live-binance` feature, data crosses a
+  network boundary from an exchange over TLS.
+- **Contributors** (semi-trusted) — propose changes via pull requests.
+- **Supply chain** — upstream dependencies and the CI/CD platform.
+
+## Threats and mitigations
+
+| Threat | Mitigation |
+| --- | --- |
+| Memory-safety exploit (buffer overflow, UAF) via crafted input | Pure safe Rust; `unsafe` is forbidden/minimised, so the compiler precludes these classes. |
+| Denial of service via malformed/degenerate input (NaN, infinities, extreme magnitudes) | Indicators reject non-finite inputs and validate parameters at construction; update paths are exercised by coverage-guided fuzzing and unit tests for edge cases. |
+| Silently incorrect results | 100% line coverage on the core crate; reference-value tests against known-good sources; streaming/batch parity tests. |
+| Integer overflow / panics | `clippy::pedantic` with `-D warnings`; debug assertions and overflow checks enabled in test/fuzz builds. |
+| Adversary-in-the-middle on the optional live feed | Connection uses TLS via the platform library; transport security is delegated to that reviewed implementation. |
+| Compromised dependency (supply chain) | Dependencies pinned (`Cargo.lock`, hash-locked CI requirements), monitored by Dependabot, audited by `cargo-deny` (advisories + licenses) on every change. |
+| Malicious or accidental change to `main` | Branch protection requires signed commits and blocks force-push and deletion; all changes flow through pull requests with required CI; static analysis (CodeQL, Clippy) and fuzzing run on every change. |
+| Compromised CI / leaked secrets | Workflows use least-privilege `permissions:`; secrets live only as encrypted GitHub Actions secrets; secret scanning with push protection is enabled; workflows are linted by `zizmor`. |
+| Tampered release artifact | Releases are built in CI, tags are signed, and assets carry build provenance attestations (verifiable with `gh attestation verify`). |
+
+## Out of scope
+
+- Wickra implements no authentication, authorization or cryptography of its own,
+  stores no user data, and exposes no network listener; those threat classes do
+  not apply.
+- Vulnerabilities in third-party dependencies that do not affect Wickra are
+  tracked as exploitability (VEX) records (see [`SECURITY.md`](SECURITY.md)).
+
+## Maintenance
+
+This threat model is reviewed when the architecture changes materially (for
+example, a new input family, a new network feature, or a new release channel).

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-file.workspace = true
+license.workspace = true
 repository.workspace = true
 homepage.workspace = true
 readme.workspace = true

bindings/node/README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
 
 **Streaming-first technical indicators for Node.js. `npm install wickra` —
 prebuilt native binary, no system dependencies.**
@@ -67,7 +67,5 @@ risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/node/__tests__/indicators.test.js

@@ -28,6 +28,45 @@ function num(v) {
 // --- Scalar indicators: update(value) vs batch(prices) ---
 
 const scalarFactories = {
+  BipowerVariation: () => new wickra.BipowerVariation(20),
+  VolatilityOfVolatility: () => new wickra.VolatilityOfVolatility(20, 20),
+  Garch11: () => new wickra.Garch11(0.000002, 0.1, 0.88),
+  EwmaVolatility: () => new wickra.EwmaVolatility(0.94),
+  PpoHistogram: () => new wickra.PpoHistogram(3, 6, 3),
+  MacdHistogram: () => new wickra.MacdHistogram(3, 6, 3),
+  TsfOscillator: () => new wickra.TsfOscillator(3),
+  WAVE_PM: () => new wickra.WAVE_PM(32, 3),
+  POLARIZED_FRACTAL_EFFICIENCY: () => new wickra.POLARIZED_FRACTAL_EFFICIENCY(10, 5),
+  TREND_STRENGTH_INDEX: () => new wickra.TREND_STRENGTH_INDEX(20),
+  DerivativeOscillator: () => new wickra.DerivativeOscillator(14, 5, 3, 9),
+  RMI: () => new wickra.RMI(14, 5),
+  DynamicMomentumIndex: () => new wickra.DynamicMomentumIndex(14),
+  RSX: () => new wickra.RSX(14),
+  FisherRSI: () => new wickra.FisherRSI(14),
+  DisparityIndex: () => new wickra.DisparityIndex(14),
+  HoltWinters: () => new wickra.HoltWinters(0.2, 0.1),
+  GD: () => new wickra.GD(5, 0.7),
+  AdaptiveLaguerre: () => new wickra.AdaptiveLaguerre(13),
+  MedianMA: () => new wickra.MedianMA(14),
+  EHMA: () => new wickra.EHMA(9),
+  GMA: () => new wickra.GMA(14),
+  SWMA: () => new wickra.SWMA(14),
+  Expectancy: () => new wickra.Expectancy(20),
+  WinRate: () => new wickra.WinRate(20),
+  RegimeLabel: () => new wickra.RegimeLabel(5, 20),
+  JumpIndicator: () => new wickra.JumpIndicator(20, 3.0),
+  TrendLabel: () => new wickra.TrendLabel(10),
+  RollingQuantile: () => new wickra.RollingQuantile(20, 0.5),
+  RollingPercentileRank: () => new wickra.RollingPercentileRank(14),
+  RollingIqr: () => new wickra.RollingIqr(14),
+  RealizedVolatility: () => new wickra.RealizedVolatility(20),
+  LogReturn: () => new wickra.LogReturn(1),
+  TSF: () => new wickra.TSF(14),
+  LINEARREG_INTERCEPT: () => new wickra.LINEARREG_INTERCEPT(14),
+  ROCR100: () => new wickra.ROCR100(10),
+  ROCR: () => new wickra.ROCR(10),
+  ROCP: () => new wickra.ROCP(10),
+  MIDPOINT: () => new wickra.MIDPOINT(14),
   SMA: () => new wickra.SMA(14),
   EMA: () => new wickra.EMA(14),
   WMA: () => new wickra.WMA(14),
@@ -90,6 +129,8 @@ const scalarFactories = {
   EhlersStochastic: () => new wickra.EhlersStochastic(20),
   EmpiricalModeDecomposition: () => new wickra.EmpiricalModeDecomposition(20, 0.5),
   HilbertDominantCycle: () => new wickra.HilbertDominantCycle(),
+  HT_DCPHASE: () => new wickra.HT_DCPHASE(),
+  HT_TRENDMODE: () => new wickra.HT_TRENDMODE(),
   AdaptiveCycle: () => new wickra.AdaptiveCycle(),
   SineWave: () => new wickra.SineWave(),
   FAMA: () => new wickra.FAMA(0.5, 0.05),
@@ -159,10 +200,17 @@ for (const [name, make] of Object.entries(scalarFactories)) {
 // --- Scalar-output candle indicators: update(...) vs batch(...) ---
 
 const candleScalar = {
+  MIDPRICE: { make: () => new wickra.MIDPRICE(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  DX: { make: () => new wickra.DX(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  MINUS_DI: { make: () => new wickra.MINUS_DI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  PLUS_DI: { make: () => new wickra.PLUS_DI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   ATR: { make: () => new wickra.ATR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  PLUS_DM: { make: () => new wickra.PLUS_DM(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  MINUS_DM: { make: () => new wickra.MINUS_DM(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   CCI: { make: () => new wickra.CCI(20), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   WilliamsR: { make: () => new wickra.WilliamsR(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   PSAR: { make: () => new wickra.PSAR(0.02, 0.02, 0.2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  SAREXT: { make: () => new wickra.SAREXT(0, 0, 0.02, 0.02, 0.2, 0.02, 0.02, 0.2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   MFI: { make: () => new wickra.MFI(14), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
   VWAP: { make: () => new wickra.VWAP(), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
   RollingVWAP: { make: () => new wickra.RollingVWAP(20), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
@@ -170,6 +218,7 @@ const candleScalar = {
   OBV: { make: () => new wickra.OBV(), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
   VWMA: { make: () => new wickra.VWMA(20), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
   RVI: { make: () => new wickra.RVI(10), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  AVGPRICE: { make: () => new wickra.AVGPRICE(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   Inertia: { make: () => new wickra.Inertia(14, 20), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   PGO: { make: () => new wickra.PGO(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   SMI: { make: () => new wickra.SMI(5, 3, 3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
@@ -281,6 +330,32 @@ const candleScalar = {
   TasukiGap: { make: () => new wickra.TasukiGap(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   UniqueThreeRiver: { make: () => new wickra.UniqueThreeRiver(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   ConcealingBabySwallow: { make: () => new wickra.ConcealingBabySwallow(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DoubleTopBottom: { make: () => new wickra.DoubleTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TripleTopBottom: { make: () => new wickra.TripleTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HeadAndShoulders: { make: () => new wickra.HeadAndShoulders(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Triangle: { make: () => new wickra.Triangle(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Wedge: { make: () => new wickra.Wedge(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  FlagPennant: { make: () => new wickra.FlagPennant(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  RectangleRange: { make: () => new wickra.RectangleRange(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  CupAndHandle: { make: () => new wickra.CupAndHandle(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Abcd: { make: () => new wickra.Abcd(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Gartley: { make: () => new wickra.Gartley(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Butterfly: { make: () => new wickra.Butterfly(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Bat: { make: () => new wickra.Bat(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Crab: { make: () => new wickra.Crab(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Shark: { make: () => new wickra.Shark(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Cypher: { make: () => new wickra.Cypher(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ThreeDrives: { make: () => new wickra.ThreeDrives(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  CloseVsOpen: { make: () => new wickra.CloseVsOpen(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  BodySizePct: { make: () => new wickra.BodySizePct(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  WickRatio: { make: () => new wickra.WickRatio(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HighLowRange: { make: () => new wickra.HighLowRange(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  StochasticCCI: { make: () => new wickra.StochasticCCI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  IMI: { make: () => new wickra.IMI(14), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TTM_TREND: { make: () => new wickra.TTM_TREND(6), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Qstick: { make: () => new wickra.Qstick(10), step: (ind, i) => ind.update(open[i], close[i]), batch: (ind) => ind.batch(open, close) },
+  VolatilityRatio: { make: () => new wickra.VolatilityRatio(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  ProjectionOscillator: { make: () => new wickra.ProjectionOscillator(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
 };
 
 for (const [name, d] of Object.entries(candleScalar)) {
@@ -302,6 +377,9 @@ const multi = {
   Alligator: { make: () => new wickra.Alligator(13, 8, 5), fields: ['jaw', 'teeth', 'lips'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
   ZeroLagMACD: { make: () => new wickra.ZeroLagMACD(12, 26, 9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
   MACD: { make: () => new wickra.MACD(12, 26, 9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  HT_PHASOR: { make: () => new wickra.HT_PHASOR(), fields: ['inphase', 'quadrature'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MACDFIX: { make: () => new wickra.MACDFIX(9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MACDEXT: { make: () => new wickra.MACDEXT(12, 0, 26, 0, 9, 0), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
   KST: { make: () => wickra.KST.classic(), fields: ['kst', 'signal'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
   BollingerBands: { make: () => new wickra.BollingerBands(20, 2), fields: ['upper', 'middle', 'lower', 'stddev'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
   Stochastic: { make: () => new wickra.Stochastic(14, 3), fields: ['k', 'd'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
@@ -350,6 +428,25 @@ const multi = {
   // Family 13: Ichimoku & alternative charts
   Ichimoku: { make: () => new wickra.Ichimoku(9, 26, 52, 26), fields: ['tenkan', 'kijun', 'senkouA', 'senkouB', 'chikou'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   HeikinAshi: { make: () => new wickra.HeikinAshi(), fields: ['open', 'high', 'low', 'close'], step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  FibRetracement: { make: () => new wickra.FibRetracement(), fields: ['level0', 'level236', 'level382', 'level500', 'level618', 'level786', 'level1000'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibExtension: { make: () => new wickra.FibExtension(), fields: ['level1272', 'level1414', 'level1618', 'level2000', 'level2618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibProjection: { make: () => new wickra.FibProjection(), fields: ['level618', 'level1000', 'level1618', 'level2618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  AutoFib: { make: () => new wickra.AutoFib(), fields: ['level0', 'level236', 'level382', 'level500', 'level618', 'level786', 'level1000'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  GoldenPocket: { make: () => new wickra.GoldenPocket(), fields: ['low', 'mid', 'high'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibConfluence: { make: () => new wickra.FibConfluence(), fields: ['price', 'strength'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibFan: { make: () => new wickra.FibFan(), fields: ['fan382', 'fan500', 'fan618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibArcs: { make: () => new wickra.FibArcs(), fields: ['arc382', 'arc500', 'arc618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibChannel: { make: () => new wickra.FibChannel(), fields: ['base', 'level618', 'level1000', 'level1618'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  FibTimeZones: { make: () => new wickra.FibTimeZones(), fields: ['onZone', 'barsToNext'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  ElderRay: { make: () => new wickra.ElderRay(13), fields: ['bullPower', 'bearPower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  QQE: { make: () => new wickra.QQE(14, 5, 4.236), fields: ['rsiMa', 'trailingLine'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  GatorOscillator: { make: () => new wickra.GatorOscillator(13, 8, 5), fields: ['upper', 'lower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  KasePermissionStochastic: { make: () => new wickra.KasePermissionStochastic(9, 3), fields: ['fast', 'slow'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  VolatilityCone: { make: () => new wickra.VolatilityCone(20, 60), fields: ['current', 'min', 'median', 'max', 'percentile'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  QuartileBands: { make: () => new wickra.QuartileBands(4), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  BomarBands: { make: () => new wickra.BomarBands(4, 0.85), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MedianChannel: { make: () => new wickra.MedianChannel(5, 2.0), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  ProjectionBands: { make: () => new wickra.ProjectionBands(3), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
 };
 
 for (const [name, d] of Object.entries(multi)) {
@@ -510,6 +607,15 @@ const pairFactories = {
   PairwiseBeta: () => new wickra.PairwiseBeta(14),
   PairSpreadZScore: () => new wickra.PairSpreadZScore(14, 14),
   SpearmanCorrelation: () => new wickra.SpearmanCorrelation(14),
+  RollingCorrelation: () => new wickra.RollingCorrelation(20),
+  RollingCovariance: () => new wickra.RollingCovariance(20),
+  OuHalfLife: () => new wickra.OuHalfLife(60),
+  SpreadHurst: () => new wickra.SpreadHurst(60),
+  DistanceSsd: () => new wickra.DistanceSsd(20),
+  BetaNeutralSpread: () => new wickra.BetaNeutralSpread(20),
+  VarianceRatio: () => new wickra.VarianceRatio(60, 2),
+  GrangerCausality: () => new wickra.GrangerCausality(60, 1),
+  SpreadAr1Coefficient: () => new wickra.SpreadAr1Coefficient(40),
 };
 
 for (const [name, make] of Object.entries(pairFactories)) {
@@ -600,6 +706,47 @@ test('Cointegration batch is flat 3*n with last row matching', () => {
   assert.ok(out[3 * (n - 1) + 2] < -2);
 });
 
+test('KalmanHedgeRatio converges to a static hedge ratio (object output)', () => {
+  const n = 500;
+  const b = Array.from({ length: n }, (_, t) => 100 + 95 * Math.sin(t * 0.5));
+  const a = b.map((v) => 2 * v + 5);
+  const k = new wickra.KalmanHedgeRatio(1e-2, 1e-3);
+  let last = null;
+  for (let i = 0; i < n; i++) last = k.update(a[i], b[i]);
+  assert.ok(Math.abs(last.hedgeRatio - 2) < 0.05);
+  assert.ok(Math.abs(last.spread) < 0.05);
+});
+
+test('KalmanHedgeRatio batch is flat 3*n with last row matching', () => {
+  const n = 500;
+  const b = Array.from({ length: n }, (_, t) => 100 + 95 * Math.sin(t * 0.5));
+  const a = b.map((v) => 2 * v + 5);
+  const out = new wickra.KalmanHedgeRatio(1e-2, 1e-3).batch(a, b);
+  assert.equal(out.length, 3 * n);
+  assert.ok(Math.abs(out[3 * (n - 1)] - 2) < 0.05);
+  assert.ok(Math.abs(out[3 * (n - 1) + 2]) < 0.05);
+});
+
+test('SpreadBollingerBands bands are ordered (object output)', () => {
+  const n = 60;
+  const b = Array.from({ length: n }, (_, t) => 100 + t);
+  const a = b.map((v, t) => v + 3 * Math.sin(t * 0.4));
+  const bb = new wickra.SpreadBollingerBands(20, 2.0);
+  let last = null;
+  for (let i = 0; i < n; i++) last = bb.update(a[i], b[i]);
+  assert.ok(last.lower <= last.middle && last.middle <= last.upper);
+});
+
+test('SpreadBollingerBands batch is flat 4*n with last row matching', () => {
+  const n = 60;
+  const b = Array.from({ length: n }, (_, t) => 100 + t);
+  const a = b.map((v, t) => v + 3 * Math.sin(t * 0.4));
+  const out = new wickra.SpreadBollingerBands(20, 2.0).batch(a, b);
+  assert.equal(out.length, 4 * n);
+  const base = 4 * (n - 1);
+  assert.ok(out[base + 2] <= out[base] && out[base] <= out[base + 1]);
+});
+
 test('RelativeStrengthAB constant ratio is flat (object output)', () => {
   const rs = new wickra.RelativeStrengthAB(5, 5);
   let last = null;
@@ -1032,6 +1179,57 @@ test('trade-flow rejects bad input', () => {
   assert.throws(() => new wickra.SignedVolume().update(100, -1, true));
 });
 
+test('order-flow imbalance reference + streaming matches batch', () => {
+  // Rising bid (px up, size 6) with an unchanged ask -> +6 flow.
+  const ofi = new wickra.OrderFlowImbalance(1);
+  assert.equal(ofi.update([100], [5], [101], [4]), null); // seeds the reference
+  assert.ok(Math.abs(ofi.update([100.5], [6], [101], [4]) - 6.0) < 1e-12);
+  const snaps = Array.from({ length: 30 }, (_, i) => ({
+    bidPx: [100 + Math.sin(i * 0.3)],
+    bidSz: [5 + Math.abs(Math.cos(i * 0.5))],
+    askPx: [101 + Math.sin(i * 0.3)],
+    askSz: [4 + Math.abs(Math.sin(i * 0.4))],
+  }));
+  const batch = new wickra.OrderFlowImbalance(10).batch(snaps);
+  const streamer = new wickra.OrderFlowImbalance(10);
+  assert.equal(batch.length, snaps.length);
+  for (let i = 0; i < snaps.length; i++) {
+    const s = streamer.update(snaps[i].bidPx, snaps[i].bidSz, snaps[i].askPx, snaps[i].askSz);
+    assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
+  }
+});
+
+test('vpin / amihud / roll reference + streaming matches batch', () => {
+  // VPIN: two pure-buy buckets of size 10 -> imbalance == size -> 1.
+  const v = new wickra.Vpin(10, 2);
+  let last;
+  for (let i = 0; i < 4; i++) last = v.update(100, 5, true);
+  assert.equal(last, 1.0);
+  // Amihud(1): |ln(101/100)| / (101 * 10).
+  const a = new wickra.AmihudIlliquidity(1);
+  assert.equal(a.update(100, 10, true), null);
+  assert.ok(Math.abs(a.update(101, 10, true) - Math.abs(Math.log(101 / 100)) / (101 * 10)) < 1e-15);
+  // Roll(6): a clean bid-ask bounce of ±1 implies a spread of 2.
+  const r = new wickra.RollMeasure(6);
+  let roll = null;
+  for (let i = 0; i < 20; i++) roll = r.update(i % 2 === 0 ? 100 : 101, 1, true);
+  assert.ok(Math.abs(roll - 2.0) < 1e-12);
+  // Streaming-vs-batch for the three trade-input indicators.
+  const n = 40;
+  const price = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.25) * 4);
+  const size = Array.from({ length: n }, (_, i) => 1 + (i % 5));
+  const isBuy = Array.from({ length: n }, (_, i) => i % 2 === 0);
+  for (const make of [() => new wickra.Vpin(8, 5), () => new wickra.AmihudIlliquidity(14), () => new wickra.RollMeasure(14)]) {
+    const batch = make().batch(price, size, isBuy);
+    const streamer = make();
+    assert.equal(batch.length, n);
+    for (let i = 0; i < n; i++) {
+      const s = streamer.update(price[i], size[i], isBuy[i]);
+      assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
+    }
+  }
+});
+
 test('price-impact indicators reference values', () => {
   // Buy at 100.05 vs mid 100.0: 2 * (100.05 - 100) / 100 * 10000 = 10 bps.
   assert.ok(Math.abs(new wickra.EffectiveSpread().update(100.05, 1, true, 100.0) - 10.0) < 1e-9);
@@ -1183,6 +1381,145 @@ test('derivatives reject bad input', () => {
   assert.throws(() => new wickra.FundingBasis().update(100, 0));
 });
 
+test('market breadth: AdvanceDecline reference values', () => {
+  // A breadth tick is the universe as parallel arrays; the sign of `change`
+  // classifies each symbol as advancing / declining / unchanged.
+  const change = [
+    [1.0, 0.5, 2.0, -1.0], // 3 up, 1 down -> net +2
+    [-1.0, -0.5, -2.0, 1.0], // 1 up, 3 down -> net -2
+    [0.0, 0.0, 1.0, -1.0], // 1 up, 1 down -> net 0
+  ];
+  const volume = change.map((row) => row.map(() => 10.0));
+  const flags = change.map((row) => row.map(() => false));
+
+  const ad = new wickra.AdvanceDecline();
+  // Cumulative line: +2 -> 0 -> 0.
+  assert.equal(ad.update(change[0], volume[0], flags[0], flags[0]), 2.0);
+  assert.equal(ad.update(change[1], volume[1], flags[1], flags[1]), 0.0);
+  assert.equal(ad.update(change[2], volume[2], flags[2], flags[2]), 0.0);
+
+  // batch matches streaming.
+  const batch = new wickra.AdvanceDecline().batch(change, volume, flags, flags);
+  assert.deepEqual(Array.from(batch), [2.0, 0.0, 0.0]);
+});
+
+test('market breadth: AdvanceDecline rejects ragged universe', () => {
+  assert.throws(() =>
+    new wickra.AdvanceDecline().update(
+      [1.0, -1.0],
+      [10.0],
+      [false, false],
+      [false, false],
+    ),
+  );
+});
+
+test('market breadth: 14 indicators reference values + batch parity', () => {
+  const flags4 = [false, false, false, false];
+
+  // Advance/Decline Ratio: 3/1 = 3 ; 0 advancers -> 0.
+  const adr = new wickra.AdvanceDeclineRatio();
+  assert.equal(adr.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4), 3.0);
+  assert.equal(adr.update([-1, -1, -1, -1], [10, 10, 10, 10], flags4, flags4), 0.0);
+  assert.deepEqual(
+    Array.from(
+      new wickra.AdvanceDeclineRatio().batch(
+        [[1, 1, 1, -1], [-1, -1, -1, -1]],
+        [[10, 10, 10, 10], [10, 10, 10, 10]],
+        [flags4, flags4],
+        [flags4, flags4],
+      ),
+    ),
+    [3.0, 0.0],
+  );
+
+  // AD Volume Line: cumulative net advancing volume.
+  const adv = new wickra.AdVolumeLine();
+  assert.equal(adv.update([1, -1], [150, 50], [false, false], [false, false]), 100.0);
+  assert.equal(adv.update([1, -1], [60, 60], [false, false], [false, false]), 100.0);
+
+  // McClellan Oscillator + Summation: seed 0, then -50.
+  const osc = new wickra.McClellanOscillator();
+  assert.ok(Math.abs(osc.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4)) < 1e-9);
+  assert.ok(Math.abs(osc.update([-1, -1, -1, 1], [10, 10, 10, 10], flags4, flags4) - -50.0) < 1e-9);
+  const msi = new wickra.McClellanSummationIndex();
+  assert.ok(Math.abs(msi.update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4)) < 1e-9);
+  assert.ok(Math.abs(msi.update([-1, -1, -1, 1], [10, 10, 10, 10], flags4, flags4) - -50.0) < 1e-9);
+
+  // TRIN: balanced breadth -> 1.
+  assert.ok(
+    Math.abs(new wickra.Trin().update([1, 1, 1, -1], [50, 50, 50, 50], flags4, flags4) - 1.0) < 1e-9,
+  );
+
+  // Breadth Thrust(2): warmup null, then SMA(2) of [0.8, 0.6] = 0.7.
+  const bt = new wickra.BreadthThrust(2);
+  const up10 = Array(10).fill(false);
+  assert.equal(bt.update([...Array(8).fill(1), -1, -1], Array(10).fill(10), up10, up10), null);
+  assert.ok(
+    Math.abs(bt.update([...Array(6).fill(1), -1, -1, -1, -1], Array(10).fill(10), up10, up10) - 0.7) < 1e-9,
+  );
+
+  // New Highs - New Lows: 2 - 1 = 1.
+  assert.equal(
+    new wickra.NewHighsNewLows().update([1, 1, -1], [10, 10, 10], [true, true, false], [false, false, true]),
+    1.0,
+  );
+
+  // High-Low Index(2): warmup null, then SMA(2) of [80, 60] = 70.
+  const hli = new wickra.HighLowIndex(2);
+  assert.equal(
+    hli.update(Array(10).fill(1), Array(10).fill(10), [...Array(8).fill(true), false, false], [...Array(8).fill(false), true, true]),
+    null,
+  );
+  assert.ok(
+    Math.abs(
+      hli.update(Array(10).fill(1), Array(10).fill(10), [...Array(6).fill(true), false, false, false, false], [...Array(6).fill(false), true, true, true, true]) - 70.0,
+    ) < 1e-9,
+  );
+
+  // Percent Above MA: 3/4 -> 75 (5-array update with aboveMa).
+  assert.equal(
+    new wickra.PercentAboveMa().update([1, 1, 1, -1], [10, 10, 10, 10], flags4, flags4, [true, true, true, false]),
+    75.0,
+  );
+
+  // Up/Down Volume Ratio: 150/50 = 3.
+  assert.equal(
+    new wickra.UpDownVolumeRatio().update([1, -1], [150, 50], [false, false], [false, false]),
+    3.0,
+  );
+
+  // Bullish Percent Index: 2/4 -> 50 (5-array update with onBuySignal).
+  assert.equal(
+    new wickra.BullishPercentIndex().update([1, 1, -1, -1], [10, 10, 10, 10], flags4, flags4, [true, true, false, false]),
+    50.0,
+  );
+
+  // Cumulative Volume Index: (100/200) -> 0.5.
+  assert.ok(
+    Math.abs(new wickra.CumulativeVolumeIndex().update([1, -1], [150, 50], [false, false], [false, false]) - 0.5) < 1e-9,
+  );
+
+  // Absolute Breadth Index: |2 - 3| = 1.
+  assert.equal(
+    new wickra.AbsoluteBreadthIndex().update([1, 1, -1, -1, -1], Array(5).fill(10), Array(5).fill(false), Array(5).fill(false)),
+    1.0,
+  );
+
+  // TICK Index: 2 - 3 = -1.
+  assert.equal(
+    new wickra.TickIndex().update([1, 1, -1, -1, -1], Array(5).fill(10), Array(5).fill(false), Array(5).fill(false)),
+    -1.0,
+  );
+});
+
+test('market breadth: rejects ragged universe', () => {
+  assert.throws(() => new wickra.Trin().update([1, -1], [10], [false, false], [false, false]));
+  assert.throws(() =>
+    new wickra.PercentAboveMa().update([1, -1], [10, 10], [false, false], [false, false], [true]),
+  );
+});
+
 test('OI / flow / liquidation indicators reference values', () => {
   // OI +10% while price flat -> divergence +0.1.
   const div = new wickra.OIPriceDivergence(1);

bindings/node/__tests__/seasonality.test.js

@@ -0,0 +1,96 @@
+// Streaming-vs-batch equivalence and reference values for the Seasonality &
+// Session family. These indicators consume the full candle (open, high, low,
+// close, volume, timestamp), so they have a dedicated suite.
+
+const test = require('node:test');
+const assert = require('node:assert/strict');
+const wickra = require('..');
+
+const HOUR = 3_600_000;
+const N = 240;
+const close = Array.from({ length: N }, (_, i) => 100 + Math.sin(i * 0.3) * 5 + Math.cos(i * 0.1) * 3);
+const open = close.map((c, i) => c + Math.sin(i * 0.5) * 0.5);
+const high = close.map((c, i) => Math.max(open[i], c) + 1);
+const low = close.map((c, i) => Math.min(open[i], c) - 1);
+const volume = Array.from({ length: N }, (_, i) => 1000 + (i % 24) * 50);
+const ts = Array.from({ length: N }, (_, i) => i * HOUR);
+
+function eq(a, b) {
+  if (Number.isNaN(a)) return Number.isNaN(b);
+  return Math.abs(a - b) < 1e-9;
+}
+
+function streamScalar(ind, i) {
+  const v = ind.update(open[i], high[i], low[i], close[i], volume[i], ts[i]);
+  return v === null || v === undefined ? NaN : v;
+}
+
+function checkScalar(name, make) {
+  test(`${name} streaming equals batch`, () => {
+    const a = make();
+    const b = make();
+    const batch = b.batch(open, high, low, close, volume, ts);
+    for (let i = 0; i < N; i += 1) {
+      assert.ok(eq(streamScalar(a, i), batch[i]), `${name} row ${i}`);
+    }
+  });
+}
+
+function checkMatrix(name, make, k, pick) {
+  test(`${name} streaming equals batch`, () => {
+    const a = make();
+    const b = make();
+    const batch = b.batch(open, high, low, close, volume, ts);
+    for (let i = 0; i < N; i += 1) {
+      const out = a.update(open[i], high[i], low[i], close[i], volume[i], ts[i]);
+      for (let j = 0; j < k; j += 1) {
+        const s = out === null || out === undefined ? NaN : pick(out, j);
+        assert.ok(eq(s, batch[i * k + j]), `${name} row ${i} col ${j}`);
+      }
+    }
+  });
+}
+
+checkScalar('SessionVwap', () => new wickra.SessionVwap(0));
+checkScalar('OvernightGap', () => new wickra.OvernightGap(0));
+checkScalar('SeasonalZScore', () => new wickra.SeasonalZScore(0));
+checkScalar('AverageDailyRange', () => new wickra.AverageDailyRange(3, 0));
+checkScalar('TurnOfMonth', () => new wickra.TurnOfMonth(3, 1, 0));
+
+checkMatrix('SessionHighLow', () => new wickra.SessionHighLow(0), 2, (o, j) => (j === 0 ? o.high : o.low));
+checkMatrix('SessionRange', () => new wickra.SessionRange(0), 3, (o, j) => [o.asia, o.eu, o.us][j]);
+checkMatrix(
+  'OvernightIntradayReturn',
+  () => new wickra.OvernightIntradayReturn(0),
+  2,
+  (o, j) => (j === 0 ? o.overnight : o.intraday),
+);
+checkMatrix('TimeOfDayReturnProfile', () => new wickra.TimeOfDayReturnProfile(24, 0), 24, (o, j) => o[j]);
+checkMatrix('IntradayVolatilityProfile', () => new wickra.IntradayVolatilityProfile(12, 0), 12, (o, j) => o[j]);
+checkMatrix('VolumeByTimeProfile', () => new wickra.VolumeByTimeProfile(24, 0), 24, (o, j) => o[j]);
+checkMatrix('DayOfWeekProfile', () => new wickra.DayOfWeekProfile(0), 7, (o, j) => o[j]);
+
+test('SessionVwap reference value', () => {
+  const vwap = new wickra.SessionVwap(0);
+  assert.ok(eq(vwap.update(100, 100, 100, 100, 10, 0), 100));
+  assert.ok(eq(vwap.update(110, 110, 110, 110, 30, HOUR), 107.5));
+  assert.ok(eq(vwap.update(200, 200, 200, 200, 5, 24 * HOUR), 200));
+});
+
+test('OvernightGap reference value', () => {
+  const gap = new wickra.OvernightGap(0);
+  assert.equal(gap.update(99, 101, 98, 100, 1, 0), null);
+  assert.ok(eq(gap.update(105, 106, 104, 105.5, 1, 24 * HOUR), 0.05));
+});
+
+test('SessionHighLow reference object', () => {
+  const shl = new wickra.SessionHighLow(0);
+  shl.update(100, 105, 99, 101, 1, 0);
+  const out = shl.update(101, 108, 100, 107, 1, HOUR);
+  assert.ok(eq(out.high, 108));
+  assert.ok(eq(out.low, 99));
+});
+
+test('AverageDailyRange rejects zero period', () => {
+  assert.throws(() => new wickra.AverageDailyRange(0, 0));
+});

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-darwin-arm64",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-arm64.node",
   "files": [
     "wickra.darwin-arm64.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-darwin-x64",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-x64.node",
   "files": [
     "wickra.darwin-x64.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-linux-arm64-gnu",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-arm64-gnu.node",
   "files": [
     "wickra.linux-arm64-gnu.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-linux-x64-gnu",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-x64-gnu.node",
   "files": [
     "wickra.linux-x64-gnu.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-win32-arm64-msvc",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-arm64-msvc.node",
   "files": [
     "wickra.win32-arm64-msvc.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

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

@@ -1,12 +1,12 @@
 {
   "name": "wickra-win32-x64-msvc",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-x64-msvc.node",
   "files": [
     "wickra.win32-x64-msvc.node"
   ],
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "engines": {
     "node": ">= 18"
   },

bindings/node/package-lock.json

@@ -1,13 +1,13 @@
 {
   "name": "wickra",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "wickra",
-      "version": "0.4.5",
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "version": "0.6.1",
+      "license": "MIT OR Apache-2.0",
       "devDependencies": {
         "@napi-rs/cli": "^2.18.0"
       },
@@ -15,12 +15,12 @@
         "node": ">= 18"
       },
       "optionalDependencies": {
-        "wickra-darwin-arm64": "0.4.5",
-        "wickra-darwin-x64": "0.4.5",
-        "wickra-linux-arm64-gnu": "0.4.5",
-        "wickra-linux-x64-gnu": "0.4.5",
-        "wickra-win32-arm64-msvc": "0.4.5",
-        "wickra-win32-x64-msvc": "0.4.5"
+        "wickra-darwin-arm64": "0.6.1",
+        "wickra-darwin-x64": "0.6.1",
+        "wickra-linux-arm64-gnu": "0.6.1",
+        "wickra-linux-x64-gnu": "0.6.1",
+        "wickra-win32-arm64-msvc": "0.6.1",
+        "wickra-win32-x64-msvc": "0.6.1"
       }
     },
     "node_modules/@napi-rs/cli": {
@@ -41,13 +41,13 @@
       }
     },
     "node_modules/wickra-darwin-arm64": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.6.1.tgz",
       "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
       "cpu": [
         "arm64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "darwin"
@@ -57,13 +57,13 @@
       }
     },
     "node_modules/wickra-darwin-x64": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.6.1.tgz",
       "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
       "cpu": [
         "x64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "darwin"
@@ -73,13 +73,13 @@
       }
     },
     "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.6.1.tgz",
       "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
       "cpu": [
         "arm64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "linux"
@@ -89,13 +89,13 @@
       }
     },
     "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.6.1.tgz",
       "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
       "cpu": [
         "x64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "linux"
@@ -105,13 +105,13 @@
       }
     },
     "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.6.1.tgz",
       "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
       "cpu": [
         "arm64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "win32"
@@ -121,13 +121,13 @@
       }
     },
     "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.4.5",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.4.5.tgz",
+      "version": "0.6.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.6.1.tgz",
       "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
       "cpu": [
         "x64"
       ],
-      "license": "PolyForm-Noncommercial-1.0.0",
+      "license": "MIT OR Apache-2.0",
       "optional": true,
       "os": [
         "win32"

bindings/node/package.json

@@ -1,11 +1,11 @@
 {
   "name": "wickra",
-  "version": "0.4.5",
+  "version": "0.6.1",
   "description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
   "author": "kingchenc <support@wickra.org>",
   "main": "index.js",
   "types": "index.d.ts",
-  "license": "LicenseRef-Wickra-Noncommercial-1.0.0",
+  "license": "MIT OR Apache-2.0",
   "keywords": [
     "trading",
     "indicators",
@@ -47,12 +47,12 @@
     "node": ">= 18"
   },
   "optionalDependencies": {
-    "wickra-linux-x64-gnu": "0.4.5",
-    "wickra-linux-arm64-gnu": "0.4.5",
-    "wickra-darwin-x64": "0.4.5",
-    "wickra-darwin-arm64": "0.4.5",
-    "wickra-win32-x64-msvc": "0.4.5",
-    "wickra-win32-arm64-msvc": "0.4.5"
+    "wickra-linux-x64-gnu": "0.6.1",
+    "wickra-linux-arm64-gnu": "0.6.1",
+    "wickra-darwin-x64": "0.6.1",
+    "wickra-darwin-arm64": "0.6.1",
+    "wickra-win32-x64-msvc": "0.6.1",
+    "wickra-win32-arm64-msvc": "0.6.1"
   },
   "scripts": {
     "build": "napi build --platform --release",

bindings/python/Cargo.toml

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

bindings/python/README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
 
 **Streaming-first technical indicators for Python. `pip install wickra` — no
 system dependencies, no C build tooling.**
@@ -66,7 +66,5 @@ risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/python/benchmarks/compare_libraries.py

@@ -49,6 +49,7 @@ TALIB = _try_import("talib")
 PANDAS_TA = _try_import("pandas_ta")
 TALIPP = _try_import("talipp.indicators") or _try_import("talipp")
 FINTA = _try_import("finta")
+TULIPY = _try_import("tulipy")
 PD = _try_import("pandas")
 import wickra as WICKRA  # noqa: E402  -- the library under test must be importable
 
@@ -275,6 +276,34 @@ def talipp_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
     return lambda: BB(period=20, std_dev_mult=2.0, input_values=list(prices))
 
 
+# tulipy wraps the C "Tulip Indicators" library; it takes contiguous float64
+# arrays and indicator options as positional arguments.
+
+
+def tulipy_sma_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.sma(prices, 20))
+
+
+def tulipy_ema_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.ema(prices, 20))
+
+
+def tulipy_rsi_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.rsi(prices, 14))
+
+
+def tulipy_macd_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.macd(prices, 12, 26, 9))
+
+
+def tulipy_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.bbands(prices, 20, 2.0))
+
+
+def tulipy_atr_batch(high: np.ndarray, low: np.ndarray, close: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.atr(high, low, close, 14))
+
+
 # --------------------------------------------------------------------------- #
 # Streaming scenario: per-tick latency
 # --------------------------------------------------------------------------- #
@@ -329,6 +358,105 @@ def talipp_rsi_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callabl
     return run
 
 
+# Scalar streaming peers: Wickra and talipp both update incrementally in O(1),
+# so this is the like-for-like per-tick comparison (batch-only libs are covered
+# by the batch tables and the recompute contrast on RSI above).
+
+
+def wickra_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        sma = WICKRA.SMA(20)
+        sma.batch(seed)
+        for p in live:
+            sma.update(float(p))
+
+    return run
+
+
+def talipp_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import SMA  # type: ignore
+
+    def run() -> None:
+        sma = SMA(period=20, input_values=list(seed))
+        for p in live:
+            sma.add(float(p))
+
+    return run
+
+
+def wickra_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        ema = WICKRA.EMA(20)
+        ema.batch(seed)
+        for p in live:
+            ema.update(float(p))
+
+    return run
+
+
+def talipp_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import EMA  # type: ignore
+
+    def run() -> None:
+        ema = EMA(period=20, input_values=list(seed))
+        for p in live:
+            ema.add(float(p))
+
+    return run
+
+
+def wickra_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        macd = WICKRA.MACD()
+        macd.batch(seed)
+        for p in live:
+            macd.update(float(p))
+
+    return run
+
+
+def talipp_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import MACD  # type: ignore
+
+    def run() -> None:
+        macd = MACD(
+            fast_period=12, slow_period=26, signal_period=9, input_values=list(seed)
+        )
+        for p in live:
+            macd.add(float(p))
+
+    return run
+
+
+def wickra_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        bb = WICKRA.BollingerBands(20, 2.0)
+        bb.batch(seed)
+        for p in live:
+            bb.update(float(p))
+
+    return run
+
+
+def talipp_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import BB  # type: ignore
+
+    def run() -> None:
+        bb = BB(period=20, std_dev_mult=2.0, input_values=list(seed))
+        for p in live:
+            bb.add(float(p))
+
+    return run
+
+
 # --------------------------------------------------------------------------- #
 # Runner
 # --------------------------------------------------------------------------- #
@@ -339,6 +467,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_sma_batch),
         ("TA-Lib", talib_sma_batch),
         ("pandas-ta", pandas_ta_sma_batch),
+        ("tulipy", tulipy_sma_batch),
         ("finta", finta_sma_batch),
         ("talipp", talipp_sma_batch),
     ]),
@@ -346,6 +475,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_ema_batch),
         ("TA-Lib", talib_ema_batch),
         ("pandas-ta", pandas_ta_ema_batch),
+        ("tulipy", tulipy_ema_batch),
         ("finta", finta_ema_batch),
         ("talipp", talipp_ema_batch),
     ]),
@@ -353,6 +483,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_rsi_batch),
         ("TA-Lib", talib_rsi_batch),
         ("pandas-ta", pandas_ta_rsi_batch),
+        ("tulipy", tulipy_rsi_batch),
         ("finta", finta_rsi_batch),
         ("talipp", talipp_rsi_batch),
     ]),
@@ -360,6 +491,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_macd_batch),
         ("TA-Lib", talib_macd_batch),
         ("pandas-ta", pandas_ta_macd_batch),
+        ("tulipy", tulipy_macd_batch),
         ("finta", finta_macd_batch),
         ("talipp", talipp_macd_batch),
     ]),
@@ -367,6 +499,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_bollinger_batch),
         ("TA-Lib", talib_bollinger_batch),
         ("pandas-ta", pandas_ta_bollinger_batch),
+        ("tulipy", tulipy_bollinger_batch),
         ("finta", finta_bollinger_batch),
         ("talipp", talipp_bollinger_batch),
     ]),
@@ -376,18 +509,35 @@ OHLC_INDICATORS = [
     ("ATR(14)", [
         ("Wickra", wickra_atr_batch),
         ("TA-Lib", talib_atr_batch),
+        ("tulipy", tulipy_atr_batch),
         ("finta", finta_atr_batch),
         ("talipp", talipp_atr_batch),
     ]),
 ]
 
 STREAMING_INDICATORS = [
+    ("SMA(20)", [
+        ("Wickra", wickra_sma_streaming),
+        ("talipp", talipp_sma_streaming),
+    ]),
+    ("EMA(20)", [
+        ("Wickra", wickra_ema_streaming),
+        ("talipp", talipp_ema_streaming),
+    ]),
     ("RSI(14)", [
         ("Wickra", wickra_rsi_streaming),
         ("TA-Lib", talib_rsi_streaming),
         ("pandas-ta", pandas_ta_rsi_streaming),
         ("talipp", talipp_rsi_streaming),
     ]),
+    ("MACD(12, 26, 9)", [
+        ("Wickra", wickra_macd_streaming),
+        ("talipp", talipp_macd_streaming),
+    ]),
+    ("Bollinger(20, 2.0)", [
+        ("Wickra", wickra_bollinger_streaming),
+        ("talipp", talipp_bollinger_streaming),
+    ]),
 ]
 
 
@@ -501,6 +651,7 @@ def main() -> None:
     available = []
     if TALIB is not None: available.append("TA-Lib")
     if PANDAS_TA is not None: available.append("pandas-ta")
+    if TULIPY is not None: available.append("tulipy")
     if FINTA is not None: available.append("finta")
     if TALIPP is not None: available.append("talipp")
     print(f"Wickra benchmark suite — wickra=v{WICKRA.__version__}")

bindings/python/pyproject.toml

@@ -4,17 +4,16 @@ build-backend = "maturin"
 
 [project]
 name = "wickra"
-version = "0.4.5"
+version = "0.6.1"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
-license = { text = "PolyForm-Noncommercial-1.0.0 with additional personal-account permissions; see LICENSE" }
+license = "MIT OR Apache-2.0"
 authors = [{ name = "kingchenc", email = "support@wickra.org" }]
 requires-python = ">=3.9"
 keywords = ["finance", "trading", "indicators", "technical-analysis", "ta-lib"]
 classifiers = [
     "Development Status :: 4 - Beta",
     "Intended Audience :: Financial and Insurance Industry",
-    "License :: Free for non-commercial use",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
     "Programming Language :: Python :: 3.9",
@@ -40,6 +39,7 @@ bench = [
     "pytest-benchmark>=4",
     "TA-Lib; platform_system != 'Windows'",
     "pandas-ta>=0.3.14b",
+    "tulipy>=0.4; platform_system != 'Windows'",
     "talipp>=2",
     "finta>=1.3",
     "pandas>=2",

bindings/python/python/wickra/__init__.py

@@ -25,6 +25,65 @@ from __future__ import annotations
 
 from ._wickra import (
     __version__,
+    ProjectionOscillator,
+    VolatilityCone,
+    VolatilityRatio,
+    BipowerVariation,
+    VolatilityOfVolatility,
+    Garch11,
+    EwmaVolatility,
+    PpoHistogram,
+    MacdHistogram,
+    TsfOscillator,
+    Qstick,
+    GatorOscillator,
+    KasePermissionStochastic,
+    WAVE_PM,
+    POLARIZED_FRACTAL_EFFICIENCY,
+    TREND_STRENGTH_INDEX,
+    TTM_TREND,
+    QQE,
+    IMI,
+    ElderRay,
+    DerivativeOscillator,
+    RMI,
+    StochasticCCI,
+    DynamicMomentumIndex,
+    RSX,
+    FisherRSI,
+    DisparityIndex,
+    HoltWinters,
+    GD,
+    AdaptiveLaguerre,
+    MedianMA,
+    EHMA,
+    GMA,
+    SWMA,
+    Expectancy,
+    WinRate,
+    RegimeLabel,
+    JumpIndicator,
+    TrendLabel,
+    HighLowRange,
+    WickRatio,
+    BodySizePct,
+    CloseVsOpen,
+    RollingQuantile,
+    RollingPercentileRank,
+    RollingIqr,
+    RealizedVolatility,
+    LogReturn,
+    TSF,
+    LINEARREG_INTERCEPT,
+    ROCR100,
+    ROCR,
+    ROCP,
+    AVGPRICE,
+    MIDPOINT,
+    MIDPRICE,
+    DX,
+    MINUS_DI,
+    PLUS_DI,
     # Trend
     SMA,
     EMA,
@@ -49,12 +108,16 @@ from ._wickra import (
     RSI,
     AnchoredRSI,
     MACD,
+    MACDFIX,
+    MACDEXT,
     Stochastic,
     CCI,
     ROC,
     WilliamsR,
     ADX,
     ADXR,
+    PLUS_DM,
+    MINUS_DM,
     MFI,
     TRIX,
     AwesomeOscillator,
@@ -98,6 +161,7 @@ from ._wickra import (
     Keltner,
     Donchian,
     PSAR,
+    SAREXT,
     NATR,
     StdDev,
     UlcerIndex,
@@ -143,6 +207,16 @@ from ._wickra import (
     MarketFacilitationIndex,
     EaseOfMovement,
     # Statistics
+    SpreadBollingerBands,
+    KalmanHedgeRatio,
+    GrangerCausality,
+    VarianceRatio,
+    BetaNeutralSpread,
+    DistanceSsd,
+    SpreadHurst,
+    OuHalfLife,
+    RollingCovariance,
+    RollingCorrelation,
     TypicalPrice,
     MedianPrice,
     WeightedClose,
@@ -163,6 +237,7 @@ from ._wickra import (
     PearsonCorrelation,
     Beta,
     PairwiseBeta,
+    SpreadAr1Coefficient,
     PairSpreadZScore,
     LeadLagCrossCorrelation,
     Cointegration,
@@ -181,11 +256,18 @@ from ._wickra import (
     EhlersStochastic,
     EmpiricalModeDecomposition,
     HilbertDominantCycle,
+    HT_DCPHASE,
+    HT_PHASOR,
+    HT_TRENDMODE,
     AdaptiveCycle,
     SineWave,
     MAMA,
     FAMA,
     # Bands & Channels
+    ProjectionBands,
+    MedianChannel,
+    BomarBands,
+    QuartileBands,
     MaEnvelope,
     AccelerationBands,
     StarcBands,
@@ -292,7 +374,37 @@ from ._wickra import (
     TasukiGap,
     UniqueThreeRiver,
     ConcealingBabySwallow,
+    # Chart patterns
+    CupAndHandle,
+    RectangleRange,
+    FlagPennant,
+    Wedge,
+    Triangle,
+    HeadAndShoulders,
+    TripleTopBottom,
+    DoubleTopBottom,
+    # Harmonic patterns
+    ThreeDrives,
+    Cypher,
+    Shark,
+    Crab,
+    Bat,
+    Butterfly,
+    Gartley,
+    Abcd,
+    # Fibonacci
+    FibTimeZones,
+    FibChannel,
+    FibArcs,
+    FibFan,
+    FibConfluence,
+    GoldenPocket,
+    AutoFib,
+    FibProjection,
+    FibExtension,
+    FibRetracement,
     # Microstructure: order book
+    OrderFlowImbalance,
     OrderBookImbalanceTop1,
     OrderBookImbalanceTopN,
     OrderBookImbalanceFull,
@@ -300,6 +412,9 @@ from ._wickra import (
     QuotedSpread,
     DepthSlope,
     # Microstructure: trade flow
+    RollMeasure,
+    AmihudIlliquidity,
+    Vpin,
     SignedVolume,
     CumulativeVolumeDelta,
     TradeImbalance,
@@ -322,6 +437,22 @@ from ._wickra import (
     LiquidationFeatures,
     TermStructureBasis,
     CalendarSpread,
+    # Market Breadth
+    TickIndex,
+    AbsoluteBreadthIndex,
+    CumulativeVolumeIndex,
+    BullishPercentIndex,
+    UpDownVolumeRatio,
+    PercentAboveMa,
+    HighLowIndex,
+    NewHighsNewLows,
+    BreadthThrust,
+    Trin,
+    McClellanSummationIndex,
+    McClellanOscillator,
+    AdVolumeLine,
+    AdvanceDeclineRatio,
+    AdvanceDecline,
     # Risk / Performance
     SharpeRatio,
     SortinoRatio,
@@ -340,9 +471,81 @@ from ._wickra import (
     TreynorRatio,
     InformationRatio,
     Alpha,
+    # Seasonality & Session
+    SessionVwap,
+    SessionHighLow,
+    SessionRange,
+    AverageDailyRange,
+    OvernightGap,
+    OvernightIntradayReturn,
+    TurnOfMonth,
+    SeasonalZScore,
+    TimeOfDayReturnProfile,
+    DayOfWeekProfile,
+    IntradayVolatilityProfile,
+    VolumeByTimeProfile,
 )
 
 __all__ = [
+    "ProjectionOscillator",
+    "VolatilityCone",
+    "VolatilityRatio",
+    "BipowerVariation",
+    "VolatilityOfVolatility",
+    "Garch11",
+    "EwmaVolatility",
+    "PpoHistogram",
+    "MacdHistogram",
+    "TsfOscillator",
+    "Qstick",
+    "GatorOscillator",
+    "KasePermissionStochastic",
+    "WAVE_PM",
+    "POLARIZED_FRACTAL_EFFICIENCY",
+    "TREND_STRENGTH_INDEX",
+    "TTM_TREND",
+    "QQE",
+    "IMI",
+    "ElderRay",
+    "DerivativeOscillator",
+    "RMI",
+    "StochasticCCI",
+    "DynamicMomentumIndex",
+    "RSX",
+    "FisherRSI",
+    "DisparityIndex",
+    "HoltWinters",
+    "GD",
+    "AdaptiveLaguerre",
+    "MedianMA",
+    "EHMA",
+    "GMA",
+    "SWMA",
+    "Expectancy",
+    "WinRate",
+    "RegimeLabel",
+    "JumpIndicator",
+    "TrendLabel",
+    "HighLowRange",
+    "WickRatio",
+    "BodySizePct",
+    "CloseVsOpen",
+    "RollingQuantile",
+    "RollingPercentileRank",
+    "RollingIqr",
+    "RealizedVolatility",
+    "LogReturn",
+    "TSF",
+    "LINEARREG_INTERCEPT",
+    "ROCR100",
+    "ROCR",
+    "ROCP",
+    "AVGPRICE",
+    "MIDPOINT",
+    "MIDPRICE",
+    "DX",
+    "MINUS_DI",
+    "PLUS_DI",
     "__version__",
     # Trend
     "SMA",
@@ -368,12 +571,16 @@ __all__ = [
     "RSI",
     "AnchoredRSI",
     "MACD",
+    "MACDFIX",
+    "MACDEXT",
     "Stochastic",
     "CCI",
     "ROC",
     "WilliamsR",
     "ADX",
     "ADXR",
+    "PLUS_DM",
+    "MINUS_DM",
     "MFI",
     "TRIX",
     "AwesomeOscillator",
@@ -417,6 +624,7 @@ __all__ = [
     "Keltner",
     "Donchian",
     "PSAR",
+    "SAREXT",
     "NATR",
     "StdDev",
     "UlcerIndex",
@@ -462,6 +670,16 @@ __all__ = [
     "MarketFacilitationIndex",
     "EaseOfMovement",
     # Statistics
+    "SpreadBollingerBands",
+    "KalmanHedgeRatio",
+    "GrangerCausality",
+    "VarianceRatio",
+    "BetaNeutralSpread",
+    "DistanceSsd",
+    "SpreadHurst",
+    "OuHalfLife",
+    "RollingCovariance",
+    "RollingCorrelation",
     "TypicalPrice",
     "MedianPrice",
     "WeightedClose",
@@ -482,6 +700,7 @@ __all__ = [
     "PearsonCorrelation",
     "Beta",
     "PairwiseBeta",
+    "SpreadAr1Coefficient",
     "PairSpreadZScore",
     "LeadLagCrossCorrelation",
     "Cointegration",
@@ -500,11 +719,18 @@ __all__ = [
     "EhlersStochastic",
     "EmpiricalModeDecomposition",
     "HilbertDominantCycle",
+    "HT_DCPHASE",
+    "HT_PHASOR",
+    "HT_TRENDMODE",
     "AdaptiveCycle",
     "SineWave",
     "MAMA",
     "FAMA",
     # Bands & Channels
+    "ProjectionBands",
+    "MedianChannel",
+    "BomarBands",
+    "QuartileBands",
     "MaEnvelope",
     "AccelerationBands",
     "StarcBands",
@@ -611,7 +837,37 @@ __all__ = [
     "TasukiGap",
     "UniqueThreeRiver",
     "ConcealingBabySwallow",
+    # Chart patterns
+    "CupAndHandle",
+    "RectangleRange",
+    "FlagPennant",
+    "Wedge",
+    "Triangle",
+    "HeadAndShoulders",
+    "TripleTopBottom",
+    "DoubleTopBottom",
+    # Harmonic patterns
+    "ThreeDrives",
+    "Cypher",
+    "Shark",
+    "Crab",
+    "Bat",
+    "Butterfly",
+    "Gartley",
+    "Abcd",
+    # Fibonacci
+    "FibTimeZones",
+    "FibChannel",
+    "FibArcs",
+    "FibFan",
+    "FibConfluence",
+    "GoldenPocket",
+    "AutoFib",
+    "FibProjection",
+    "FibExtension",
+    "FibRetracement",
     # Microstructure: order book
+    "OrderFlowImbalance",
     "OrderBookImbalanceTop1",
     "OrderBookImbalanceTopN",
     "OrderBookImbalanceFull",
@@ -619,6 +875,9 @@ __all__ = [
     "QuotedSpread",
     "DepthSlope",
     # Microstructure: trade flow
+    "RollMeasure",
+    "AmihudIlliquidity",
+    "Vpin",
     "SignedVolume",
     "CumulativeVolumeDelta",
     "TradeImbalance",
@@ -641,6 +900,22 @@ __all__ = [
     "LiquidationFeatures",
     "TermStructureBasis",
     "CalendarSpread",
+    # Market Breadth
+    "TickIndex",
+    "AbsoluteBreadthIndex",
+    "CumulativeVolumeIndex",
+    "BullishPercentIndex",
+    "UpDownVolumeRatio",
+    "PercentAboveMa",
+    "HighLowIndex",
+    "NewHighsNewLows",
+    "BreadthThrust",
+    "Trin",
+    "McClellanSummationIndex",
+    "McClellanOscillator",
+    "AdVolumeLine",
+    "AdvanceDeclineRatio",
+    "AdvanceDecline",
     # Risk / Performance
     "SharpeRatio",
     "SortinoRatio",
@@ -659,4 +934,17 @@ __all__ = [
     "TreynorRatio",
     "InformationRatio",
     "Alpha",
+    # Seasonality & Session
+    "SessionVwap",
+    "SessionHighLow",
+    "SessionRange",
+    "AverageDailyRange",
+    "OvernightGap",
+    "OvernightIntradayReturn",
+    "TurnOfMonth",
+    "SeasonalZScore",
+    "TimeOfDayReturnProfile",
+    "DayOfWeekProfile",
+    "IntradayVolatilityProfile",
+    "VolumeByTimeProfile",
 ]

bindings/python/tests/test_seasonality.py

@@ -0,0 +1,132 @@
+"""Streaming-vs-batch equivalence and reference values for the Seasonality &
+Session family.
+
+These indicators read the full candle (including ``timestamp``), so they have a
+dedicated test rather than joining the timestamp-less parametrize harness in
+``test_new_indicators.py``.
+"""
+
+import numpy as np
+import pytest
+
+import wickra as ta
+
+HOUR_MS = 3_600_000
+
+
+@pytest.fixture(scope="module")
+def candle_columns():
+    """240 hourly candles (10 days) with valid OHLCV and epoch-ms timestamps."""
+    n = 240
+    t = np.arange(n, dtype=np.float64)
+    close = 100.0 + np.sin(t * 0.3) * 5.0 + np.cos(t * 0.1) * 3.0
+    open_ = close + np.sin(t * 0.5) * 0.5
+    high = np.maximum(open_, close) + 1.0
+    low = np.minimum(open_, close) - 1.0
+    volume = 1000.0 + (t % 24) * 50.0
+    timestamp = (np.arange(n, dtype=np.int64)) * HOUR_MS
+    return open_, high, low, close, volume, timestamp
+
+
+def _candles(cols):
+    open_, high, low, close, volume, timestamp = cols
+    return [
+        (open_[i], high[i], low[i], close[i], volume[i], int(timestamp[i]))
+        for i in range(len(close))
+    ]
+
+
+def _check_scalar(make, cols):
+    candles = _candles(cols)
+    a, b = make(), make()
+    stream = np.array(
+        [np.nan if (v := a.update(c)) is None else v for c in candles],
+        dtype=np.float64,
+    )
+    batch = np.asarray(b.batch(*cols))
+    np.testing.assert_allclose(stream, batch, equal_nan=True, rtol=1e-9, atol=1e-9)
+
+
+def _check_matrix(make, k, cols):
+    candles = _candles(cols)
+    a, b = make(), make()
+    rows = []
+    for c in candles:
+        out = a.update(c)
+        rows.append(np.full(k, np.nan) if out is None else np.asarray(out, dtype=float))
+    stream = np.vstack(rows)
+    batch = np.asarray(b.batch(*cols))
+    assert batch.shape == (len(candles), k)
+    np.testing.assert_allclose(stream, batch, equal_nan=True, rtol=1e-9, atol=1e-9)
+
+
+SCALAR = [
+    lambda: ta.SessionVwap(0),
+    lambda: ta.OvernightGap(0),
+    lambda: ta.SeasonalZScore(0),
+    lambda: ta.AverageDailyRange(3, 0),
+    lambda: ta.TurnOfMonth(3, 1, 0),
+]
+
+MATRIX = [
+    (lambda: ta.SessionHighLow(0), 2),
+    (lambda: ta.SessionRange(0), 3),
+    (lambda: ta.OvernightIntradayReturn(0), 2),
+    (lambda: ta.TimeOfDayReturnProfile(24, 0), 24),
+    (lambda: ta.IntradayVolatilityProfile(12, 0), 12),
+    (lambda: ta.VolumeByTimeProfile(24, 0), 24),
+    (lambda: ta.DayOfWeekProfile(0), 7),
+]
+
+
+@pytest.mark.parametrize("make", SCALAR)
+def test_scalar_streaming_equals_batch(make, candle_columns):
+    _check_scalar(make, candle_columns)
+
+
+@pytest.mark.parametrize("make,k", MATRIX)
+def test_matrix_streaming_equals_batch(make, k, candle_columns):
+    _check_matrix(make, k, candle_columns)
+
+
+def test_session_vwap_reference():
+    vwap = ta.SessionVwap(0)
+    # typical = close for a flat candle; volume-weighted within the day.
+    v1 = vwap.update((100.0, 100.0, 100.0, 100.0, 10.0, 0))
+    assert v1 == pytest.approx(100.0)
+    v2 = vwap.update((110.0, 110.0, 110.0, 110.0, 30.0, HOUR_MS))
+    assert v2 == pytest.approx(107.5)
+    # New day re-anchors.
+    v3 = vwap.update((200.0, 200.0, 200.0, 200.0, 5.0, 24 * HOUR_MS))
+    assert v3 == pytest.approx(200.0)
+
+
+def test_overnight_gap_reference():
+    gap = ta.OvernightGap(0)
+    assert gap.update((99.0, 101.0, 98.0, 100.0, 1.0, 0)) is None
+    g = gap.update((105.0, 106.0, 104.0, 105.5, 1.0, 24 * HOUR_MS))
+    assert g == pytest.approx(0.05)
+
+
+def test_session_high_low_reference():
+    shl = ta.SessionHighLow(0)
+    shl.update((100.0, 105.0, 99.0, 101.0, 1.0, 0))
+    out = shl.update((101.0, 108.0, 100.0, 107.0, 1.0, HOUR_MS))
+    assert out == (108.0, 99.0)
+
+
+def test_volume_by_time_profile_reference():
+    prof = ta.VolumeByTimeProfile(24, 0)
+    out = prof.update((100.0, 100.0, 100.0, 100.0, 500.0, HOUR_MS))  # 01:00 -> bucket 1
+    assert out[1] == pytest.approx(500.0)
+    assert out[0] == pytest.approx(0.0)
+
+
+def test_rejects_zero_buckets():
+    with pytest.raises(ValueError):
+        ta.TimeOfDayReturnProfile(0, 0)
+
+
+def test_average_daily_range_rejects_zero_period():
+    with pytest.raises(ValueError):
+        ta.AverageDailyRange(0, 0)

bindings/wasm/Cargo.toml

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

bindings/wasm/README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
 [![npm](https://img.shields.io/npm/v/wickra-wasm.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra-wasm)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
 
 **Streaming-first technical indicators in the browser. `npm install
 wickra-wasm` — pure WebAssembly, runs anywhere a modern JS engine does.**
@@ -66,7 +66,5 @@ risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
-research, education, non-profits, and hobby trading bots are all fine; the one
-thing not allowed is commercial sale of the software or of services built
-around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

clippy.toml

@@ -1,4 +1,4 @@
 # Proper nouns that appear in indicator documentation. They are real names,
 # not code identifiers, so `clippy::doc_markdown` must not demand backticks.
 # `..` keeps clippy's built-in default identifier list in addition to these.
-doc-valid-idents = ["LeBeau", ".."]
+doc-valid-idents = ["LeBeau", "McClellan", ".."]

crates/wickra-bench/Cargo.toml

@@ -0,0 +1,22 @@
+[package]
+name = "wickra-bench"
+version.workspace = true
+edition.workspace = true
+license.workspace = true
+publish = false
+description = "Internal cross-library benchmark harness (not published)."
+
+[lints]
+workspace = true
+
+[dev-dependencies]
+wickra = { path = "../wickra" }
+wickra-data = { path = "../wickra-data" }
+criterion = { workspace = true }
+kand = "0.2.2"
+ta = "0.5.0"
+yata = "0.7.0"
+
+[[bench]]
+name = "cross_lib"
+harness = false

crates/wickra-bench/benches/cross_lib.rs

@@ -0,0 +1,695 @@
+//! Cross-library Criterion benchmark: Wickra vs `kand` vs `ta` (ta-rs) vs `yata`.
+//!
+//! All four are pure-Rust technical-analysis crates, so this is a like-for-like
+//! Rust-vs-Rust comparison with no language-binding overhead. It feeds the exact
+//! same BTCUSDT 1-minute candle series used by `crates/wickra/benches/indicators.rs`.
+//!
+//! Two arenas, kept honest:
+//!
+//! * **Streaming** (`*/stream`): one value fed at a time. Wickra (`Indicator::update`),
+//!   ta-rs (`Next::next`) and yata (`Method::next`) carry their own state; `kand`
+//!   exposes stateless `*_inc` helpers, so the per-tick state is threaded manually
+//!   here, seeded from `kand`'s own batch output (the seed is computed outside the
+//!   timed closure). yata only appears for SMA/EMA — its RSI/MACD/Bollinger/ATR are
+//!   exposed through a heavier signal-oriented indicator API, not a raw-value method,
+//!   so they are intentionally left out rather than compared unfairly.
+//! * **Batch** (`*/batch`): the whole series at once. Only Wickra (`BatchExt::batch`)
+//!   and `kand` (TA-Lib-style fill-the-output-slice functions) have a real batch API;
+//!   ta-rs and yata are streaming-only and are deliberately absent from this arena.
+//!
+//! Run: `cargo bench -p wickra-bench`
+
+// Each indicator's benchmark group spells out every library arm explicitly, which
+// runs a few groups over the 100-line lint threshold; that verbosity is the point.
+#![allow(clippy::too_many_lines)]
+
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+use std::hint::black_box;
+use wickra::{Atr, BatchExt, BollingerBands, Candle, Ema, Indicator, MacdIndicator, Rsi, Sma};
+use wickra_data::csv::CandleReader;
+use yata::prelude::Method;
+
+const SIZES: &[usize] = &[1_000, 10_000, 50_000];
+
+const SMA_PERIOD: usize = 20;
+const EMA_PERIOD: usize = 20;
+const RSI_PERIOD: usize = 14;
+const ATR_PERIOD: usize = 14;
+const BB_PERIOD: usize = 20;
+const BB_DEV: f64 = 2.0;
+const MACD_FAST: usize = 12;
+const MACD_SLOW: usize = 26;
+const MACD_SIGNAL: usize = 9;
+
+fn load_candles() -> Vec<Candle> {
+    let path = concat!(
+        env!("CARGO_MANIFEST_DIR"),
+        "/../../examples/data/btcusdt-1m.csv"
+    );
+    CandleReader::open(path)
+        .expect("dataset present")
+        .read_all()
+        .expect("valid OHLCV rows")
+}
+
+/// Mean of the first `period` samples — the warmup seed for `kand`'s SMA/EMA `*_inc`.
+fn window_mean(series: &[f64], period: usize) -> f64 {
+    series[..period].iter().sum::<f64>() / period as f64
+}
+
+fn sma_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("sma_20");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Sma::new(SMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Sma::new(SMA_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let seed = window_mean(series, SMA_PERIOD);
+                bencher.iter(|| {
+                    let mut prev = seed;
+                    for idx in SMA_PERIOD..series.len() {
+                        prev = kand::ohlcv::sma::sma_inc(
+                            prev,
+                            series[idx],
+                            series[idx - SMA_PERIOD],
+                            SMA_PERIOD,
+                        )
+                        .unwrap();
+                        black_box(prev);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut out = vec![0.0; series.len()];
+                    kand::ohlcv::sma::sma(series, SMA_PERIOD, &mut out).unwrap();
+                    black_box(&out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::SimpleMovingAverage::new(SMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("yata/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = yata::methods::SMA::new(SMA_PERIOD as u8, &series[0]).unwrap();
+                    for price in series {
+                        black_box(ind.next(price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn ema_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("ema_20");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Ema::new(EMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Ema::new(EMA_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let seed = window_mean(series, EMA_PERIOD);
+                bencher.iter(|| {
+                    let mut prev = seed;
+                    for &price in &series[EMA_PERIOD..] {
+                        prev = kand::ohlcv::ema::ema_inc(price, prev, EMA_PERIOD, None).unwrap();
+                        black_box(prev);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut out = vec![0.0; series.len()];
+                    kand::ohlcv::ema::ema(series, EMA_PERIOD, None, &mut out).unwrap();
+                    black_box(&out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind =
+                        ta::indicators::ExponentialMovingAverage::new(EMA_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("yata/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = yata::methods::EMA::new(EMA_PERIOD as u8, &series[0]).unwrap();
+                    for price in series {
+                        black_box(ind.next(price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn rsi_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("rsi_14");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Rsi::new(RSI_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Rsi::new(RSI_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Wilder seed: simple average of the first `period` gains and losses.
+                let mut gain = 0.0;
+                let mut loss = 0.0;
+                for idx in 1..=RSI_PERIOD {
+                    let delta = series[idx] - series[idx - 1];
+                    if delta > 0.0 {
+                        gain += delta;
+                    } else {
+                        loss -= delta;
+                    }
+                }
+                let seed_gain = gain / RSI_PERIOD as f64;
+                let seed_loss = loss / RSI_PERIOD as f64;
+                bencher.iter(|| {
+                    let mut avg_gain = seed_gain;
+                    let mut avg_loss = seed_loss;
+                    let mut prev_price = series[RSI_PERIOD];
+                    for &price in &series[RSI_PERIOD + 1..] {
+                        let (rsi, next_gain, next_loss) = kand::ohlcv::rsi::rsi_inc(
+                            price, prev_price, avg_gain, avg_loss, RSI_PERIOD,
+                        )
+                        .unwrap();
+                        avg_gain = next_gain;
+                        avg_loss = next_loss;
+                        prev_price = price;
+                        black_box(rsi);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut rsi = vec![0.0; series.len()];
+                    let mut avg_gain = vec![0.0; series.len()];
+                    let mut avg_loss = vec![0.0; series.len()];
+                    kand::ohlcv::rsi::rsi(
+                        series,
+                        RSI_PERIOD,
+                        &mut rsi,
+                        &mut avg_gain,
+                        &mut avg_loss,
+                    )
+                    .unwrap();
+                    black_box(&rsi);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::RelativeStrengthIndex::new(RSI_PERIOD).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn macd_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("macd_12_26_9");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = MacdIndicator::classic();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = MacdIndicator::classic();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Seed the fast/slow/signal EMAs from kand's own warmed-up batch state.
+                let lookback =
+                    kand::ohlcv::macd::lookback(MACD_FAST, MACD_SLOW, MACD_SIGNAL).unwrap();
+                let mut macd_line = vec![0.0; series.len()];
+                let mut signal_line = vec![0.0; series.len()];
+                let mut histogram = vec![0.0; series.len()];
+                let mut fast_ema = vec![0.0; series.len()];
+                let mut slow_ema = vec![0.0; series.len()];
+                kand::ohlcv::macd::macd(
+                    series,
+                    MACD_FAST,
+                    MACD_SLOW,
+                    MACD_SIGNAL,
+                    &mut macd_line,
+                    &mut signal_line,
+                    &mut histogram,
+                    &mut fast_ema,
+                    &mut slow_ema,
+                )
+                .unwrap();
+                let seed_fast = fast_ema[lookback];
+                let seed_slow = slow_ema[lookback];
+                let seed_signal = signal_line[lookback];
+                bencher.iter(|| {
+                    // macd_inc returns (macd, signal, hist) but not the new EMAs, so the
+                    // fast/slow/signal state is threaded with kand's own ema_inc primitive.
+                    let mut prev_fast = seed_fast;
+                    let mut prev_slow = seed_slow;
+                    let mut prev_signal = seed_signal;
+                    for &price in &series[lookback + 1..] {
+                        let fast =
+                            kand::ohlcv::ema::ema_inc(price, prev_fast, MACD_FAST, None).unwrap();
+                        let slow =
+                            kand::ohlcv::ema::ema_inc(price, prev_slow, MACD_SLOW, None).unwrap();
+                        let macd = fast - slow;
+                        let signal =
+                            kand::ohlcv::ema::ema_inc(macd, prev_signal, MACD_SIGNAL, None)
+                                .unwrap();
+                        prev_fast = fast;
+                        prev_slow = slow;
+                        prev_signal = signal;
+                        black_box((macd, signal, macd - signal));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut macd_line = vec![0.0; series.len()];
+                    let mut signal_line = vec![0.0; series.len()];
+                    let mut histogram = vec![0.0; series.len()];
+                    let mut fast_ema = vec![0.0; series.len()];
+                    let mut slow_ema = vec![0.0; series.len()];
+                    kand::ohlcv::macd::macd(
+                        series,
+                        MACD_FAST,
+                        MACD_SLOW,
+                        MACD_SIGNAL,
+                        &mut macd_line,
+                        &mut signal_line,
+                        &mut histogram,
+                        &mut fast_ema,
+                        &mut slow_ema,
+                    )
+                    .unwrap();
+                    black_box(&macd_line);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::MovingAverageConvergenceDivergence::new(
+                        MACD_FAST,
+                        MACD_SLOW,
+                        MACD_SIGNAL,
+                    )
+                    .unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn bbands_group(crit: &mut Criterion, closes: &[f64]) {
+    let mut group = crit.benchmark_group("bollinger_20_2");
+    for &len in SIZES {
+        let len = len.min(closes.len());
+        let series: &[f64] = &closes[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    for &price in series {
+                        black_box(ind.update(price));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                // Seed running sma/sum/sum_sq from kand's batch state at the warmup edge.
+                let mut upper = vec![0.0; series.len()];
+                let mut middle = vec![0.0; series.len()];
+                let mut lower = vec![0.0; series.len()];
+                let mut sma = vec![0.0; series.len()];
+                let mut variance = vec![0.0; series.len()];
+                let mut sum = vec![0.0; series.len()];
+                let mut sum_sq = vec![0.0; series.len()];
+                kand::ohlcv::bbands::bbands(
+                    series,
+                    BB_PERIOD,
+                    BB_DEV,
+                    BB_DEV,
+                    &mut upper,
+                    &mut middle,
+                    &mut lower,
+                    &mut sma,
+                    &mut variance,
+                    &mut sum,
+                    &mut sum_sq,
+                )
+                .unwrap();
+                let seed_sma = sma[BB_PERIOD - 1];
+                let seed_sum = sum[BB_PERIOD - 1];
+                let seed_sum_sq = sum_sq[BB_PERIOD - 1];
+                bencher.iter(|| {
+                    let mut prev_sma = seed_sma;
+                    let mut prev_sum = seed_sum;
+                    let mut prev_sum_sq = seed_sum_sq;
+                    for idx in BB_PERIOD..series.len() {
+                        let result = kand::ohlcv::bbands::bbands_inc(
+                            series[idx],
+                            prev_sma,
+                            prev_sum,
+                            prev_sum_sq,
+                            series[idx - BB_PERIOD],
+                            BB_PERIOD,
+                            BB_DEV,
+                            BB_DEV,
+                        )
+                        .unwrap();
+                        prev_sma = result.1;
+                        prev_sum = result.4;
+                        prev_sum_sq = result.5;
+                        black_box((result.0, result.1, result.2));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut upper = vec![0.0; series.len()];
+                    let mut middle = vec![0.0; series.len()];
+                    let mut lower = vec![0.0; series.len()];
+                    let mut sma = vec![0.0; series.len()];
+                    let mut variance = vec![0.0; series.len()];
+                    let mut sum = vec![0.0; series.len()];
+                    let mut sum_sq = vec![0.0; series.len()];
+                    kand::ohlcv::bbands::bbands(
+                        series,
+                        BB_PERIOD,
+                        BB_DEV,
+                        BB_DEV,
+                        &mut upper,
+                        &mut middle,
+                        &mut lower,
+                        &mut sma,
+                        &mut variance,
+                        &mut sum,
+                        &mut sum_sq,
+                    )
+                    .unwrap();
+                    black_box(&upper);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::BollingerBands::new(BB_PERIOD, BB_DEV).unwrap();
+                    for &price in series {
+                        black_box(ta::Next::next(&mut ind, price));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn atr_group(crit: &mut Criterion, candles: &[Candle]) {
+    let mut group = crit.benchmark_group("atr_14");
+    for &len in SIZES {
+        let len = len.min(candles.len());
+        let series: &[Candle] = &candles[..len];
+        group.throughput(Throughput::Elements(len as u64));
+
+        group.bench_with_input(
+            BenchmarkId::new("wickra/stream", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Atr::new(ATR_PERIOD).unwrap();
+                    for &candle in series {
+                        black_box(ind.update(candle));
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("wickra/batch", len),
+            &series,
+            |bencher, &series| {
+                bencher.iter(|| {
+                    let mut ind = Atr::new(ATR_PERIOD).unwrap();
+                    black_box(ind.batch(series));
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/stream", len),
+            &series,
+            |bencher, &series| {
+                let high: Vec<f64> = series.iter().map(|candle| candle.high).collect();
+                let low: Vec<f64> = series.iter().map(|candle| candle.low).collect();
+                let close: Vec<f64> = series.iter().map(|candle| candle.close).collect();
+                // Seed prev_atr from kand's batch ATR at the first valid index (= period).
+                let mut atr_out = vec![0.0; series.len()];
+                kand::ohlcv::atr::atr(&high, &low, &close, ATR_PERIOD, &mut atr_out).unwrap();
+                let seed_atr = atr_out[ATR_PERIOD];
+                bencher.iter(|| {
+                    let mut prev_atr = seed_atr;
+                    for idx in ATR_PERIOD + 1..series.len() {
+                        prev_atr = kand::ohlcv::atr::atr_inc(
+                            high[idx],
+                            low[idx],
+                            close[idx - 1],
+                            prev_atr,
+                            ATR_PERIOD,
+                        )
+                        .unwrap();
+                        black_box(prev_atr);
+                    }
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("kand/batch", len),
+            &series,
+            |bencher, &series| {
+                let high: Vec<f64> = series.iter().map(|candle| candle.high).collect();
+                let low: Vec<f64> = series.iter().map(|candle| candle.low).collect();
+                let close: Vec<f64> = series.iter().map(|candle| candle.close).collect();
+                bencher.iter(|| {
+                    let mut atr_out = vec![0.0; series.len()];
+                    kand::ohlcv::atr::atr(&high, &low, &close, ATR_PERIOD, &mut atr_out).unwrap();
+                    black_box(&atr_out);
+                });
+            },
+        );
+        group.bench_with_input(
+            BenchmarkId::new("ta-rs/stream", len),
+            &series,
+            |bencher, &series| {
+                let items: Vec<ta::DataItem> = series
+                    .iter()
+                    .map(|candle| {
+                        ta::DataItem::builder()
+                            .open(candle.open)
+                            .high(candle.high)
+                            .low(candle.low)
+                            .close(candle.close)
+                            .volume(candle.volume)
+                            .build()
+                            .unwrap()
+                    })
+                    .collect();
+                bencher.iter(|| {
+                    let mut ind = ta::indicators::AverageTrueRange::new(ATR_PERIOD).unwrap();
+                    for item in &items {
+                        black_box(ta::Next::next(&mut ind, item));
+                    }
+                });
+            },
+        );
+    }
+    group.finish();
+}
+
+fn benches(crit: &mut Criterion) {
+    let candles = load_candles();
+    let closes: Vec<f64> = candles.iter().map(|candle| candle.close).collect();
+    sma_group(crit, &closes);
+    ema_group(crit, &closes);
+    rsi_group(crit, &closes);
+    macd_group(crit, &closes);
+    bbands_group(crit, &closes);
+    atr_group(crit, &candles);
+}
+
+criterion_group!(name = cross_lib; config = Criterion::default(); targets = benches);
+criterion_main!(cross_lib);

crates/wickra-bench/src/lib.rs

@@ -0,0 +1,6 @@
+//! Internal cross-library benchmark harness for Wickra.
+//!
+//! This crate is `publish = false`. It exists only to host the Criterion
+//! benchmark in `benches/cross_lib.rs`, which compares Wickra against the
+//! Rust technical-analysis crates `kand`, `ta` (ta-rs) and `yata` on an
+//! identical candle series. It deliberately carries no library code.

crates/wickra-core/Cargo.toml

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

crates/wickra-core/src/calendar.rs

@@ -0,0 +1,203 @@
+//! Pure calendar arithmetic for the timestamp-driven seasonality indicators.
+//!
+//! Every indicator in the *Seasonality & Session* family keys off the wall-clock
+//! fields of [`Candle::timestamp`](crate::Candle) (epoch milliseconds), shifted
+//! by a caller-supplied `utc_offset_minutes` so the buckets line up with the
+//! relevant exchange session rather than UTC. This module turns an epoch
+//! millisecond instant into its civil fields using Howard Hinnant's
+//! branch-light `civil_from_days` algorithm (the same one libc++ ships).
+//!
+//! All arithmetic is floor-based (`div_euclid`/`rem_euclid`) so instants before
+//! the Unix epoch decompose correctly without a dedicated negative-input branch.
+
+/// Civil (wall-clock) decomposition of an epoch-millisecond instant.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub(crate) struct CivilTime {
+    /// Proleptic Gregorian year (can be negative for instants before year 1).
+    pub(crate) year: i64,
+    /// Month of year, `1..=12`.
+    pub(crate) month: u32,
+    /// Day of month, `1..=31`.
+    pub(crate) day: u32,
+    /// Hour of day, `0..=23`.
+    pub(crate) hour: u32,
+    /// Minute of hour, `0..=59`.
+    pub(crate) minute: u32,
+    /// Day of week with Monday as `0` through Sunday as `6`.
+    pub(crate) weekday: u32,
+}
+
+impl CivilTime {
+    /// Minute of day, `0..=1439`.
+    pub(crate) const fn minute_of_day(&self) -> u32 {
+        self.hour * 60 + self.minute
+    }
+}
+
+/// Decompose an epoch-millisecond instant into local civil fields.
+///
+/// `utc_offset_minutes` shifts the instant before decomposition: `0` yields
+/// UTC, `-300` U.S. Eastern standard time, `60` Central European time, etc.
+pub(crate) fn civil_from_timestamp(millis: i64, utc_offset_minutes: i32) -> CivilTime {
+    let local_secs = millis.div_euclid(1000) + i64::from(utc_offset_minutes) * 60;
+    let days = local_secs.div_euclid(86_400);
+    let secs_of_day = local_secs.rem_euclid(86_400);
+    let hour = (secs_of_day / 3600) as u32;
+    let minute = ((secs_of_day % 3600) / 60) as u32;
+    let (year, month, day) = civil_from_days(days);
+    // 1970-01-01 was a Thursday; Monday-based weekday is `(z + 3) mod 7`.
+    let weekday = (days + 3).rem_euclid(7) as u32;
+    CivilTime {
+        year,
+        month,
+        day,
+        hour,
+        minute,
+        weekday,
+    }
+}
+
+/// Gregorian `(year, month, day)` for a day count `z` relative to 1970-01-01.
+///
+/// Howard Hinnant, "chrono-Compatible Low-Level Date Algorithms".
+fn civil_from_days(z: i64) -> (i64, u32, u32) {
+    let z = z + 719_468;
+    let era = if z >= 0 { z } else { z - 146_096 } / 146_097;
+    let doe = z - era * 146_097; // [0, 146096]
+    let yoe = (doe - doe / 1460 + doe / 36_524 - doe / 146_096) / 365; // [0, 399]
+    let year = yoe + era * 400;
+    let doy = doe - (365 * yoe + yoe / 4 - yoe / 100); // [0, 365]
+    let mp = (5 * doy + 2) / 153; // [0, 11]
+    let day = (doy - (153 * mp + 2) / 5 + 1) as u32; // [1, 31]
+    let month = if mp < 10 { mp + 3 } else { mp - 9 } as u32; // [1, 12]
+    (if month <= 2 { year + 1 } else { year }, month, day)
+}
+
+/// Whether `year` is a Gregorian leap year.
+pub(crate) const fn is_leap(year: i64) -> bool {
+    (year % 4 == 0 && year % 100 != 0) || year % 400 == 0
+}
+
+/// Number of days in `month` (`1..=12`) of `year`.
+pub(crate) const fn days_in_month(year: i64, month: u32) -> u32 {
+    match month {
+        1 | 3 | 5 | 7 | 8 | 10 | 12 => 31,
+        4 | 6 | 9 | 11 => 30,
+        _ => {
+            if is_leap(year) {
+                29
+            } else {
+                28
+            }
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn epoch_zero_is_thursday_midnight() {
+        let t = civil_from_timestamp(0, 0);
+        assert_eq!(
+            t,
+            CivilTime {
+                year: 1970,
+                month: 1,
+                day: 1,
+                hour: 0,
+                minute: 0,
+                weekday: 3, // Thursday
+            }
+        );
+        assert_eq!(t.minute_of_day(), 0);
+    }
+
+    #[test]
+    fn known_utc_instant_mid_year() {
+        // 2021-06-15 13:45:00 UTC = 1623764700 s.
+        let t = civil_from_timestamp(1_623_764_700_000, 0);
+        assert_eq!(t.year, 2021);
+        assert_eq!(t.month, 6);
+        assert_eq!(t.day, 15);
+        assert_eq!(t.hour, 13);
+        assert_eq!(t.minute, 45);
+        assert_eq!(t.weekday, 1); // Tuesday
+        assert_eq!(t.minute_of_day(), 13 * 60 + 45);
+    }
+
+    #[test]
+    fn new_year_2021_is_friday() {
+        // 2021-01-01 00:00:00 UTC = 1609459200 s — exercises the m<=2 year bump.
+        let t = civil_from_timestamp(1_609_459_200_000, 0);
+        assert_eq!((t.year, t.month, t.day), (2021, 1, 1));
+        assert_eq!(t.weekday, 4); // Friday
+    }
+
+    #[test]
+    fn positive_offset_rolls_to_next_day() {
+        // 2021-01-01 23:30 UTC shifted +60 min -> 2021-01-02 00:30 local.
+        let base = 1_609_459_200_000 + (23 * 3600 + 30 * 60) * 1000;
+        let t = civil_from_timestamp(base, 60);
+        assert_eq!((t.year, t.month, t.day), (2021, 1, 2));
+        assert_eq!((t.hour, t.minute), (0, 30));
+        assert_eq!(t.weekday, 5); // Saturday
+    }
+
+    #[test]
+    fn negative_offset_rolls_to_previous_day() {
+        // 2021-01-01 00:30 UTC shifted -60 min -> 2020-12-31 23:30 local.
+        let base = 1_609_459_200_000 + 30 * 60 * 1000;
+        let t = civil_from_timestamp(base, -60);
+        assert_eq!((t.year, t.month, t.day), (2020, 12, 31));
+        assert_eq!((t.hour, t.minute), (23, 30));
+        assert_eq!(t.weekday, 3); // Thursday
+    }
+
+    #[test]
+    fn sub_epoch_millis_floor_correctly() {
+        // -1 ms -> 1969-12-31 23:59:59.999, a Wednesday.
+        let t = civil_from_timestamp(-1, 0);
+        assert_eq!((t.year, t.month, t.day), (1969, 12, 31));
+        assert_eq!((t.hour, t.minute), (23, 59));
+        assert_eq!(t.weekday, 2); // Wednesday
+    }
+
+    #[test]
+    fn far_negative_day_count_hits_pre_era_branch() {
+        // A day count below -719468 drives `z + 719468` negative, exercising the
+        // `z - 146096` era branch in civil_from_days (year < 1).
+        let (year, month, day) = civil_from_days(-1_000_000);
+        // -1_000_000 days before 1970-01-01 is 0768-02-04 BCE (proleptic
+        // Gregorian, astronomical year numbering where year 0 exists).
+        assert_eq!((year, month, day), (-768, 2, 4));
+    }
+
+    #[test]
+    fn leap_year_rules() {
+        assert!(is_leap(2000));
+        assert!(!is_leap(1900));
+        assert!(is_leap(2024));
+        assert!(!is_leap(2023));
+    }
+
+    #[test]
+    fn days_in_month_all_cases() {
+        assert_eq!(days_in_month(2023, 1), 31);
+        assert_eq!(days_in_month(2023, 4), 30);
+        assert_eq!(days_in_month(2023, 2), 28);
+        assert_eq!(days_in_month(2024, 2), 29);
+        assert_eq!(days_in_month(2023, 12), 31);
+        assert_eq!(days_in_month(2023, 11), 30);
+    }
+
+    #[test]
+    fn leap_day_decodes() {
+        // 2024-02-29 12:00 UTC.
+        let secs = 1_709_208_000; // 2024-02-29T12:00:00Z
+        let t = civil_from_timestamp(secs * 1000, 0);
+        assert_eq!((t.year, t.month, t.day), (2024, 2, 29));
+        assert_eq!(t.hour, 12);
+    }
+}

crates/wickra-core/src/cross_section.rs

@@ -0,0 +1,387 @@
+//! Cross-section value type: a market-breadth snapshot across a whole universe.
+//!
+//! A [`CrossSection`] is a single tick that carries the per-symbol state of
+//! *every* symbol in a universe at one point in time. It is the non-OHLCV input
+//! consumed by the market-breadth indicator family (advance/decline, `McClellan`,
+//! the TRIN / Arms index, the high-low index, ...), each of which aggregates the
+//! whole cross-section into a single breadth reading. This is the same
+//! one-rich-type-per-family pattern as [`DerivativesTick`] and [`OrderBook`].
+//!
+//! Each [`Member`] precomputes the per-symbol signals the breadth indicators
+//! need — a signed price `change` (whose sign classifies the symbol as
+//! advancing, declining or unchanged), the period `volume`, the
+//! `new_high` / `new_low` extreme flags, and the `above_ma` / `on_buy_signal`
+//! state flags — so the indicators stay stateless per tick and never have to
+//! track per-symbol history.
+//!
+//! [`DerivativesTick`]: crate::DerivativesTick
+//! [`OrderBook`]: crate::OrderBook
+
+use crate::error::{Error, Result};
+
+/// One symbol's contribution to a [`CrossSection`] tick.
+///
+/// Field invariants enforced by [`CrossSection::new`] when the member is placed
+/// into a tick:
+///
+/// - `change` is finite (its sign classifies the symbol — positive is
+///   advancing, negative is declining, zero is unchanged).
+/// - `volume` is finite and non-negative.
+///
+/// `new_high` / `new_low` are caller-supplied flags marking whether the symbol
+/// printed a new period extreme; `above_ma` / `on_buy_signal` are caller-supplied
+/// per-symbol state signals (whether the symbol trades above its reference moving
+/// average, and whether it is on a point-and-figure buy signal). None of the four
+/// flags carries a numeric invariant.
+#[non_exhaustive]
+#[derive(Debug, Clone, Copy, PartialEq)]
+#[allow(
+    clippy::struct_excessive_bools,
+    reason = "the four flags are independent per-symbol breadth signals, not a state machine"
+)]
+pub struct Member {
+    /// Price change versus the previous close. Sign classifies the symbol:
+    /// positive is advancing, negative is declining, zero is unchanged.
+    pub change: f64,
+    /// Period volume for the symbol (finite, non-negative).
+    pub volume: f64,
+    /// Whether the symbol printed a new period high.
+    pub new_high: bool,
+    /// Whether the symbol printed a new period low.
+    pub new_low: bool,
+    /// Whether the symbol is trading above its reference moving average
+    /// (consumed by the `% Above Moving Average` breadth indicator).
+    pub above_ma: bool,
+    /// Whether the symbol is on a point-and-figure buy signal
+    /// (consumed by the `Bullish Percent Index` breadth indicator).
+    pub on_buy_signal: bool,
+}
+
+impl Member {
+    /// Assemble a cross-section member from its core signals, leaving the
+    /// extended per-symbol state flags (`above_ma`, `on_buy_signal`) cleared.
+    ///
+    /// The field invariants documented on [`Member`] are validated centrally by
+    /// [`CrossSection::new`] when the member is placed into a tick; this
+    /// constructor only assembles the value so the `#[non_exhaustive]` struct can
+    /// be built from outside the crate.
+    #[must_use]
+    pub const fn new(change: f64, volume: f64, new_high: bool, new_low: bool) -> Self {
+        Self {
+            change,
+            volume,
+            new_high,
+            new_low,
+            above_ma: false,
+            on_buy_signal: false,
+        }
+    }
+
+    /// Assemble a cross-section member including the extended per-symbol state
+    /// signals `above_ma` and `on_buy_signal`.
+    ///
+    /// Use this constructor for the breadth indicators that read per-symbol
+    /// state (`% Above Moving Average`, `Bullish Percent Index`); [`new`](Member::new)
+    /// is the shorthand that leaves both flags `false`.
+    #[must_use]
+    #[allow(
+        clippy::fn_params_excessive_bools,
+        reason = "mirrors the four independent per-symbol flag fields of Member"
+    )]
+    pub const fn with_signals(
+        change: f64,
+        volume: f64,
+        new_high: bool,
+        new_low: bool,
+        above_ma: bool,
+        on_buy_signal: bool,
+    ) -> Self {
+        Self {
+            change,
+            volume,
+            new_high,
+            new_low,
+            above_ma,
+            on_buy_signal,
+        }
+    }
+}
+
+/// A market-breadth cross-section: the per-symbol state of an entire universe at
+/// a single point in time.
+///
+/// Invariants enforced by [`new`](CrossSection::new):
+///
+/// - `members` is non-empty (a breadth reading needs at least one symbol).
+/// - every member's `change` is finite, and `volume` is finite and non-negative.
+///
+/// `timestamp` is a caller-defined epoch / resolution and is not validated.
+#[non_exhaustive]
+#[derive(Debug, Clone, PartialEq)]
+pub struct CrossSection {
+    /// Per-symbol members of the universe for this tick.
+    pub members: Vec<Member>,
+    /// Tick timestamp (caller-defined epoch / resolution).
+    pub timestamp: i64,
+}
+
+impl CrossSection {
+    /// Construct a cross-section, validating every member invariant.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidCrossSection`] if `members` is empty, if any
+    /// member has a non-finite `change`, or if any member has a `volume` that is
+    /// not a finite non-negative number.
+    pub fn new(members: Vec<Member>, timestamp: i64) -> Result<Self> {
+        if members.is_empty() {
+            return Err(Error::InvalidCrossSection {
+                message: "cross-section must contain at least one member",
+            });
+        }
+        for member in &members {
+            if !member.change.is_finite() {
+                return Err(Error::InvalidCrossSection {
+                    message: "member change must be finite",
+                });
+            }
+            if !member.volume.is_finite() || member.volume < 0.0 {
+                return Err(Error::InvalidCrossSection {
+                    message: "member volume must be finite and non-negative",
+                });
+            }
+        }
+        Ok(Self { members, timestamp })
+    }
+
+    /// Construct a cross-section without validation. The caller asserts that
+    /// every invariant documented on [`CrossSection`] holds.
+    #[must_use]
+    pub const fn new_unchecked(members: Vec<Member>, timestamp: i64) -> Self {
+        Self { members, timestamp }
+    }
+
+    /// Number of advancing symbols (those with a strictly positive `change`).
+    #[must_use]
+    pub fn advancers(&self) -> usize {
+        self.members.iter().filter(|m| m.change > 0.0).count()
+    }
+
+    /// Number of declining symbols (those with a strictly negative `change`).
+    #[must_use]
+    pub fn decliners(&self) -> usize {
+        self.members.iter().filter(|m| m.change < 0.0).count()
+    }
+
+    /// Total volume traded by advancing symbols (those with positive `change`).
+    #[must_use]
+    pub fn advancing_volume(&self) -> f64 {
+        self.members
+            .iter()
+            .filter(|m| m.change > 0.0)
+            .map(|m| m.volume)
+            .sum()
+    }
+
+    /// Total volume traded by declining symbols (those with negative `change`).
+    #[must_use]
+    pub fn declining_volume(&self) -> f64 {
+        self.members
+            .iter()
+            .filter(|m| m.change < 0.0)
+            .map(|m| m.volume)
+            .sum()
+    }
+
+    /// Total volume traded across the whole universe.
+    #[must_use]
+    pub fn total_volume(&self) -> f64 {
+        self.members.iter().map(|m| m.volume).sum()
+    }
+
+    /// Number of symbols that printed a new period high.
+    #[must_use]
+    pub fn new_highs(&self) -> usize {
+        self.members.iter().filter(|m| m.new_high).count()
+    }
+
+    /// Number of symbols that printed a new period low.
+    #[must_use]
+    pub fn new_lows(&self) -> usize {
+        self.members.iter().filter(|m| m.new_low).count()
+    }
+
+    /// Number of symbols trading above their reference moving average.
+    #[must_use]
+    pub fn above_ma_count(&self) -> usize {
+        self.members.iter().filter(|m| m.above_ma).count()
+    }
+
+    /// Number of symbols on a point-and-figure buy signal.
+    #[must_use]
+    pub fn on_buy_signal_count(&self) -> usize {
+        self.members.iter().filter(|m| m.on_buy_signal).count()
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn members() -> Vec<Member> {
+        vec![
+            Member::new(1.5, 100.0, true, false),
+            Member::new(-0.5, 50.0, false, true),
+            Member::new(0.0, 0.0, false, false),
+        ]
+    }
+
+    #[test]
+    fn new_accepts_valid() {
+        let cs = CrossSection::new(members(), 42).unwrap();
+        assert_eq!(cs.members.len(), 3);
+        assert_eq!(cs.timestamp, 42);
+        assert_eq!(cs.members[0].change, 1.5);
+        assert_eq!(cs.members[0].volume, 100.0);
+        assert!(cs.members[0].new_high);
+        assert!(cs.members[1].new_low);
+    }
+
+    #[test]
+    fn member_new_assembles_fields() {
+        let m = Member::new(2.0, 10.0, true, false);
+        assert_eq!(m.change, 2.0);
+        assert_eq!(m.volume, 10.0);
+        assert!(m.new_high);
+        assert!(!m.new_low);
+    }
+
+    #[test]
+    fn new_rejects_empty() {
+        assert!(matches!(
+            CrossSection::new(Vec::new(), 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_change() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(f64::NAN, 10.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(f64::INFINITY, 10.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_negative_volume() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(1.0, -1.0, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_rejects_non_finite_volume() {
+        assert!(matches!(
+            CrossSection::new(vec![Member::new(1.0, f64::NAN, false, false)], 0),
+            Err(Error::InvalidCrossSection { .. })
+        ));
+    }
+
+    #[test]
+    fn new_unchecked_skips_validation() {
+        let cs = CrossSection::new_unchecked(vec![Member::new(f64::NAN, -1.0, false, false)], 7);
+        assert_eq!(cs.members.len(), 1);
+        assert_eq!(cs.timestamp, 7);
+    }
+
+    #[test]
+    fn advancers_and_decliners_count_by_sign() {
+        let cs = CrossSection::new(members(), 0).unwrap();
+        assert_eq!(cs.advancers(), 1);
+        assert_eq!(cs.decliners(), 1);
+    }
+
+    #[test]
+    fn unchanged_members_count_as_neither() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(0.0, 1.0, false, false),
+                Member::new(0.0, 1.0, false, false),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.advancers(), 0);
+        assert_eq!(cs.decliners(), 0);
+    }
+
+    #[test]
+    fn new_leaves_extended_flags_cleared() {
+        let m = Member::new(1.0, 10.0, true, false);
+        assert!(!m.above_ma);
+        assert!(!m.on_buy_signal);
+    }
+
+    #[test]
+    fn with_signals_assembles_all_fields() {
+        let m = Member::with_signals(2.0, 10.0, true, false, true, true);
+        assert_eq!(m.change, 2.0);
+        assert_eq!(m.volume, 10.0);
+        assert!(m.new_high);
+        assert!(!m.new_low);
+        assert!(m.above_ma);
+        assert!(m.on_buy_signal);
+    }
+
+    #[test]
+    fn volume_helpers_bucket_by_change_sign() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(1.5, 100.0, false, false), // advancing
+                Member::new(2.0, 40.0, false, false),  // advancing
+                Member::new(-0.5, 50.0, false, false), // declining
+                Member::new(0.0, 7.0, false, false),   // unchanged
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.advancing_volume(), 140.0);
+        assert_eq!(cs.declining_volume(), 50.0);
+        assert_eq!(cs.total_volume(), 197.0);
+    }
+
+    #[test]
+    fn high_low_helpers_count_flags() {
+        let cs = CrossSection::new(
+            vec![
+                Member::new(1.0, 1.0, true, false),
+                Member::new(1.0, 1.0, true, false),
+                Member::new(-1.0, 1.0, false, true),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.new_highs(), 2);
+        assert_eq!(cs.new_lows(), 1);
+    }
+
+    #[test]
+    fn state_helpers_count_extended_flags() {
+        let cs = CrossSection::new(
+            vec![
+                Member::with_signals(1.0, 1.0, false, false, true, true),
+                Member::with_signals(1.0, 1.0, false, false, true, false),
+                Member::with_signals(-1.0, 1.0, false, false, false, true),
+            ],
+            0,
+        )
+        .unwrap();
+        assert_eq!(cs.above_ma_count(), 2);
+        assert_eq!(cs.on_buy_signal_count(), 2);
+    }
+}

crates/wickra-core/src/error.rs

@@ -52,6 +52,21 @@ pub enum Error {
     /// own variant.
     #[error("invalid derivatives tick: {message}")]
     InvalidDerivatives { message: &'static str },
+
+    /// A market-breadth cross-section whose members do not satisfy the
+    /// cross-section invariants (an empty universe, a non-finite change, or a
+    /// negative / non-finite volume) was provided. A cross-section is a
+    /// breadth input distinct from candles, ticks, order books and trades, so
+    /// it surfaces as its own variant.
+    #[error("invalid cross-section: {message}")]
+    InvalidCrossSection { message: &'static str },
+
+    /// A real-valued configuration parameter was outside its admissible range
+    /// (e.g. a non-positive standard-deviation multiplier, or a Kalman filter
+    /// covariance that is not strictly positive). This is the floating-point
+    /// analogue of [`Error::InvalidPeriod`], which only covers integer windows.
+    #[error("invalid parameter: {message}")]
+    InvalidParameter { message: &'static str },
 }
 
 /// Convenience alias for `Result<T, wickra_core::Error>`.

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

@@ -0,0 +1,154 @@
+//! AB=CD harmonic pattern.
+
+use crate::indicators::pattern_swing::{approx_equal, ratios_in, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// AB=CD — the simplest four-point harmonic pattern: an A→B leg, a B→C
+/// retracement, and a C→D leg that mirrors A→B in length:
+///
+/// ```text
+/// BC / AB ∈ [0.382, 0.886]   (C retraces AB)
+/// CD / BC ∈ [1.13, 2.618]    (D extends BC)
+/// AB ≈ CD (within 10%)        (the two legs are equal — the defining symmetry)
+/// ```
+///
+/// Read from the last four confirmed pivots `A-B-C-D`. Output is `+1.0`
+/// (bullish, D a swing low), `-1.0` (bearish, D a swing high), or `0.0`; never
+/// `None`. See `crates/wickra-core/src/indicators/abcd.rs`.
+#[derive(Debug, Clone)]
+pub struct Abcd {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Abcd {
+    /// Construct a new AB=CD detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 4),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Abcd {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Abcd {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 4 {
+            return Some(0.0);
+        }
+        let len = pivots.len();
+        let pa = pivots[len - 4];
+        let pb = pivots[len - 3];
+        let pc = pivots[len - 2];
+        let pd = pivots[len - 1];
+        let ab = (pb.price - pa.price).abs();
+        let bc = (pc.price - pb.price).abs();
+        let cd = (pd.price - pc.price).abs();
+        let ratios_ok = ratios_in(&[(bc / ab, 0.382, 0.886), (cd / bc, 1.13, 2.618)]);
+        let legs_equal = approx_equal(ab, cd, 0.10);
+        if ratios_ok && legs_equal {
+            return Some(if pd.direction < 0.0 { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        5
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Abcd"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Abcd::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Abcd::new();
+        assert_eq!(indicator.name(), "Abcd");
+        assert_eq!(indicator.warmup_period(), 5);
+        assert!(!indicator.is_ready());
+        assert!(!Abcd::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_abcd_is_plus_one() {
+        // AB = 40 down, BC = 24.7 up (0.618), CD = 40 down → AB = CD.
+        let out = run(&[140.0, 100.0, 124.7, 84.7]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_abcd_is_minus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 115.3, 155.3]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn unequal_legs_do_not_trigger() {
+        // CD (82) far longer than AB (40) → not an AB=CD.
+        let out = run(&[150.0, 100.0, 140.0, 118.0, 200.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Abcd::new();
+        for c in candles_for_pivots(&[140.0, 100.0, 124.7]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[140.0, 100.0, 124.7, 84.7]);
+        let mut a = Abcd::new();
+        let mut b = Abcd::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,144 @@
+//! Absolute Breadth Index — the magnitude of net advancing-minus-declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Absolute Breadth Index (ABI) — the absolute value of net advancing issues,
+/// `|advancers - decliners|`.
+///
+/// The ABI ignores the *direction* of breadth and measures only its *magnitude*:
+/// a high reading means the universe moved decisively one way or the other (high
+/// internal activity / volatility), while a low reading means advances and
+/// declines were nearly balanced (a quiet, directionless market). It is sometimes
+/// called a "market thermometer" because elevated readings often cluster around
+/// turning points.
+///
+/// `Input = CrossSection`, `Output = f64`, `warmup_period == 1`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AbsoluteBreadthIndex, CrossSection, Indicator, Member};
+///
+/// let mut abi = AbsoluteBreadthIndex::new();
+/// // 2 advancers, 5 decliners -> |2 - 5| = 3.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(abi.update(tick), Some(3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AbsoluteBreadthIndex {
+    has_emitted: bool,
+}
+
+impl AbsoluteBreadthIndex {
+    /// Construct a new Absolute Breadth Index indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AbsoluteBreadthIndex {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancers() as f64 - section.decliners() as f64;
+        self.has_emitted = true;
+        Some(net.abs())
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AbsoluteBreadthIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.name(), "AbsoluteBreadthIndex");
+        assert_eq!(abi.warmup_period(), 1);
+        assert!(!abi.is_ready());
+    }
+
+    #[test]
+    fn magnitude_ignores_direction() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.update(section(2, 5)), Some(3.0));
+        // Same magnitude with the direction reversed.
+        let mut abi2 = AbsoluteBreadthIndex::new();
+        assert_eq!(abi2.update(section(5, 2)), Some(3.0));
+    }
+
+    #[test]
+    fn balanced_universe_yields_zero() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        assert_eq!(abi.update(section(3, 3)), Some(0.0));
+        assert!(abi.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut abi = AbsoluteBreadthIndex::new();
+        abi.update(section(2, 5));
+        assert!(abi.is_ready());
+        abi.reset();
+        assert!(!abi.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(2, 5), section(5, 2), section(3, 3)];
+        let mut a = AbsoluteBreadthIndex::new();
+        let mut b = AbsoluteBreadthIndex::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,157 @@
+//! Advance/Decline Volume Line — cumulative net advancing-minus-declining volume.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Volume Line (AD Volume Line) — the running cumulative sum of
+/// net advancing volume across a universe.
+///
+/// On each [`CrossSection`] tick the net is `advancing volume - declining volume`,
+/// where advancing volume is the total volume of symbols with a positive change
+/// and declining volume the total volume of symbols with a negative change. The
+/// line accumulates this net over time, so a rising line means volume is flowing
+/// into advancing issues (healthy participation) while a falling line warns that
+/// declining issues are carrying the volume — the volume-weighted analogue of the
+/// plain Advance/Decline Line.
+///
+/// `Input = CrossSection`, `Output = f64`, `warmup_period == 1` (defined from the
+/// first tick).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdVolumeLine, CrossSection, Indicator, Member};
+///
+/// let mut adv = AdVolumeLine::new();
+/// // advancing volume 150, declining volume 50 -> net +100.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 150.0, false, false),
+///         Member::new(-1.0, 50.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(adv.update(tick), Some(100.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdVolumeLine {
+    line: f64,
+    has_emitted: bool,
+}
+
+impl AdVolumeLine {
+    /// Construct a new Advance/Decline Volume Line indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            line: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for AdVolumeLine {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancing_volume() - section.declining_volume();
+        self.line += net;
+        self.has_emitted = true;
+        Some(self.line)
+    }
+
+    fn reset(&mut self) {
+        self.line = 0.0;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdVolumeLine"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn tick(items: &[(f64, f64)]) -> CrossSection {
+        CrossSection::new(
+            items
+                .iter()
+                .map(|&(change, volume)| Member::new(change, volume, false, false))
+                .collect(),
+            0,
+        )
+        .unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let adv = AdVolumeLine::new();
+        assert_eq!(adv.name(), "AdVolumeLine");
+        assert_eq!(adv.warmup_period(), 1);
+        assert!(!adv.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_net_volume() {
+        let mut adv = AdVolumeLine::new();
+        assert_eq!(adv.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(100.0));
+        assert!(adv.is_ready());
+    }
+
+    #[test]
+    fn line_accumulates_across_ticks() {
+        let mut adv = AdVolumeLine::new();
+        assert_eq!(adv.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(100.0));
+        assert_eq!(adv.update(tick(&[(1.0, 60.0), (-1.0, 60.0)])), Some(100.0));
+        assert_eq!(adv.update(tick(&[(1.0, 30.0)])), Some(130.0));
+    }
+
+    #[test]
+    fn unchanged_volume_is_ignored() {
+        let mut adv = AdVolumeLine::new();
+        // Unchanged symbols (zero change) contribute to neither bucket.
+        assert_eq!(adv.update(tick(&[(0.0, 1000.0), (1.0, 10.0)])), Some(10.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adv = AdVolumeLine::new();
+        adv.update(tick(&[(1.0, 100.0)]));
+        assert!(adv.is_ready());
+        adv.reset();
+        assert!(!adv.is_ready());
+        assert_eq!(adv.update(tick(&[(1.0, 20.0)])), Some(20.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![
+            tick(&[(1.0, 150.0), (-1.0, 50.0)]),
+            tick(&[(1.0, 60.0), (-1.0, 60.0)]),
+            tick(&[(1.0, 30.0)]),
+        ];
+        let mut a = AdVolumeLine::new();
+        let mut b = AdVolumeLine::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,344 @@
+//! Ehlers' Adaptive Laguerre Filter.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// John Ehlers' Adaptive Laguerre Filter — a four-stage Laguerre polynomial
+/// smoother whose damping factor `gamma` is recomputed every bar from how well
+/// the filter is currently tracking price.
+///
+/// The Laguerre cascade is the same one used by [`LaguerreRsi`](crate::LaguerreRsi),
+/// but instead of a fixed `gamma` the filter adapts: it measures the recent
+/// absolute error `|price − filter|`, normalises those errors across a window of
+/// `period` bars to `[0, 1]`, and takes their **median** as `gamma`. When price
+/// is tracking smoothly the errors are small and uniform (low `gamma`, fast
+/// response); when price jumps, the spread of errors widens and `gamma` rises,
+/// slowing the filter to reject the noise.
+///
+/// ```text
+/// diff_t  = |price_t − filter_{t-1}|
+/// over the last `period` diffs:
+///   HH = max(diff),  LL = min(diff)
+///   norm_i = (diff_i − LL) / (HH − LL)      (0 if HH == LL)
+///   gamma  = median(norm)
+/// alpha   = 1 − gamma
+/// L0_t = alpha·price_t + gamma·L0_{t-1}
+/// L1_t = −gamma·L0_t + L0_{t-1} + gamma·L1_{t-1}
+/// L2_t = −gamma·L1_t + L1_{t-1} + gamma·L2_{t-1}
+/// L3_t = −gamma·L2_t + L2_{t-1} + gamma·L3_{t-1}
+/// filter_t = (L0_t + 2·L1_t + 2·L2_t + L3_t) / 6
+/// ```
+///
+/// The output is a smoothed price on the same scale as the input. The first
+/// emission lands once the error window holds `period` values.
+///
+/// Reference: John F. Ehlers, *"Adaptive Laguerre Filter"*, Technical Analysis
+/// of Stocks & Commodities, 2007.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, AdaptiveLaguerreFilter};
+///
+/// let mut indicator = AdaptiveLaguerreFilter::new(13).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + f64::from(i));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct AdaptiveLaguerreFilter {
+    period: usize,
+    l0: f64,
+    l1: f64,
+    l2: f64,
+    l3: f64,
+    /// Previous filter output, or `None` before the first bar.
+    filter: Option<f64>,
+    /// The last `period` absolute errors `|price − filter|`.
+    diffs: VecDeque<f64>,
+}
+
+impl AdaptiveLaguerreFilter {
+    /// Construct a new adaptive Laguerre filter with the given error-window
+    /// length.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            l0: 0.0,
+            l1: 0.0,
+            l2: 0.0,
+            l3: 0.0,
+            filter: None,
+            diffs: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured error-window length.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if the error window is full.
+    pub fn value(&self) -> Option<f64> {
+        if self.diffs.len() == self.period {
+            self.filter
+        } else {
+            None
+        }
+    }
+
+    /// Median of the normalised errors currently in the window. Returns `0.0`
+    /// when every error is equal (e.g. during a constant warmup), which makes
+    /// the filter maximally fast.
+    fn adaptive_gamma(&self) -> f64 {
+        let mut hh = f64::MIN;
+        let mut ll = f64::MAX;
+        for &d in &self.diffs {
+            if d > hh {
+                hh = d;
+            }
+            if d < ll {
+                ll = d;
+            }
+        }
+        let range = hh - ll;
+        if range <= 0.0 {
+            return 0.0;
+        }
+        let mut norm: Vec<f64> = self.diffs.iter().map(|&d| (d - ll) / range).collect();
+        // `total_cmp` never panics — under pathological (e.g. overflowing) fuzz
+        // inputs a normalised error can be non-finite; a total order keeps the
+        // sort sound where `partial_cmp` would return `None`.
+        norm.sort_by(f64::total_cmp);
+        let mid = norm.len() / 2;
+        if norm.len() % 2 == 1 {
+            norm[mid]
+        } else {
+            f64::midpoint(norm[mid - 1], norm[mid])
+        }
+    }
+}
+
+impl Indicator for AdaptiveLaguerreFilter {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, price: f64) -> Option<f64> {
+        if !price.is_finite() {
+            return self.value();
+        }
+        // Absolute tracking error against the previous filter (0 on the first
+        // bar, where there is no prior filter value).
+        let diff = self.filter.map_or(0.0, |f| (price - f).abs());
+        if self.diffs.len() == self.period {
+            self.diffs.pop_front();
+        }
+        self.diffs.push_back(diff);
+
+        let gamma = self.adaptive_gamma();
+        let alpha = 1.0 - gamma;
+
+        let l0 = alpha * price + gamma * self.l0;
+        let l1 = -gamma * l0 + self.l0 + gamma * self.l1;
+        let l2 = -gamma * l1 + self.l1 + gamma * self.l2;
+        let l3 = -gamma * l2 + self.l2 + gamma * self.l3;
+        self.l0 = l0;
+        self.l1 = l1;
+        self.l2 = l2;
+        self.l3 = l3;
+
+        let filter = (l0 + 2.0 * l1 + 2.0 * l2 + l3) / 6.0;
+        self.filter = Some(filter);
+        self.value()
+    }
+
+    fn reset(&mut self) {
+        self.l0 = 0.0;
+        self.l1 = 0.0;
+        self.l2 = 0.0;
+        self.l3 = 0.0;
+        self.filter = None;
+        self.diffs.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.diffs.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "AdaptiveLaguerre"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    /// Independent reference: replays the exact recurrence from scratch.
+    fn naive(prices: &[f64], period: usize) -> Vec<Option<f64>> {
+        let (mut l0, mut l1, mut l2, mut l3) = (0.0_f64, 0.0_f64, 0.0_f64, 0.0_f64);
+        let mut filter: Option<f64> = None;
+        let mut diffs: Vec<f64> = Vec::new();
+        let mut out = Vec::with_capacity(prices.len());
+        for &price in prices {
+            let diff = filter.map_or(0.0, |f: f64| (price - f).abs());
+            diffs.push(diff);
+            if diffs.len() > period {
+                diffs.remove(0);
+            }
+            let hh = diffs.iter().copied().fold(f64::MIN, f64::max);
+            let ll = diffs.iter().copied().fold(f64::MAX, f64::min);
+            let range = hh - ll;
+            let gamma = if range <= 0.0 {
+                0.0
+            } else {
+                let mut norm: Vec<f64> = diffs.iter().map(|&d| (d - ll) / range).collect();
+                norm.sort_by(|a, b| a.partial_cmp(b).unwrap());
+                let mid = norm.len() / 2;
+                if norm.len() % 2 == 1 {
+                    norm[mid]
+                } else {
+                    f64::midpoint(norm[mid - 1], norm[mid])
+                }
+            };
+            let alpha = 1.0 - gamma;
+            let n0 = alpha * price + gamma * l0;
+            let n1 = -gamma * n0 + l0 + gamma * l1;
+            let n2 = -gamma * n1 + l1 + gamma * l2;
+            let n3 = -gamma * n2 + l2 + gamma * l3;
+            l0 = n0;
+            l1 = n1;
+            l2 = n2;
+            l3 = n3;
+            let f = (n0 + 2.0 * n1 + 2.0 * n2 + n3) / 6.0;
+            filter = Some(f);
+            out.push(if diffs.len() == period { Some(f) } else { None });
+        }
+        out
+    }
+
+    #[test]
+    fn new_rejects_zero_period() {
+        assert!(matches!(
+            AdaptiveLaguerreFilter::new(0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    /// Cover the const accessor `period` and the Indicator-impl `warmup_period`
+    /// + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let alf = AdaptiveLaguerreFilter::new(13).unwrap();
+        assert_eq!(alf.period(), 13);
+        assert_eq!(alf.warmup_period(), 13);
+        assert_eq!(alf.name(), "AdaptiveLaguerre");
+    }
+
+    #[test]
+    fn warmup_returns_none_until_window_full() {
+        let mut alf = AdaptiveLaguerreFilter::new(3).unwrap();
+        assert_eq!(alf.update(10.0), None);
+        assert_eq!(alf.update(11.0), None);
+        assert!(alf.update(12.0).is_some());
+    }
+
+    #[test]
+    fn constant_series_converges_to_constant() {
+        // Errors are all zero -> gamma 0 -> the 4-stage delay line fills with
+        // the constant and the filter settles on it.
+        let mut alf = AdaptiveLaguerreFilter::new(5).unwrap();
+        let out = alf.batch(&[42.0_f64; 40]);
+        let last = out.iter().rev().flatten().next().unwrap();
+        assert_relative_eq!(*last, 42.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn converged_output_stays_within_price_range() {
+        // Once the Laguerre cascade has filled (it cold-starts from zero, so the
+        // first few post-warmup values ramp up toward price), the filter is a
+        // convex blend of recent prices and must stay inside the data range.
+        let prices: Vec<f64> = (0..120)
+            .map(|i| 50.0 + (f64::from(i) * 0.4).sin() * 10.0)
+            .collect();
+        let lo = prices.iter().copied().fold(f64::MAX, f64::min);
+        let hi = prices.iter().copied().fold(f64::MIN, f64::max);
+        let period = 8;
+        let mut alf = AdaptiveLaguerreFilter::new(period).unwrap();
+        for (i, v) in alf.batch(&prices).into_iter().enumerate() {
+            // Skip the cold-start transient (a few multiples of the window).
+            if i < 4 * period {
+                continue;
+            }
+            let v = v.expect("filter is ready well past warmup");
+            assert!(
+                v >= lo - 1e-6 && v <= hi + 1e-6,
+                "filter out of range at {i}"
+            );
+        }
+    }
+
+    #[test]
+    fn matches_naive_recurrence() {
+        let prices: Vec<f64> = (0..80)
+            .map(|i| 100.0 + (f64::from(i) * 0.5).sin() * 8.0 + f64::from(i) * 0.1)
+            .collect();
+        let mut alf = AdaptiveLaguerreFilter::new(10).unwrap();
+        let got = alf.batch(&prices);
+        let want = naive(&prices, 10);
+        for (i, (g, w)) in got.iter().zip(want.iter()).enumerate() {
+            assert_eq!(g.is_some(), w.is_some(), "readiness mismatch at {i}");
+            if let (Some(a), Some(b)) = (g, w) {
+                assert_relative_eq!(*a, *b, epsilon = 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut alf = AdaptiveLaguerreFilter::new(5).unwrap();
+        alf.batch(&(1..=40).map(f64::from).collect::<Vec<_>>());
+        assert!(alf.is_ready());
+        alf.reset();
+        assert!(!alf.is_ready());
+        assert_eq!(alf.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=50).map(|i| f64::from(i) * 0.7).collect();
+        let mut a = AdaptiveLaguerreFilter::new(7).unwrap();
+        let mut b = AdaptiveLaguerreFilter::new(7).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut alf = AdaptiveLaguerreFilter::new(3).unwrap();
+        alf.update(10.0);
+        alf.update(11.0);
+        let ready = alf.update(12.0).expect("ready after three inputs");
+        assert_eq!(alf.update(f64::NAN), Some(ready));
+        assert_eq!(alf.update(f64::INFINITY), Some(ready));
+    }
+}

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

@@ -0,0 +1,168 @@
+//! Advance/Decline Line — cumulative net advancing-minus-declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Line (A/D Line) — the running cumulative sum of net advancing
+/// issues across a universe.
+///
+/// On each [`CrossSection`] tick the net breadth is `advancers - decliners`:
+/// the number of symbols with a positive price change minus the number with a
+/// negative change (unchanged symbols are ignored). The line accumulates this
+/// net value over time, so a rising line means advancers have persistently
+/// outnumbered decliners — broad participation — while a falling line warns that
+/// a rally is being carried by fewer and fewer names (a breadth divergence when
+/// the index itself is still rising).
+///
+/// `Input = CrossSection`, `Output = f64`. The line is defined from the very
+/// first tick, so `warmup_period == 1` and the indicator is ready after one
+/// update.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdvanceDecline, CrossSection, Indicator, Member};
+///
+/// let mut ad = AdvanceDecline::new();
+/// // 3 advancers, 1 decliner -> net +2.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(0.5, 10.0, false, false),
+///         Member::new(2.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(ad.update(tick), Some(2.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdvanceDecline {
+    line: f64,
+    has_emitted: bool,
+}
+
+impl AdvanceDecline {
+    /// Construct a new Advance/Decline Line indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            line: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for AdvanceDecline {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancers() as f64 - section.decliners() as f64;
+        self.line += net;
+        self.has_emitted = true;
+        Some(self.line)
+    }
+
+    fn reset(&mut self) {
+        self.line = 0.0;
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdvanceDecline"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    /// Build a cross-section with `up` advancers, `down` decliners and `flat`
+    /// unchanged symbols.
+    fn section(up: usize, down: usize, flat: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        for _ in 0..flat {
+            members.push(Member::new(0.0, 10.0, false, false));
+        }
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ad = AdvanceDecline::new();
+        assert_eq!(ad.name(), "AdvanceDecline");
+        assert_eq!(ad.warmup_period(), 1);
+        assert!(!ad.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_net_breadth() {
+        let mut ad = AdvanceDecline::new();
+        assert_eq!(ad.update(section(3, 1, 0)), Some(2.0));
+        assert!(ad.is_ready());
+    }
+
+    #[test]
+    fn line_accumulates_across_ticks() {
+        let mut ad = AdvanceDecline::new();
+        assert_eq!(ad.update(section(3, 1, 0)), Some(2.0)); // +2 -> 2
+        assert_eq!(ad.update(section(1, 4, 0)), Some(-1.0)); // -3 -> -1
+        assert_eq!(ad.update(section(2, 0, 0)), Some(1.0)); // +2 -> 1
+    }
+
+    #[test]
+    fn unchanged_symbols_are_ignored() {
+        let mut ad = AdvanceDecline::new();
+        // 2 up, 2 down, 5 unchanged -> net 0, line stays flat.
+        assert_eq!(ad.update(section(2, 2, 5)), Some(0.0));
+        assert_eq!(ad.update(section(2, 2, 5)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ad = AdvanceDecline::new();
+        ad.update(section(5, 0, 0));
+        assert!(ad.is_ready());
+        ad.reset();
+        assert!(!ad.is_ready());
+        // Line restarts from zero, not from the pre-reset value.
+        assert_eq!(ad.update(section(1, 0, 0)), Some(1.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![
+            section(3, 1, 2),
+            section(1, 4, 0),
+            section(2, 2, 1),
+            section(5, 0, 3),
+        ];
+        let mut a = AdvanceDecline::new();
+        let mut b = AdvanceDecline::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,151 @@
+//! Advance/Decline Ratio — advancing issues divided by declining issues.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Advance/Decline Ratio (ADR) — the number of advancing symbols divided by the
+/// number of declining symbols across a universe.
+///
+/// On each [`CrossSection`] tick the ratio is `advancers / decliners`: a reading
+/// above one means advancing issues outnumber declining ones (broad strength),
+/// while a reading below one signals broad weakness. Because it is a ratio rather
+/// than a difference, the ADR is comparable across universes of different sizes.
+///
+/// When a tick has no declining symbols the denominator is floored to one, so the
+/// ratio degrades gracefully to the advancer count instead of dividing by zero.
+///
+/// `Input = CrossSection`, `Output = f64`. The ratio is defined from the first
+/// tick, so `warmup_period == 1` and the indicator is ready after one update.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{AdvanceDeclineRatio, CrossSection, Indicator, Member};
+///
+/// let mut adr = AdvanceDeclineRatio::new();
+/// // 3 advancers, 1 decliner -> ratio 3.0.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 10.0, false, false),
+///         Member::new(0.5, 10.0, false, false),
+///         Member::new(2.0, 10.0, false, false),
+///         Member::new(-1.0, 10.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(adr.update(tick), Some(3.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AdvanceDeclineRatio {
+    has_emitted: bool,
+}
+
+impl AdvanceDeclineRatio {
+    /// Construct a new Advance/Decline Ratio indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AdvanceDeclineRatio {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let advancers = section.advancers() as f64;
+        let decliners = section.decliners().max(1) as f64;
+        self.has_emitted = true;
+        Some(advancers / decliners)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AdvanceDeclineRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        // A non-empty unchanged member guarantees a valid universe when both
+        // counts are zero.
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.name(), "AdvanceDeclineRatio");
+        assert_eq!(adr.warmup_period(), 1);
+        assert!(!adr.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_ratio() {
+        let mut adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.update(section(3, 1)), Some(3.0));
+        assert!(adr.is_ready());
+    }
+
+    #[test]
+    fn zero_decliners_floors_denominator() {
+        let mut adr = AdvanceDeclineRatio::new();
+        // 4 advancers, 0 decliners -> 4 / max(0, 1) = 4.0.
+        assert_eq!(adr.update(section(4, 0)), Some(4.0));
+    }
+
+    #[test]
+    fn no_advancers_yields_zero() {
+        let mut adr = AdvanceDeclineRatio::new();
+        assert_eq!(adr.update(section(0, 5)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adr = AdvanceDeclineRatio::new();
+        adr.update(section(3, 1));
+        assert!(adr.is_ready());
+        adr.reset();
+        assert!(!adr.is_ready());
+        assert_eq!(adr.update(section(2, 1)), Some(2.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(3, 1), section(4, 0), section(0, 5), section(2, 2)];
+        let mut a = AdvanceDeclineRatio::new();
+        let mut b = AdvanceDeclineRatio::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -91,7 +91,7 @@ impl Adx {
     }
 }
 
-fn directional_movement(prev: &Candle, current: &Candle) -> (f64, f64) {
+pub(crate) fn directional_movement(prev: &Candle, current: &Candle) -> (f64, f64) {
     let up = current.high - prev.high;
     let down = prev.low - current.low;
     let plus_dm = if up > down && up > 0.0 { up } else { 0.0 };

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

@@ -0,0 +1,239 @@
+//! Amihud Illiquidity — average price impact per unit traded value.
+
+use std::collections::VecDeque;
+
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+use crate::{Error, Result};
+
+/// Amihud Illiquidity — the average absolute log return per unit of traded
+/// value over the last `period` trades (Amihud, 2002).
+///
+/// ```text
+/// rₜ      = ln(priceₜ / priceₜ₋₁)
+/// ILLIQₜ  = |rₜ| / (priceₜ · sizeₜ)        (return per dollar of volume)
+/// Amihud  = mean of ILLIQ over the last `period` trades
+/// ```
+///
+/// Amihud's measure captures how much the price moves for a given amount of
+/// traded value: a **high** reading means small volume already shifts the price
+/// a lot (an illiquid, easily-moved market), a **low** reading means it takes
+/// large volume to move the price (a deep, liquid market). It is the workhorse
+/// cross-sectional liquidity proxy in market-microstructure research.
+///
+/// `Input = Trade`. Trades with zero size carry no traded value and are skipped
+/// (the ratio is undefined); the last value is returned and state is untouched.
+/// The first valid trade only seeds the reference price.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Side, Trade, AmihudIlliquidity};
+///
+/// let mut amihud = AmihudIlliquidity::new(20).unwrap();
+/// assert_eq!(amihud.update(Trade::new(100.0, 5.0, Side::Buy, 0).unwrap()), None);
+/// ```
+#[derive(Debug, Clone)]
+pub struct AmihudIlliquidity {
+    period: usize,
+    prev_price: Option<f64>,
+    window: VecDeque<f64>,
+    sum: f64,
+    last: Option<f64>,
+}
+
+impl AmihudIlliquidity {
+    /// Construct a new Amihud Illiquidity over the given trade window.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            prev_price: None,
+            window: VecDeque::with_capacity(period),
+            sum: 0.0,
+            last: None,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for AmihudIlliquidity {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        // A zero-size trade has no traded value: the ratio is undefined, so the
+        // trade is skipped without touching the reference price.
+        if trade.size == 0.0 {
+            return self.last;
+        }
+        let Some(prev) = self.prev_price else {
+            self.prev_price = Some(trade.price);
+            return None;
+        };
+        self.prev_price = Some(trade.price);
+        // `prev` and `trade.price` are both finite and strictly positive
+        // (enforced by `Trade::new`), so the log return is well-defined and the
+        // traded value is strictly positive.
+        let ret = (trade.price / prev).ln().abs();
+        let illiq = ret / (trade.price * trade.size);
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("window is non-empty");
+            self.sum -= old;
+        }
+        self.window.push_back(illiq);
+        self.sum += illiq;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let value = self.sum / self.period as f64;
+        self.last = Some(value);
+        Some(value)
+    }
+
+    fn reset(&mut self) {
+        self.prev_price = None;
+        self.window.clear();
+        self.sum = 0.0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "AmihudIlliquidity"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn trade(price: f64, size: f64) -> Trade {
+        Trade::new(price, size, Side::Buy, 0).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(AmihudIlliquidity::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let a = AmihudIlliquidity::new(20).unwrap();
+        assert_eq!(a.period(), 20);
+        assert_eq!(a.warmup_period(), 21);
+        assert_eq!(a.name(), "AmihudIlliquidity");
+        assert!(!a.is_ready());
+    }
+
+    #[test]
+    fn known_value() {
+        // period 1. Seed at 100, then 101 with size 10:
+        // |ln(101/100)| / (101 * 10).
+        let mut a = AmihudIlliquidity::new(1).unwrap();
+        assert_eq!(a.update(trade(100.0, 10.0)), None);
+        let out = a.update(trade(101.0, 10.0)).unwrap();
+        let expected = (101.0_f64 / 100.0).ln().abs() / (101.0 * 10.0);
+        assert_relative_eq!(out, expected, epsilon = 1e-15);
+    }
+
+    #[test]
+    fn higher_for_thinner_volume() {
+        // Same price move on smaller volume => larger illiquidity reading.
+        let thin = {
+            let mut a = AmihudIlliquidity::new(1).unwrap();
+            a.update(trade(100.0, 1.0));
+            a.update(trade(101.0, 1.0)).unwrap()
+        };
+        let thick = {
+            let mut a = AmihudIlliquidity::new(1).unwrap();
+            a.update(trade(100.0, 1000.0));
+            a.update(trade(101.0, 1000.0)).unwrap()
+        };
+        assert!(thin > thick, "thin {thin} should exceed thick {thick}");
+    }
+
+    #[test]
+    fn flat_price_is_zero() {
+        let mut a = AmihudIlliquidity::new(5).unwrap();
+        for v in a.batch(&[trade(100.0, 3.0); 20]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-15);
+        }
+    }
+
+    #[test]
+    fn skips_zero_size_trades() {
+        let mut a = AmihudIlliquidity::new(1).unwrap();
+        a.update(trade(100.0, 10.0));
+        let baseline = a.update(trade(101.0, 10.0)).unwrap();
+        // A zero-size trade is ignored; the previous reference price is kept.
+        assert_eq!(a.update(trade(200.0, 0.0)), Some(baseline));
+        // The next real trade still references price 101, not 200.
+        let mut control = a.clone();
+        let after = a.update(trade(102.0, 10.0)).unwrap();
+        assert_eq!(control.update(trade(102.0, 10.0)).unwrap(), after);
+    }
+
+    #[test]
+    fn output_is_non_negative() {
+        let mut a = AmihudIlliquidity::new(10).unwrap();
+        let trades: Vec<Trade> = (0..100)
+            .map(|i| {
+                trade(
+                    100.0 + (f64::from(i) * 0.3).sin() * 5.0,
+                    1.0 + f64::from(i % 7),
+                )
+            })
+            .collect();
+        for v in a.batch(&trades).into_iter().flatten() {
+            assert!(v >= 0.0, "illiquidity must be non-negative, got {v}");
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut a = AmihudIlliquidity::new(5).unwrap();
+        for i in 0..20 {
+            a.update(trade(100.0 + f64::from(i), 2.0));
+        }
+        assert!(a.is_ready());
+        a.reset();
+        assert!(!a.is_ready());
+        assert_eq!(a.update(trade(100.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..80)
+            .map(|i| {
+                trade(
+                    100.0 + (f64::from(i) * 0.25).sin() * 4.0,
+                    1.0 + f64::from(i % 5),
+                )
+            })
+            .collect();
+        let batch = AmihudIlliquidity::new(14).unwrap().batch(&trades);
+        let mut b = AmihudIlliquidity::new(14).unwrap();
+        let streamed: Vec<_> = trades.iter().map(|t| b.update(*t)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -28,9 +28,17 @@ use crate::traits::Indicator;
 #[derive(Debug, Clone)]
 pub struct Atr {
     period: usize,
+    /// `period - 1` as `f64`, precomputed for the Wilder smoothing step.
+    n_minus_1: f64,
+    /// `1 / period`, precomputed so the per-tick smoothing multiplies instead of
+    /// divides.
+    inv_period: f64,
     prev_close: Option<f64>,
     seed_buf: Vec<f64>,
-    avg: Option<f64>,
+    /// Smoothed ATR, valid once `seeded` is set. Bare `f64` + flag rather than
+    /// `Option<f64>` so the hot recurrence avoids an enum-tag read per tick.
+    avg: f64,
+    seeded: bool,
 }
 
 impl Atr {
@@ -45,9 +53,12 @@ impl Atr {
         }
         Ok(Self {
             period,
+            n_minus_1: (period - 1) as f64,
+            inv_period: 1.0 / period as f64,
             prev_close: None,
             seed_buf: Vec::with_capacity(period),
-            avg: None,
+            avg: 0.0,
+            seeded: false,
         })
     }
 
@@ -58,7 +69,11 @@ impl Atr {
 
     /// Current value if available.
     pub const fn value(&self) -> Option<f64> {
-        self.avg
+        if self.seeded {
+            Some(self.avg)
+        } else {
+            None
+        }
     }
 }
 
@@ -70,17 +85,18 @@ impl Indicator for Atr {
         let tr = candle.true_range(self.prev_close);
         self.prev_close = Some(candle.close);
 
-        if let Some(avg) = self.avg {
-            let n = self.period as f64;
-            let new_avg = avg.mul_add(n - 1.0, tr) / n;
-            self.avg = Some(new_avg);
+        if self.seeded {
+            // Wilder smoothing with the reciprocal hoisted out of the hot path.
+            let new_avg = self.avg.mul_add(self.n_minus_1, tr) * self.inv_period;
+            self.avg = new_avg;
             return Some(new_avg);
         }
 
         self.seed_buf.push(tr);
         if self.seed_buf.len() == self.period {
             let seed = self.seed_buf.iter().copied().sum::<f64>() / self.period as f64;
-            self.avg = Some(seed);
+            self.avg = seed;
+            self.seeded = true;
             return Some(seed);
         }
         None
@@ -89,7 +105,8 @@ impl Indicator for Atr {
     fn reset(&mut self) {
         self.prev_close = None;
         self.seed_buf.clear();
-        self.avg = None;
+        self.avg = 0.0;
+        self.seeded = false;
     }
 
     fn warmup_period(&self) -> usize {
@@ -97,7 +114,7 @@ impl Indicator for Atr {
     }
 
     fn is_ready(&self) -> bool {
-        self.avg.is_some()
+        self.seeded
     }
 
     fn name(&self) -> &'static str {

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

@@ -0,0 +1,176 @@
+//! Auto-Fibonacci — retracement of the most significant recent swing leg.
+
+use crate::indicators::pattern_swing::{SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// How many recent pivots to consider when picking the dominant leg.
+const PIVOT_HISTORY: usize = 6;
+
+/// The seven canonical retracement ratios, in ascending order.
+const RATIOS: [f64; 7] = [0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0];
+
+/// Auto-Fibonacci retracement levels for the dominant recent swing leg.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct AutoFibOutput {
+    /// 0.0% — the dominant leg's end.
+    pub level_0: f64,
+    /// 23.6% retracement.
+    pub level_236: f64,
+    /// 38.2% retracement.
+    pub level_382: f64,
+    /// 50% retracement.
+    pub level_500: f64,
+    /// 61.8% retracement.
+    pub level_618: f64,
+    /// 78.6% retracement.
+    pub level_786: f64,
+    /// 100% — the dominant leg's start.
+    pub level_1000: f64,
+}
+
+/// Auto-Fibonacci (`AutoFib`).
+///
+/// Like [`crate::indicators::FibRetracement`], but instead of always using the
+/// immediate last leg it scans the last six confirmed pivots and anchors the
+/// retracement on the single largest-magnitude leg among them — the dominant
+/// swing the market is most likely respecting.
+///
+/// Parameter-free; construction is infallible. Returns `None` until two pivots
+/// have confirmed.
+///
+/// See `crates/wickra-core/src/indicators/auto_fib.rs`.
+#[derive(Debug, Clone)]
+pub struct AutoFib {
+    swing: SwingTracker,
+}
+
+impl AutoFib {
+    /// Construct a new Auto-Fibonacci tracker.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, PIVOT_HISTORY),
+        }
+    }
+
+    fn levels(&self) -> Option<AutoFibOutput> {
+        let dominant = self.swing.pivots().windows(2).max_by(|x, y| {
+            (x[0].price - x[1].price)
+                .abs()
+                .total_cmp(&(y[0].price - y[1].price).abs())
+        })?;
+        let (start, end) = (dominant[0].price, dominant[1].price);
+        let level = |r: f64| end + r * (start - end);
+        Some(AutoFibOutput {
+            level_0: level(RATIOS[0]),
+            level_236: level(RATIOS[1]),
+            level_382: level(RATIOS[2]),
+            level_500: level(RATIOS[3]),
+            level_618: level(RATIOS[4]),
+            level_786: level(RATIOS[5]),
+            level_1000: level(RATIOS[6]),
+        })
+    }
+}
+
+impl Default for AutoFib {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for AutoFib {
+    type Input = Candle;
+    type Output = AutoFibOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<AutoFibOutput> {
+        self.swing.update(candle);
+        self.levels()
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.swing.pivots().len() >= 2
+    }
+
+    fn name(&self) -> &'static str {
+        "AutoFib"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = AutoFib::new();
+        assert_eq!(indicator.name(), "AutoFib");
+        assert_eq!(indicator.warmup_period(), 2);
+        assert!(!indicator.is_ready());
+        assert!(!AutoFib::default().is_ready());
+    }
+
+    #[test]
+    fn no_output_before_two_pivots() {
+        let mut indicator = AutoFib::new();
+        let outputs: Vec<_> = candles_for_pivots(&[120.0])
+            .into_iter()
+            .map(|c| indicator.update(c))
+            .collect();
+        assert!(outputs.iter().all(Option::is_none));
+    }
+
+    #[test]
+    fn anchors_on_the_largest_leg() {
+        // Pivots: 130 -> 120 (small, 10) -> 220 (large, 100) -> 200 (small, 20).
+        // The dominant leg is 120 -> 220; its retracement spans [120, 220].
+        let mut indicator = AutoFib::new();
+        let mut last = None;
+        for candle in candles_for_pivots(&[130.0, 120.0, 220.0, 200.0]) {
+            last = indicator.update(candle);
+        }
+        let v = last.unwrap();
+        assert!(indicator.is_ready());
+        // Largest leg 120 -> 220: 0% on 220 (end), 100% on 120 (start).
+        assert_relative_eq!(v.level_0, 220.0);
+        assert_relative_eq!(v.level_1000, 120.0);
+        assert_relative_eq!(v.level_500, 170.0);
+        assert_relative_eq!(v.level_618, 220.0 + 0.618 * (120.0 - 220.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = AutoFib::new();
+        for candle in candles_for_pivots(&[200.0, 100.0]) {
+            let _ = indicator.update(candle);
+        }
+        assert!(indicator.is_ready());
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert!(indicator.update(c).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[130.0, 120.0, 220.0, 200.0]);
+        let mut a = AutoFib::new();
+        let mut b = AutoFib::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,231 @@
+//! Average Daily Range (ADR) — the mean high-minus-low range of the last `period`
+//! completed calendar-day sessions.
+
+use std::collections::VecDeque;
+
+use crate::calendar::civil_from_timestamp;
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Average Daily Range over the last `period` completed sessions.
+///
+/// The indicator tracks the running high / low of the current session (the
+/// wall-clock day of [`Candle::timestamp`](crate::Candle) shifted by
+/// `utc_offset_minutes`). When a new day begins, the just-finished session's
+/// range (`high - low`) joins a rolling window of the last `period` completed
+/// days, and the reported value is their mean. The current, still-forming day is
+/// excluded until it closes. No value is produced until the first session
+/// completes.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, AverageDailyRange};
+///
+/// let hour = 3_600_000;
+/// let mut adr = AverageDailyRange::new(2, 0).unwrap();
+/// // Day 1 range 10 (high 110, low 100) — still forming, so None.
+/// assert!(adr.update(Candle::new(105.0, 110.0, 100.0, 108.0, 1.0, 0).unwrap()).is_none());
+/// // First bar of day 2 closes day 1: ADR = 10.
+/// let v = adr.update(Candle::new(108.0, 112.0, 106.0, 109.0, 1.0, 24 * hour).unwrap()).unwrap();
+/// assert!((v - 10.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct AverageDailyRange {
+    period: usize,
+    utc_offset_minutes: i32,
+    day_key: Option<(i64, u32, u32)>,
+    cur_high: f64,
+    cur_low: f64,
+    completed: VecDeque<f64>,
+    sum: f64,
+}
+
+impl AverageDailyRange {
+    /// Construct an ADR indicator over `period` completed days.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize, utc_offset_minutes: i32) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            utc_offset_minutes,
+            day_key: None,
+            cur_high: f64::NEG_INFINITY,
+            cur_low: f64::INFINITY,
+            completed: VecDeque::with_capacity(period),
+            sum: 0.0,
+        })
+    }
+
+    /// Configured `(period, utc_offset_minutes)`.
+    pub const fn params(&self) -> (usize, i32) {
+        (self.period, self.utc_offset_minutes)
+    }
+
+    /// Most recent ADR if at least one session has completed.
+    pub fn value(&self) -> Option<f64> {
+        if self.completed.is_empty() {
+            None
+        } else {
+            Some(self.sum / self.completed.len() as f64)
+        }
+    }
+}
+
+impl Indicator for AverageDailyRange {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let civil = civil_from_timestamp(candle.timestamp, self.utc_offset_minutes);
+        let key = (civil.year, civil.month, civil.day);
+        match self.day_key {
+            Some(prev) if prev == key => {
+                if candle.high > self.cur_high {
+                    self.cur_high = candle.high;
+                }
+                if candle.low < self.cur_low {
+                    self.cur_low = candle.low;
+                }
+            }
+            Some(_) => {
+                let range = self.cur_high - self.cur_low;
+                self.completed.push_back(range);
+                self.sum += range;
+                if self.completed.len() > self.period {
+                    self.sum -= self
+                        .completed
+                        .pop_front()
+                        .expect("len > period implies a front element");
+                }
+                self.day_key = Some(key);
+                self.cur_high = candle.high;
+                self.cur_low = candle.low;
+            }
+            None => {
+                self.day_key = Some(key);
+                self.cur_high = candle.high;
+                self.cur_low = candle.low;
+            }
+        }
+        self.value()
+    }
+
+    fn reset(&mut self) {
+        self.day_key = None;
+        self.cur_high = f64::NEG_INFINITY;
+        self.cur_low = f64::INFINITY;
+        self.completed.clear();
+        self.sum = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        !self.completed.is_empty()
+    }
+
+    fn name(&self) -> &'static str {
+        "AverageDailyRange"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    const HOUR: i64 = 3_600_000;
+    const DAY: i64 = 24 * HOUR;
+
+    fn c(high: f64, low: f64, ts: i64) -> Candle {
+        let mid = f64::midpoint(high, low);
+        Candle::new(mid, high, low, mid, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(
+            AverageDailyRange::new(0, 0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    #[test]
+    fn metadata_and_accessors() {
+        let adr = AverageDailyRange::new(5, -60).unwrap();
+        assert_eq!(adr.params(), (5, -60));
+        assert_eq!(adr.name(), "AverageDailyRange");
+        assert_eq!(adr.warmup_period(), 5);
+        assert!(!adr.is_ready());
+        assert!(adr.value().is_none());
+    }
+
+    #[test]
+    fn averages_completed_day_ranges() {
+        let mut adr = AverageDailyRange::new(3, 0).unwrap();
+        // Day 1: range 10.
+        assert!(adr.update(c(110.0, 100.0, 0)).is_none());
+        assert!(adr.update(c(108.0, 104.0, HOUR)).is_none());
+        // Day 2 opens -> day 1 (range 10) completes.
+        let v = adr.update(c(120.0, 110.0, DAY)).unwrap();
+        assert_relative_eq!(v, 10.0);
+        assert!(adr.is_ready());
+        // Day 3 opens -> day 2 (range 10) completes: mean of [10, 10] = 10.
+        let v = adr.update(c(130.0, 100.0, 2 * DAY)).unwrap();
+        assert_relative_eq!(v, 10.0);
+    }
+
+    #[test]
+    fn rolls_off_oldest_day_beyond_period() {
+        let mut adr = AverageDailyRange::new(2, 0).unwrap();
+        adr.update(c(110.0, 100.0, 0)); // day 1 range 10
+        let v = adr.update(c(125.0, 110.0, DAY)).unwrap(); // close day 1 -> [10]
+        assert_relative_eq!(v, 10.0);
+        // Close day 2 (range 125-110=15) -> window [10, 15], mean 12.5.
+        let v = adr.update(c(130.0, 110.0, 2 * DAY)).unwrap();
+        assert_relative_eq!(v, 12.5);
+        // Close day 3 (range 130-110=20) -> window [15, 20], oldest (10) rolled off.
+        let v = adr.update(c(140.0, 138.0, 3 * DAY)).unwrap();
+        assert_relative_eq!(v, 17.5);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut adr = AverageDailyRange::new(2, 0).unwrap();
+        adr.update(c(110.0, 100.0, 0));
+        adr.update(c(120.0, 110.0, DAY));
+        adr.reset();
+        assert!(!adr.is_ready());
+        assert!(adr.value().is_none());
+        assert!(adr.update(c(50.0, 40.0, 2 * DAY)).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..60)
+            .map(|i| {
+                c(
+                    110.0 + f64::from(i % 5),
+                    100.0 - f64::from(i % 3),
+                    i64::from(i) * 6 * HOUR,
+                )
+            })
+            .collect();
+        let mut a = AverageDailyRange::new(4, 0).unwrap();
+        let mut b = AverageDailyRange::new(4, 0).unwrap();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,92 @@
+//! Average Price (AVGPRICE).
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Average Price (`AVGPRICE`) — the bar's `(open + high + low + close) / 4`.
+///
+/// A per-bar price aggregate that, unlike [`TypicalPrice`](crate::TypicalPrice)
+/// and [`WeightedClose`](crate::WeightedClose), folds in the open as well as the
+/// high, low and close. As a stateless transform it emits a value from the very
+/// first candle.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, AvgPrice};
+///
+/// let mut indicator = AvgPrice::new();
+/// let mut last = None;
+/// for i in 0..80 {
+///     let base = 100.0 + f64::from(i);
+///     let candle =
+///         Candle::new(base, base + 2.0, base - 2.0, base + 1.0, 10.0, i64::from(i)).unwrap();
+///     last = indicator.update(candle);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct AvgPrice {
+    has_emitted: bool,
+}
+
+impl AvgPrice {
+    /// Construct a new Average Price transform.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for AvgPrice {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        Some(candle.avg_price())
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "AVGPRICE"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn averages_the_four_prices() {
+        // (open + high + low + close) / 4 = (10 + 14 + 6 + 12) / 4 = 10.5.
+        let candle = Candle::new(10.0, 14.0, 6.0, 12.0, 1.0, 0).unwrap();
+        let mut ap = AvgPrice::new();
+        assert!(!ap.is_ready());
+        assert_relative_eq!(ap.update(candle).unwrap(), 10.5, epsilon = 1e-12);
+        assert!(ap.is_ready());
+    }
+
+    #[test]
+    fn accessors_and_reset() {
+        let mut ap = AvgPrice::new();
+        assert_eq!(ap.name(), "AVGPRICE");
+        assert_eq!(ap.warmup_period(), 1);
+        let candle = Candle::new(10.0, 14.0, 6.0, 12.0, 1.0, 0).unwrap();
+        let _ = ap.update(candle);
+        assert!(ap.is_ready());
+        ap.reset();
+        assert!(!ap.is_ready());
+    }
+}

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

@@ -0,0 +1,154 @@
+//! Bat harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Bat — a 5-point (X-A-B-C-D) harmonic pattern with a shallow B and a deep
+/// `0.886` D completion:
+///
+/// ```text
+/// AB / XA ∈ [0.382, 0.50]
+/// BC / AB ∈ [0.382, 0.886]
+/// CD / BC ∈ [1.618, 2.618]
+/// AD / XA ∈ [0.84, 0.93]   (≈ 0.886 — the defining D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/bat.rs`.
+#[derive(Debug, Clone)]
+pub struct Bat {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Bat {
+    /// Construct a new Bat detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Bat {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Bat {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let cd = (p.d - p.c).abs();
+        let ad = (p.d - p.a).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.382, 0.50),
+            (bc / ab, 0.382, 0.886),
+            (cd / bc, 1.618, 2.618),
+            (ad / xa, 0.84, 0.93),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Bat"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Bat::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Bat::new();
+        assert_eq!(indicator.name(), "Bat");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Bat::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_bat_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 122.0, 137.0, 104.56]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_bat_is_minus_one() {
+        let out = run(&[150.0, 110.0, 128.0, 113.0, 145.44]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Bat::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 122.0, 137.0, 104.56]);
+        let mut a = Bat::new();
+        let mut b = Bat::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,247 @@
+//! Beta-neutral spread: the rolling OLS regression residual of two series.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// The beta-neutral spread between two assets — the residual of a rolling
+/// ordinary-least-squares regression of `a` on `b`.
+///
+/// Each `update` takes one `(a, b)` price pair. Over the trailing window of
+/// `period` pairs the indicator fits the hedge ratio `β` (and intercept `α`) by
+/// OLS and reports the **current** residual:
+///
+/// ```text
+/// β = cov(a, b) / var(b)        α = ā − β · b̄
+/// spread = a_now − (α + β · b_now)
+/// ```
+///
+/// Subtracting `β · b` removes `a`'s exposure to `b`, so the spread is market-
+/// (beta-)neutral: it is what is left after the common factor is hedged out.
+/// Positive means `a` is rich relative to its hedge, negative means cheap — the
+/// raw signal a pairs trade fades. Where [`crate::PairSpreadZScore`] standardises
+/// this residual into a z-score and [`crate::Cointegration`] bundles it with an
+/// ADF test, this indicator returns the residual itself, in price units.
+///
+/// If `b` is flat over the window (`var(b) = 0`) there is no defined slope; the
+/// indicator falls back to `β = 0`, so the spread becomes `a_now − ā`.
+///
+/// Each `update` is `O(1)`: four running sums (`Σa`, `Σb`, `Σb²`, `Σab`) are
+/// maintained as the window slides.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BetaNeutralSpread, Indicator};
+///
+/// let mut s = BetaNeutralSpread::new(20).unwrap();
+/// let mut last = None;
+/// for t in 0..40 {
+///     let b = 100.0 + f64::from(t);
+///     // a = 2·b + 5 exactly ⇒ the regression explains a fully ⇒ spread ≈ 0.
+///     last = s.update((2.0 * b + 5.0, b));
+/// }
+/// assert!(last.unwrap().abs() < 1e-6);
+/// ```
+#[derive(Debug, Clone)]
+pub struct BetaNeutralSpread {
+    period: usize,
+    window: VecDeque<(f64, f64)>,
+    sum_a: f64,
+    sum_b: f64,
+    sum_bb: f64,
+    sum_ab: f64,
+}
+
+impl BetaNeutralSpread {
+    /// Construct a new beta-neutral spread.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` — a regression slope
+    /// needs at least two points.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "beta-neutral spread needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+            sum_a: 0.0,
+            sum_b: 0.0,
+            sum_bb: 0.0,
+            sum_ab: 0.0,
+        })
+    }
+
+    /// Configured look-back window.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for BetaNeutralSpread {
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        let (a, b) = input;
+        if self.window.len() == self.period {
+            let (oa, ob) = self.window.pop_front().expect("non-empty");
+            self.sum_a -= oa;
+            self.sum_b -= ob;
+            self.sum_bb -= ob * ob;
+            self.sum_ab -= oa * ob;
+        }
+        self.window.push_back((a, b));
+        self.sum_a += a;
+        self.sum_b += b;
+        self.sum_bb += b * b;
+        self.sum_ab += a * b;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let n = self.period as f64;
+        let mean_a = self.sum_a / n;
+        let mean_b = self.sum_b / n;
+        let var_b = (self.sum_bb / n - mean_b * mean_b).max(0.0);
+        let (beta, intercept) = if var_b == 0.0 {
+            (0.0, mean_a)
+        } else {
+            let cov = self.sum_ab / n - mean_a * mean_b;
+            let slope = cov / var_b;
+            (slope, mean_a - slope * mean_b)
+        };
+        Some(a - (intercept + beta * b))
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum_a = 0.0;
+        self.sum_b = 0.0;
+        self.sum_bb = 0.0;
+        self.sum_ab = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "BetaNeutralSpread"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(BetaNeutralSpread::new(1).is_err());
+        assert!(BetaNeutralSpread::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let s = BetaNeutralSpread::new(20).unwrap();
+        assert_eq!(s.period(), 20);
+        assert_eq!(s.warmup_period(), 20);
+        assert_eq!(s.name(), "BetaNeutralSpread");
+        assert!(!s.is_ready());
+    }
+
+    #[test]
+    fn warmup_returns_none() {
+        let mut s = BetaNeutralSpread::new(3).unwrap();
+        assert_eq!(s.update((1.0, 1.0)), None);
+        assert_eq!(s.update((2.0, 2.0)), None);
+        assert!(s.update((3.0, 3.0)).is_some());
+        assert!(s.is_ready());
+    }
+
+    #[test]
+    fn perfect_linear_relationship_has_zero_spread() {
+        let pairs: Vec<(f64, f64)> = (0..40)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                (2.0 * b + 5.0, b)
+            })
+            .collect();
+        let last = BetaNeutralSpread::new(20)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-6);
+    }
+
+    #[test]
+    fn dislocation_produces_nonzero_spread() {
+        // a tracks 2·b, then the last bar jumps up ⇒ positive residual.
+        let mut pairs: Vec<(f64, f64)> = (0..19)
+            .map(|t| {
+                let b = 100.0 + f64::from(t);
+                (2.0 * b + 5.0, b)
+            })
+            .collect();
+        pairs.push((2.0 * 119.0 + 5.0 + 10.0, 119.0));
+        let last = BetaNeutralSpread::new(20)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last > 1.0, "spread {last}");
+    }
+
+    #[test]
+    fn flat_b_falls_back_to_demeaned_a() {
+        // b constant ⇒ β = 0 ⇒ spread = a − mean(a). Last window of a = 0..9,
+        // mean = 4.5, last a = 9 ⇒ spread = 4.5.
+        let pairs: Vec<(f64, f64)> = (0..10).map(|t| (f64::from(t), 7.0)).collect();
+        let last = BetaNeutralSpread::new(10)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 4.5, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut s = BetaNeutralSpread::new(4).unwrap();
+        s.batch(&[(1.0, 2.0), (2.0, 4.0), (3.0, 5.0), (4.0, 9.0), (5.0, 2.0)]);
+        assert!(s.is_ready());
+        s.reset();
+        assert!(!s.is_ready());
+        assert_eq!(s.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|t| {
+                let b = 30.0 + 0.7 * f64::from(t);
+                (1.8 * b + 2.0 + (f64::from(t) * 0.4).sin(), b)
+            })
+            .collect();
+        let batch = BetaNeutralSpread::new(20).unwrap().batch(&pairs);
+        let mut s = BetaNeutralSpread::new(20).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| s.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,281 @@
+//! Realized Bipower Variation — a jump-robust quadratic-variation estimator.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Realized Bipower Variation — the sum of *adjacent* absolute log-return
+/// products over the trailing `period` returns, scaled to estimate integrated
+/// variance.
+///
+/// ```text
+/// r_t = ln(price_t / price_{t−1})
+/// BV  = (π / 2) · Σ |r_t| · |r_{t−1}|   over the window
+/// ```
+///
+/// Bipower variation (Barndorff-Nielsen & Shephard 2004) estimates the same
+/// integrated variance as [`RealizedVolatility`](crate::RealizedVolatility)'s
+/// `Σ r²`, but by multiplying *neighbouring* absolute returns rather than
+/// squaring a single one. A price jump inflates exactly one return; because that
+/// return appears in a product with its (ordinary) neighbour rather than squared,
+/// its contribution stays bounded — so `BV` is **robust to jumps** while realized
+/// variance is not. The constant `π / 2 = μ₁⁻²` (with `μ₁ = E|Z| = √(2/π)` for a
+/// standard normal) debiases the product of two half-normal magnitudes back to a
+/// variance scale.
+///
+/// The output is on the **variance** scale (the jump-robust counterpart of
+/// realized *variance*, not volatility); take its square root for a volatility,
+/// and compare `RV − BV` to isolate the jump contribution. A window of `period`
+/// returns contributes `period − 1` adjacent products; each `update` is O(1) via
+/// a running sum.
+///
+/// Non-finite and non-positive prices are ignored (the log return would be
+/// undefined): the tick is dropped, state is left untouched, and the last value
+/// is returned.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BipowerVariation, Indicator};
+///
+/// let mut indicator = BipowerVariation::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + (f64::from(i) * 0.3).sin() * 5.0);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct BipowerVariation {
+    period: usize,
+    prev_price: Option<f64>,
+    /// Rolling window of the last `period` log returns.
+    window: VecDeque<f64>,
+    /// Running sum of adjacent absolute-return products inside the window.
+    sum_adjacent: f64,
+    last: Option<f64>,
+}
+
+impl BipowerVariation {
+    /// Construct a new bipower-variation indicator.
+    ///
+    /// `period` is the number of log returns in the rolling window; the estimate
+    /// uses the `period − 1` adjacent products between them.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`, or
+    /// [`Error::InvalidPeriod`] if `period == 1` (an adjacent product needs at
+    /// least two returns).
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "bipower variation period must be >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            prev_price: None,
+            window: VecDeque::with_capacity(period),
+            sum_adjacent: 0.0,
+            last: None,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+/// `μ₁⁻² = π / 2`, the debiasing constant for a product of half-normal returns.
+const MU1_INV_SQ: f64 = std::f64::consts::FRAC_PI_2;
+
+impl Indicator for BipowerVariation {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        // Non-finite / non-positive prices are skipped: `ln(input / prev)` is
+        // undefined, so the tick must not enter the return window.
+        if !input.is_finite() || input <= 0.0 {
+            return self.last;
+        }
+        let Some(prev) = self.prev_price else {
+            self.prev_price = Some(input);
+            return None;
+        };
+        self.prev_price = Some(input);
+        // `prev` came from `self.prev_price`, gated by the guard above, so it is
+        // finite and positive — the log return is always well-defined.
+        let r = (input / prev).ln();
+        // The incoming return forms a product with the current last return.
+        if let Some(&back) = self.window.back() {
+            self.sum_adjacent += back.abs() * r.abs();
+        }
+        self.window.push_back(r);
+        if self.window.len() > self.period {
+            let first = self.window.pop_front().expect("window is non-empty");
+            // The product between the dropped return and the new front leaves.
+            let second = *self.window.front().expect("window still has >= 1 element");
+            self.sum_adjacent -= first.abs() * second.abs();
+        }
+        if self.window.len() < self.period {
+            return None;
+        }
+        // Products are non-negative; the rolling subtraction can leave a tiny
+        // negative residual when returns are ~0, so clamp before scaling.
+        let bv = MU1_INV_SQ * self.sum_adjacent.max(0.0);
+        self.last = Some(bv);
+        Some(bv)
+    }
+
+    fn reset(&mut self) {
+        self.prev_price = None;
+        self.window.clear();
+        self.sum_adjacent = 0.0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // The first log return needs a previous price, then the window fills.
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "BipowerVariation"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BipowerVariation::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn rejects_period_one() {
+        assert!(matches!(
+            BipowerVariation::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bv = BipowerVariation::new(20).unwrap();
+        assert_eq!(bv.period(), 20);
+        assert_eq!(bv.warmup_period(), 21);
+        assert_eq!(bv.name(), "BipowerVariation");
+        assert!(!bv.is_ready());
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let out = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        for v in out.iter().take(5) {
+            assert!(v.is_none());
+        }
+        assert!(out[5].is_some());
+    }
+
+    #[test]
+    fn known_value() {
+        // period = 2: one adjacent product. r1 = ln(1.1), r2 = ln(0.9).
+        // BV = (π/2)·|r1|·|r2|.
+        let mut bv = BipowerVariation::new(2).unwrap();
+        let out = bv.batch(&[100.0, 110.0, 99.0]);
+        assert!(out[1].is_none());
+        let r1 = (110.0_f64 / 100.0).ln();
+        let r2 = (99.0_f64 / 110.0).ln();
+        let expected = std::f64::consts::FRAC_PI_2 * r1.abs() * r2.abs();
+        assert_relative_eq!(out[2].unwrap(), expected, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rolling_window_drops_oldest_product() {
+        // period = 2, four prices -> two emissions, each a single product.
+        let mut bv = BipowerVariation::new(2).unwrap();
+        let out = bv.batch(&[100.0, 110.0, 99.0, 105.0]);
+        let r2 = (99.0_f64 / 110.0).ln();
+        let r3 = (105.0_f64 / 99.0).ln();
+        let expected = std::f64::consts::FRAC_PI_2 * r2.abs() * r3.abs();
+        assert_relative_eq!(out[3].unwrap(), expected, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn constant_series_yields_zero() {
+        let mut bv = BipowerVariation::new(10).unwrap();
+        for v in bv.batch(&[100.0; 40]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn output_is_non_negative() {
+        let mut bv = BipowerVariation::new(20).unwrap();
+        let prices: Vec<f64> = (1..=200)
+            .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 12.0)
+            .collect();
+        for v in bv.batch(&prices).into_iter().flatten() {
+            assert!(v >= 0.0, "bipower variation must be non-negative, got {v}");
+        }
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let out = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let last = *out.last().unwrap();
+        assert!(last.is_some());
+        assert_eq!(bv.update(f64::NAN), last);
+        assert_eq!(bv.update(f64::INFINITY), last);
+    }
+
+    #[test]
+    fn skips_non_positive_prices() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        let warmup = bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let baseline = warmup.last().copied().flatten().expect("warmed up");
+        assert_eq!(bv.update(-5.0), Some(baseline));
+        assert_eq!(bv.update(0.0), Some(baseline));
+        // State untouched: a clone advanced by the same real tick agrees.
+        let mut control = bv.clone();
+        let after = bv.update(21.0).expect("ready");
+        assert_eq!(control.update(21.0).expect("ready"), after);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bv = BipowerVariation::new(5).unwrap();
+        bv.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        assert!(bv.is_ready());
+        bv.reset();
+        assert!(!bv.is_ready());
+        assert_eq!(bv.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=120)
+            .map(|i| 100.0 + (f64::from(i) * 0.25).sin() * 9.0)
+            .collect();
+        let batch = BipowerVariation::new(20).unwrap().batch(&prices);
+        let mut b = BipowerVariation::new(20).unwrap();
+        let streamed: Vec<_> = prices.iter().map(|p| b.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,193 @@
+//! Body Size Percent — candle body as a fraction of its range.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Body Size Percent — the absolute body as a fraction of the bar's range.
+///
+/// ```text
+/// BodySizePct = |close − open| / (high − low)
+/// ```
+///
+/// The result lives in `[0, 1]`: `1` is a full-bodied marubozu (the bar opened
+/// at one extreme and closed at the other, no wicks), `0` a doji (open equals
+/// close, the bar is all wick). It is the *unsigned* magnitude companion to
+/// [`BalanceOfPower`](crate::BalanceOfPower) — where `BoP` keeps the direction,
+/// this keeps only the conviction, which is exactly what candlestick body /
+/// range filters key on. A zero-range bar carries no information and yields `0`.
+///
+/// This is a stateless per-bar transform: every candle produces one value.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, BodySizePct};
+///
+/// let mut indicator = BodySizePct::new();
+/// // body |12 - 10| = 2, range 14 - 10 = 4 -> 0.5.
+/// let c = Candle::new(10.0, 14.0, 10.0, 12.0, 10.0, 0).unwrap();
+/// assert!((indicator.update(c).unwrap() - 0.5).abs() < 1e-12);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct BodySizePct {
+    has_emitted: bool,
+}
+
+impl BodySizePct {
+    /// Construct a new Body Size Percent transform.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for BodySizePct {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let range = candle.high - candle.low;
+        let out = if range == 0.0 {
+            // A zero-range bar has no body proportion to speak of.
+            0.0
+        } else {
+            (candle.close - candle.open).abs() / range
+        };
+        Some(out)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "BodySizePct"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn candle(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn reference_value() {
+        // |12 - 10| / (14 - 10) = 0.5.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 14.0, 10.0, 12.0, 0)).unwrap(),
+            0.5,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn marubozu_is_one() {
+        // open == low, close == high, no wicks -> full body -> 1.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(9.0, 11.0, 9.0, 11.0, 0)).unwrap(),
+            1.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn doji_is_zero() {
+        // open == close with a real range -> body 0.
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 12.0, 8.0, 10.0, 0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn unsigned_regardless_of_direction() {
+        // A red bar with the same body magnitude reads identically to a green one.
+        let mut bsp = BodySizePct::new();
+        let green = bsp.update(candle(10.0, 14.0, 10.0, 12.0, 0)).unwrap();
+        let mut bsp2 = BodySizePct::new();
+        let red = bsp2.update(candle(12.0, 14.0, 10.0, 10.0, 0)).unwrap();
+        assert_relative_eq!(green, red, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn zero_range_bar_yields_zero() {
+        let mut bsp = BodySizePct::new();
+        assert_relative_eq!(
+            bsp.update(candle(10.0, 10.0, 10.0, 10.0, 0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn stays_within_unit_range() {
+        let candles: Vec<Candle> = (0..100)
+            .map(|i| {
+                let mid = 100.0 + (f64::from(i) * 0.2).sin() * 8.0;
+                let close = mid + (f64::from(i) * 0.5).cos() * 2.0;
+                candle(mid, mid + 3.0, mid - 3.0, close, i64::from(i))
+            })
+            .collect();
+        let mut bsp = BodySizePct::new();
+        for v in bsp.batch(&candles).into_iter().flatten() {
+            assert!((0.0..=1.0).contains(&v), "BodySizePct {v} outside [0, 1]");
+        }
+    }
+
+    #[test]
+    fn name_metadata() {
+        let bsp = BodySizePct::new();
+        assert_eq!(bsp.name(), "BodySizePct");
+    }
+
+    #[test]
+    fn emits_from_first_candle() {
+        let mut bsp = BodySizePct::new();
+        assert_eq!(bsp.warmup_period(), 1);
+        assert!(!bsp.is_ready());
+        assert!(bsp.update(candle(10.0, 11.0, 9.0, 10.0, 0)).is_some());
+        assert!(bsp.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bsp = BodySizePct::new();
+        bsp.update(candle(10.0, 11.0, 9.0, 10.0, 0));
+        assert!(bsp.is_ready());
+        bsp.reset();
+        assert!(!bsp.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + f64::from(i);
+                candle(base, base + 2.0, base - 2.0, base + 1.0, i64::from(i))
+            })
+            .collect();
+        let mut a = BodySizePct::new();
+        let mut b = BodySizePct::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -1,7 +1,5 @@
 //! Bollinger Bands.
 
-use std::collections::VecDeque;
-
 use crate::error::{Error, Result};
 use crate::traits::Indicator;
 
@@ -49,7 +47,13 @@ pub struct BollingerOutput {
 pub struct BollingerBands {
     period: usize,
     multiplier: f64,
-    window: VecDeque<f64>,
+    /// Fixed-capacity ring buffer of the last `period` finite inputs. A flat
+    /// `Box<[f64]>` with a manual write cursor beats `VecDeque` on this hot path.
+    buf: Box<[f64]>,
+    /// Index of the next slot to write — also the oldest element once full.
+    head: usize,
+    /// Number of slots filled, saturating at `period`.
+    count: usize,
     sum: f64,
     sum_sq: f64,
     /// Number of finite updates since the running sums were last reseeded
@@ -80,7 +84,9 @@ impl BollingerBands {
         Ok(Self {
             period,
             multiplier,
-            window: VecDeque::with_capacity(period),
+            buf: vec![0.0; period].into_boxed_slice(),
+            head: 0,
+            count: 0,
             sum: 0.0,
             sum_sq: 0.0,
             updates_since_recompute: 0,
@@ -103,7 +109,7 @@ impl BollingerBands {
     }
 
     fn current(&self) -> Option<BollingerOutput> {
-        if self.window.len() != self.period {
+        if self.count != self.period {
             return None;
         }
         let n = self.period as f64;
@@ -129,25 +135,38 @@ impl Indicator for BollingerBands {
         if !input.is_finite() {
             return self.current();
         }
-        if self.window.len() == self.period {
-            let old = self.window.pop_front().expect("non-empty");
+        if self.count == self.period {
+            let old = self.buf[self.head];
             self.sum -= old;
             self.sum_sq -= old * old;
+            self.buf[self.head] = input;
+            self.sum += input;
+            self.sum_sq += input * input;
+        } else {
+            self.buf[self.head] = input;
+            self.sum += input;
+            self.sum_sq += input * input;
+            self.count += 1;
+        }
+        self.head += 1;
+        if self.head == self.period {
+            self.head = 0;
         }
-        self.window.push_back(input);
-        self.sum += input;
-        self.sum_sq += input * input;
         self.updates_since_recompute += 1;
         if self.updates_since_recompute >= RECOMPUTE_EVERY * self.period {
-            self.sum = self.window.iter().copied().sum();
-            self.sum_sq = self.window.iter().copied().map(|x| x * x).sum();
+            // Reseed in chronological order (oldest at `head`) to keep the running
+            // sums bit-equivalent to a fresh from-scratch pass on stable inputs.
+            let chronological = self.buf[self.head..].iter().chain(&self.buf[..self.head]);
+            self.sum = chronological.clone().copied().sum();
+            self.sum_sq = chronological.map(|&x| x * x).sum();
             self.updates_since_recompute = 0;
         }
         self.current()
     }
 
     fn reset(&mut self) {
-        self.window.clear();
+        self.head = 0;
+        self.count = 0;
         self.sum = 0.0;
         self.sum_sq = 0.0;
         self.updates_since_recompute = 0;
@@ -158,7 +177,7 @@ impl Indicator for BollingerBands {
     }
 
     fn is_ready(&self) -> bool {
-        self.window.len() == self.period
+        self.count == self.period
     }
 
     fn name(&self) -> &'static str {
@@ -171,6 +190,7 @@ mod tests {
     use super::*;
     use crate::traits::BatchExt;
     use approx::assert_relative_eq;
+    use std::collections::VecDeque;
 
     fn naive(prices: &[f64], period: usize, mult: f64) -> BollingerOutput {
         assert!(

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

@@ -0,0 +1,256 @@
+//! Bomar Bands — adaptive percentage bands that contain a target fraction of
+//! recent price.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::indicators::rolling_quantile::quantile_sorted;
+use crate::traits::Indicator;
+
+/// Bomar Bands output.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct BomarBandsOutput {
+    /// Upper band: `middle + |middle| · p`.
+    pub upper: f64,
+    /// Middle line: the simple moving average over the window.
+    pub middle: f64,
+    /// Lower band: `middle − |middle| · p`.
+    pub lower: f64,
+}
+
+/// Bomar Bands: percentage bands whose width adapts so that a fixed `coverage`
+/// fraction of recent closes falls inside them.
+///
+/// The Bomar Bands predate Bollinger Bands; John Bollinger cites them as an
+/// inspiration — percentage bands around a moving average, with the percentage
+/// tuned so a fixed share (classically ~85%) of price stayed within. Wickra
+/// realises that idea deterministically: the half-width is the `coverage`
+/// quantile of the relative deviations from the midline, so by construction
+/// `coverage` of the window's closes lie inside the bands.
+///
+/// ```text
+/// middle = SMA(close, period)
+/// dev_i  = | close_i / middle − 1 |          // relative distance from midline
+/// p      = coverage-quantile of { dev_i }     // type-7 interpolation
+/// upper  = middle + |middle| · p
+/// lower  = middle − |middle| · p
+/// ```
+///
+/// Unlike the fixed-percentage [`MaEnvelope`](crate::MaEnvelope), the offset
+/// here is data-driven: the bands widen in turbulent regimes and tighten in
+/// quiet ones without a volatility input. Unlike Bollinger Bands, the width is
+/// an order statistic of the actual deviations rather than a multiple of the
+/// standard deviation, so it is unaffected by the shape of the tails beyond the
+/// `coverage` rank. When the midline is zero the relative deviation is
+/// undefined and the bands collapse onto the midline.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BomarBands, Indicator};
+///
+/// let mut indicator = BomarBands::new(20, 0.85).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update(100.0 + f64::from(i % 7));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct BomarBands {
+    period: usize,
+    coverage: f64,
+    window: VecDeque<f64>,
+    scratch: Vec<f64>,
+}
+
+impl BomarBands {
+    /// Construct new Bomar Bands.
+    ///
+    /// `coverage` is the target fraction of closes to contain, in `(0.0, 1.0]`.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`, or
+    /// [`Error::InvalidParameter`] if `coverage` is not a finite value in
+    /// `(0.0, 1.0]`.
+    pub fn new(period: usize, coverage: f64) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if !coverage.is_finite() || coverage <= 0.0 || coverage > 1.0 {
+            return Err(Error::InvalidParameter {
+                message: "bomar bands coverage must be a finite value in (0.0, 1.0]",
+            });
+        }
+        Ok(Self {
+            period,
+            coverage,
+            window: VecDeque::with_capacity(period),
+            scratch: Vec::with_capacity(period),
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Configured coverage fraction.
+    pub const fn coverage(&self) -> f64 {
+        self.coverage
+    }
+}
+
+impl Indicator for BomarBands {
+    type Input = f64;
+    type Output = BomarBandsOutput;
+
+    fn update(&mut self, value: f64) -> Option<BomarBandsOutput> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(value);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let sum: f64 = self.window.iter().sum();
+        let middle = sum / (self.period as f64);
+        let denom = middle.abs();
+
+        self.scratch.clear();
+        for &v in &self.window {
+            let dev = if denom == 0.0 {
+                0.0
+            } else {
+                ((v - middle) / denom).abs()
+            };
+            self.scratch.push(dev);
+        }
+        self.scratch.sort_by(f64::total_cmp);
+        let p = quantile_sorted(&self.scratch, self.coverage);
+        let offset = denom * p;
+
+        Some(BomarBandsOutput {
+            upper: middle + offset,
+            middle,
+            lower: middle - offset,
+        })
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.scratch.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "BomarBands"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BomarBands::new(0, 0.85), Err(Error::PeriodZero)));
+        assert!(BomarBands::new(1, 0.85).is_ok());
+    }
+
+    #[test]
+    fn rejects_out_of_range_coverage() {
+        assert!(matches!(
+            BomarBands::new(20, 0.0),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, 1.1),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, -0.5),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            BomarBands::new(20, f64::NAN),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bb = BomarBands::new(20, 0.85).unwrap();
+        assert_eq!(bb.period(), 20);
+        assert_relative_eq!(bb.coverage(), 0.85, epsilon = 1e-12);
+        assert_eq!(bb.warmup_period(), 20);
+        assert_eq!(bb.name(), "BomarBands");
+        assert!(!bb.is_ready());
+    }
+
+    #[test]
+    fn warms_up_then_emits() {
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        assert!(bb.update(100.0).is_none());
+        assert!(bb.update(102.0).is_none());
+        assert!(bb.update(98.0).is_none());
+        assert!(bb.update(104.0).is_some());
+        assert!(bb.is_ready());
+    }
+
+    #[test]
+    fn known_bands() {
+        // mean=101; |dev| = {1,1,3,3}/101; coverage 0.85 quantile -> 3/101.
+        // offset = 101 * 3/101 = 3 -> upper 104, lower 98.
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        let out = bb.batch(&[100.0, 102.0, 98.0, 104.0]);
+        let last = out[3].unwrap();
+        assert_relative_eq!(last.middle, 101.0, epsilon = 1e-9);
+        assert_relative_eq!(last.upper, 104.0, epsilon = 1e-9);
+        assert_relative_eq!(last.lower, 98.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn zero_midline_collapses_bands() {
+        // Window mean exactly zero -> relative deviation undefined -> collapse.
+        let mut bb = BomarBands::new(2, 0.85).unwrap();
+        let out = bb.batch(&[3.0, -3.0]);
+        let last = out[1].unwrap();
+        assert_relative_eq!(last.middle, 0.0, epsilon = 1e-12);
+        assert_relative_eq!(last.upper, 0.0, epsilon = 1e-12);
+        assert_relative_eq!(last.lower, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rolling_window_evicts_oldest() {
+        // Eight values through a period-4 window: only the last four survive,
+        // reproducing the `known_bands` window.
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        let out = bb.batch(&[50.0, 50.0, 50.0, 50.0, 100.0, 102.0, 98.0, 104.0]);
+        let last = out[7].unwrap();
+        assert_relative_eq!(last.middle, 101.0, epsilon = 1e-9);
+        assert_relative_eq!(last.upper, 104.0, epsilon = 1e-9);
+        assert_relative_eq!(last.lower, 98.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bb = BomarBands::new(4, 0.85).unwrap();
+        for v in [100.0, 102.0, 98.0, 104.0] {
+            bb.update(v);
+        }
+        assert!(bb.is_ready());
+        bb.reset();
+        assert!(!bb.is_ready());
+        assert!(bb.update(100.0).is_none());
+    }
+}

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

@@ -0,0 +1,165 @@
+//! Breadth Thrust (Zweig) — a moving average of the advancing-issues share.
+
+use crate::cross_section::CrossSection;
+use crate::error::Result;
+use crate::traits::Indicator;
+use crate::Sma;
+
+/// Breadth Thrust (Zweig) — a simple moving average of the advancing-issues
+/// share, `advancers / (advancers + decliners)`.
+///
+/// Martin Zweig's breadth thrust smooths the fraction of participating issues
+/// that are advancing over a short window (the classic period is 10). A "thrust"
+/// fires when this average climbs from below ~0.40 (oversold, washed-out breadth)
+/// to above ~0.615 within about ten sessions — historically a rare, reliable
+/// signal that a powerful new advance has begun with broad participation.
+///
+/// Each tick's share floors the participating count to one, so a tick with no
+/// advancing or declining issues contributes a defined `0.0` instead of dividing
+/// by zero. The reading is `None` until `period` ticks have been seen.
+///
+/// `Input = CrossSection`, `Output = f64` (a share in `0..=1`),
+/// `warmup_period == period`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BreadthThrust, CrossSection, Indicator, Member};
+///
+/// let mut bt = BreadthThrust::new(2).unwrap();
+/// let up = CrossSection::new(vec![Member::new(1.0, 1.0, false, false)], 0).unwrap();
+/// assert_eq!(bt.update(up.clone()), None); // warming up
+/// assert_eq!(bt.update(up), Some(1.0)); // both ticks 100% advancing
+/// ```
+#[derive(Debug, Clone)]
+pub struct BreadthThrust {
+    sma: Sma,
+}
+
+impl BreadthThrust {
+    /// Construct a new Breadth Thrust over the given window length.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`](crate::Error::PeriodZero) if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        Ok(Self {
+            sma: Sma::new(period)?,
+        })
+    }
+
+    /// Configured window length.
+    #[must_use]
+    pub const fn period(&self) -> usize {
+        self.sma.period()
+    }
+}
+
+impl Indicator for BreadthThrust {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let advancers = section.advancers();
+        let decliners = section.decliners();
+        let participating = (advancers + decliners).max(1) as f64;
+        let share = advancers as f64 / participating;
+        self.sma.update(share)
+    }
+
+    fn reset(&mut self) {
+        self.sma.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.sma.period()
+    }
+
+    fn is_ready(&self) -> bool {
+        self.sma.value().is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "BreadthThrust"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::error::Error;
+    use crate::traits::BatchExt;
+
+    fn section(up: usize, down: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..up {
+            members.push(Member::new(1.0, 10.0, false, false));
+        }
+        for _ in 0..down {
+            members.push(Member::new(-1.0, 10.0, false, false));
+        }
+        members.push(Member::new(0.0, 10.0, false, false));
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bt = BreadthThrust::new(10).unwrap();
+        assert_eq!(bt.name(), "BreadthThrust");
+        assert_eq!(bt.warmup_period(), 10);
+        assert_eq!(bt.period(), 10);
+        assert!(!bt.is_ready());
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(BreadthThrust::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn averages_the_advancing_share() {
+        let mut bt = BreadthThrust::new(2).unwrap();
+        // share = 8 / 10 = 0.8 ; window not full yet.
+        assert_eq!(bt.update(section(8, 2)), None);
+        // share = 6 / 10 = 0.6 ; SMA(2) = (0.8 + 0.6) / 2 = 0.7.
+        let value = bt.update(section(6, 4)).unwrap();
+        assert!((value - 0.7).abs() < 1e-9);
+        assert!(bt.is_ready());
+        // share = 5 / 10 = 0.5 ; SMA(2) = (0.6 + 0.5) / 2 = 0.55.
+        let value = bt.update(section(5, 5)).unwrap();
+        assert!((value - 0.55).abs() < 1e-9);
+    }
+
+    #[test]
+    fn empty_participation_floors_to_zero_share() {
+        let mut bt = BreadthThrust::new(1).unwrap();
+        // No advancers or decliners -> 0 / max(0, 1) = 0.0.
+        assert_eq!(bt.update(section(0, 0)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bt = BreadthThrust::new(2).unwrap();
+        bt.update(section(8, 2));
+        bt.update(section(6, 4));
+        assert!(bt.is_ready());
+        bt.reset();
+        assert!(!bt.is_ready());
+        assert_eq!(bt.update(section(8, 2)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![section(8, 2), section(6, 4), section(5, 5), section(0, 0)];
+        let mut a = BreadthThrust::new(2).unwrap();
+        let mut b = BreadthThrust::new(2).unwrap();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,147 @@
+//! Bullish Percent Index — share of a universe on a point-and-figure buy signal.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Bullish Percent Index (BPI) — the percentage of symbols in a universe that are
+/// currently on a point-and-figure buy signal.
+///
+/// On each [`CrossSection`] tick the value is `100 * on_buy_signal_count /
+/// universe size`, read from the per-symbol `on_buy_signal` flag (the caller
+/// evaluates each symbol's point-and-figure chart when it builds the tick). It is
+/// a bounded `0..=100` gauge of how many issues are in a confirmed uptrend.
+/// Readings above 70 are considered overbought (broad strength, but a crowded
+/// market) and below 30 oversold; reversals from those zones are classic BPI
+/// buy/sell triggers.
+///
+/// `Input = CrossSection`, `Output = f64` (a percentage in `0..=100`),
+/// `warmup_period == 1`. The universe is non-empty by construction, so the share
+/// is always defined.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BullishPercentIndex, CrossSection, Indicator, Member};
+///
+/// let mut bpi = BullishPercentIndex::new();
+/// // 2 of 4 symbols on a buy signal -> 50%.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::with_signals(1.0, 10.0, false, false, false, true),
+///         Member::with_signals(1.0, 10.0, false, false, false, true),
+///         Member::with_signals(-1.0, 10.0, false, false, false, false),
+///         Member::with_signals(-1.0, 10.0, false, false, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(bpi.update(tick), Some(50.0));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct BullishPercentIndex {
+    has_emitted: bool,
+}
+
+impl BullishPercentIndex {
+    /// Construct a new Bullish Percent Index indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for BullishPercentIndex {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let bullish = section.on_buy_signal_count() as f64;
+        let total = section.members.len() as f64;
+        self.has_emitted = true;
+        Some(100.0 * bullish / total)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "BullishPercentIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn tick(bullish: usize, bearish: usize) -> CrossSection {
+        let mut members = Vec::new();
+        for _ in 0..bullish {
+            members.push(Member::with_signals(1.0, 10.0, false, false, false, true));
+        }
+        for _ in 0..bearish {
+            members.push(Member::with_signals(-1.0, 10.0, false, false, false, false));
+        }
+        CrossSection::new(members, 0).unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.name(), "BullishPercentIndex");
+        assert_eq!(bpi.warmup_period(), 1);
+        assert!(!bpi.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_percentage() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(2, 2)), Some(50.0));
+        assert!(bpi.is_ready());
+    }
+
+    #[test]
+    fn all_bullish_is_one_hundred() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(5, 0)), Some(100.0));
+    }
+
+    #[test]
+    fn none_bullish_is_zero() {
+        let mut bpi = BullishPercentIndex::new();
+        assert_eq!(bpi.update(tick(0, 4)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut bpi = BullishPercentIndex::new();
+        bpi.update(tick(2, 2));
+        assert!(bpi.is_ready());
+        bpi.reset();
+        assert!(!bpi.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![tick(2, 2), tick(5, 0), tick(0, 4)];
+        let mut a = BullishPercentIndex::new();
+        let mut b = BullishPercentIndex::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,154 @@
+//! Butterfly harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Butterfly — a 5-point (X-A-B-C-D) harmonic pattern with a `0.786` B and an
+/// **extended** D that overshoots X:
+///
+/// ```text
+/// AB / XA ∈ [0.74, 0.84]   (≈ 0.786)
+/// BC / AB ∈ [0.382, 0.886]
+/// CD / BC ∈ [1.618, 2.618]
+/// AD / XA ∈ [1.27, 1.618]  (the defining extended D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/butterfly.rs`.
+#[derive(Debug, Clone)]
+pub struct Butterfly {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Butterfly {
+    /// Construct a new Butterfly detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Butterfly {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Butterfly {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let cd = (p.d - p.c).abs();
+        let ad = (p.d - p.a).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.74, 0.84),
+            (bc / ab, 0.382, 0.886),
+            (cd / bc, 1.618, 2.618),
+            (ad / xa, 1.27, 1.618),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Butterfly"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Butterfly::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Butterfly::new();
+        assert_eq!(indicator.name(), "Butterfly");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Butterfly::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_butterfly_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 108.6, 128.0, 79.8]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_butterfly_is_minus_one() {
+        let out = run(&[150.0, 110.0, 141.4, 121.4, 170.2]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Butterfly::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 108.6, 128.0, 79.8]);
+        let mut a = Butterfly::new();
+        let mut b = Butterfly::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,157 @@
+//! Close vs Open — the signed relative body of a bar.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Close vs Open — the bar's body as a signed fraction of its open price.
+///
+/// ```text
+/// CloseVsOpen = (close − open) / open
+/// ```
+///
+/// A scale-free, signed measure of how far price travelled from open to close:
+/// `+0.02` is a bar that closed 2% above its open (a green bar), `−0.02` the
+/// mirror. Unlike [`BalanceOfPower`](crate::BalanceOfPower) — which normalises
+/// the body by the bar *range* — this normalises by the *open price*, so it is
+/// directly comparable to a return and stays meaningful across instruments of
+/// different nominal price. A zero open carries no scale and yields `0`.
+///
+/// This is a stateless per-bar transform: every candle produces one value.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, CloseVsOpen};
+///
+/// let mut indicator = CloseVsOpen::new();
+/// // open 100, close 102 -> +0.02.
+/// let c = Candle::new(100.0, 103.0, 99.0, 102.0, 10.0, 0).unwrap();
+/// assert!((indicator.update(c).unwrap() - 0.02).abs() < 1e-12);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct CloseVsOpen {
+    has_emitted: bool,
+}
+
+impl CloseVsOpen {
+    /// Construct a new Close vs Open transform.
+    pub const fn new() -> Self {
+        Self { has_emitted: false }
+    }
+}
+
+impl Indicator for CloseVsOpen {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        let out = if candle.open == 0.0 {
+            // A zero open price carries no scale to normalise against.
+            0.0
+        } else {
+            (candle.close - candle.open) / candle.open
+        };
+        Some(out)
+    }
+
+    fn reset(&mut self) {
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "CloseVsOpen"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn candle(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
+        Candle::new(open, high, low, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn reference_value() {
+        // (102 - 100) / 100 = 0.02.
+        let mut cvo = CloseVsOpen::new();
+        assert_relative_eq!(
+            cvo.update(candle(100.0, 103.0, 99.0, 102.0, 0)).unwrap(),
+            0.02,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn negative_body_is_negative() {
+        let mut cvo = CloseVsOpen::new();
+        // close below open -> negative.
+        assert_relative_eq!(
+            cvo.update(candle(100.0, 101.0, 97.0, 98.0, 0)).unwrap(),
+            -0.02,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn zero_open_yields_zero() {
+        // Candle permits a zero open (only finiteness + OHLC ordering checked).
+        let mut cvo = CloseVsOpen::new();
+        assert_relative_eq!(
+            cvo.update(candle(0.0, 1.0, 0.0, 0.5, 0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn name_metadata() {
+        let cvo = CloseVsOpen::new();
+        assert_eq!(cvo.name(), "CloseVsOpen");
+    }
+
+    #[test]
+    fn emits_from_first_candle() {
+        let mut cvo = CloseVsOpen::new();
+        assert_eq!(cvo.warmup_period(), 1);
+        assert!(!cvo.is_ready());
+        assert!(cvo.update(candle(10.0, 11.0, 9.0, 10.0, 0)).is_some());
+        assert!(cvo.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut cvo = CloseVsOpen::new();
+        cvo.update(candle(10.0, 11.0, 9.0, 10.0, 0));
+        assert!(cvo.is_ready());
+        cvo.reset();
+        assert!(!cvo.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + f64::from(i);
+                candle(base, base + 2.0, base - 2.0, base + 1.0, i64::from(i))
+            })
+            .collect();
+        let mut a = CloseVsOpen::new();
+        let mut b = CloseVsOpen::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,154 @@
+//! Crab harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Crab — a 5-point (X-A-B-C-D) harmonic pattern with the deepest D completion
+/// of the family, an `1.618` extension of XA:
+///
+/// ```text
+/// AB / XA ∈ [0.382, 0.618]
+/// BC / AB ∈ [0.382, 0.886]
+/// CD / BC ∈ [2.24, 3.618]  (a very long terminal leg)
+/// AD / XA ∈ [1.55, 1.65]   (≈ 1.618 — the defining D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/crab.rs`.
+#[derive(Debug, Clone)]
+pub struct Crab {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Crab {
+    /// Construct a new Crab detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Crab {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Crab {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let cd = (p.d - p.c).abs();
+        let ad = (p.d - p.a).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.382, 0.618),
+            (bc / ab, 0.382, 0.886),
+            (cd / bc, 2.24, 3.618),
+            (ad / xa, 1.55, 1.65),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Crab"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Crab::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Crab::new();
+        assert_eq!(indicator.name(), "Crab");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Crab::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_crab_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 120.0, 137.5, 75.3]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_crab_is_minus_one() {
+        let out = run(&[150.0, 110.0, 130.0, 112.5, 174.7]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Crab::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 120.0, 137.5, 75.3]);
+        let mut a = Crab::new();
+        let mut b = Crab::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,163 @@
+//! Cumulative Volume Index — running total of volume-normalised net advancing volume.
+
+use crate::cross_section::CrossSection;
+use crate::traits::Indicator;
+
+/// Cumulative Volume Index (CVI) — the running total of *volume-normalised* net
+/// advancing volume across a universe.
+///
+/// On each [`CrossSection`] tick the increment is `(advancing volume - declining
+/// volume) / total volume`: the share of the tick's total volume that flowed,
+/// net, into advancing issues. The index accumulates this share over time. Where
+/// the raw [`AdVolumeLine`](crate::AdVolumeLine) sums *absolute* net volume — and
+/// so drifts with secular growth in trading activity — the CVI normalises each
+/// tick by its own total volume, so a one-share-net day in a thin market counts
+/// the same as in a heavy one. This keeps the index comparable across regimes of
+/// very different volume.
+///
+/// When a tick has zero total volume the net is necessarily zero too, so the
+/// increment is zero and the index is unchanged (the divisor is floored to the
+/// smallest positive `f64` purely to keep the division defined).
+///
+/// `Input = CrossSection`, `Output = f64`, `warmup_period == 1`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{CrossSection, CumulativeVolumeIndex, Indicator, Member};
+///
+/// let mut cvi = CumulativeVolumeIndex::new();
+/// // adv vol 150, dec vol 50, total 200 -> (150 - 50) / 200 = 0.5.
+/// let tick = CrossSection::new(
+///     vec![
+///         Member::new(1.0, 150.0, false, false),
+///         Member::new(-1.0, 50.0, false, false),
+///     ],
+///     0,
+/// )
+/// .unwrap();
+/// assert_eq!(cvi.update(tick), Some(0.5));
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct CumulativeVolumeIndex {
+    index: f64,
+    has_emitted: bool,
+}
+
+impl CumulativeVolumeIndex {
+    /// Construct a new Cumulative Volume Index indicator.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            index: 0.0,
+            has_emitted: false,
+        }
+    }
+}
+
+impl Indicator for CumulativeVolumeIndex {
+    type Input = CrossSection;
+    type Output = f64;
+
+    fn update(&mut self, section: CrossSection) -> Option<f64> {
+        let net = section.advancing_volume() - section.declining_volume();
+        let total = section.total_volume().max(f64::MIN_POSITIVE);
+        self.index += net / total;
+        self.has_emitted = true;
+        Some(self.index)
+    }
+
+    fn reset(&mut self) {
+        self.index = 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 {
+        "CumulativeVolumeIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::cross_section::Member;
+    use crate::traits::BatchExt;
+
+    fn tick(items: &[(f64, f64)]) -> CrossSection {
+        CrossSection::new(
+            items
+                .iter()
+                .map(|&(change, volume)| Member::new(change, volume, false, false))
+                .collect(),
+            0,
+        )
+        .unwrap()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let cvi = CumulativeVolumeIndex::new();
+        assert_eq!(cvi.name(), "CumulativeVolumeIndex");
+        assert_eq!(cvi.warmup_period(), 1);
+        assert!(!cvi.is_ready());
+    }
+
+    #[test]
+    fn first_tick_emits_normalised_net() {
+        let mut cvi = CumulativeVolumeIndex::new();
+        assert_eq!(cvi.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(0.5));
+        assert!(cvi.is_ready());
+    }
+
+    #[test]
+    fn index_accumulates_normalised_shares() {
+        let mut cvi = CumulativeVolumeIndex::new();
+        assert_eq!(cvi.update(tick(&[(1.0, 150.0), (-1.0, 50.0)])), Some(0.5));
+        // adv 60, dec 60, total 120 -> net 0 -> index unchanged.
+        assert_eq!(cvi.update(tick(&[(1.0, 60.0), (-1.0, 60.0)])), Some(0.5));
+    }
+
+    #[test]
+    fn zero_total_volume_leaves_index_unchanged() {
+        let mut cvi = CumulativeVolumeIndex::new();
+        cvi.update(tick(&[(1.0, 150.0), (-1.0, 50.0)]));
+        // A tick with no volume at all: net 0 / floored divisor -> 0 increment.
+        assert_eq!(cvi.update(tick(&[(0.0, 0.0)])), Some(0.5));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut cvi = CumulativeVolumeIndex::new();
+        cvi.update(tick(&[(1.0, 150.0), (-1.0, 50.0)]));
+        assert!(cvi.is_ready());
+        cvi.reset();
+        assert!(!cvi.is_ready());
+        assert_eq!(cvi.update(tick(&[(1.0, 100.0)])), Some(1.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let sections = vec![
+            tick(&[(1.0, 150.0), (-1.0, 50.0)]),
+            tick(&[(1.0, 60.0), (-1.0, 60.0)]),
+            tick(&[(0.0, 0.0)]),
+        ];
+        let mut a = CumulativeVolumeIndex::new();
+        let mut b = CumulativeVolumeIndex::new();
+        assert_eq!(
+            a.batch(&sections),
+            sections
+                .iter()
+                .map(|s| b.update(s.clone()))
+                .collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,176 @@
+//! Cup-and-Handle (and Inverse) continuation chart pattern.
+
+use crate::indicators::pattern_swing::{
+    approx_equal, SwingTracker, LEVEL_TOLERANCE, SWING_THRESHOLD,
+};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Cup-and-Handle / Inverse — a rounded base (the cup) followed by a shallow
+/// pullback (the handle) near the rim, then a breakout in the cup's direction.
+///
+/// Built on confirmed swing pivots ([`SWING_THRESHOLD`] = 5%) and read from the
+/// last four pivots:
+///
+/// ```text
+/// cup-and-handle (bullish, +1):  Rim(high) , Cup(low) , Rim(high) , Handle(low)
+///   the two rims match (±3%) ; the handle low sits ABOVE the cup low (a shallow
+///   pullback) and below the right rim
+///
+/// inverse (bearish, -1):         Rim(low) , Cap(high) , Rim(low) , Handle(high)
+///   the two rims match ; the handle high sits BELOW the cap high and above the
+///   right rim
+/// ```
+///
+/// The shallow handle (closer to the rim than the cup extreme) is what
+/// distinguishes a cup-and-handle from a plain double bottom/top. Output is
+/// `+1.0` / `-1.0` / `0.0`; never `None`.
+#[derive(Debug, Clone)]
+pub struct CupAndHandle {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl CupAndHandle {
+    /// Construct a new Cup-and-Handle detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 4),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for CupAndHandle {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for CupAndHandle {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 4 {
+            return Some(0.0);
+        }
+        let n = pivots.len();
+        let rim_left = pivots[n - 4];
+        let extreme = pivots[n - 3];
+        let rim_right = pivots[n - 2];
+        let handle = pivots[n - 1];
+        let rims_match = approx_equal(rim_left.price, rim_right.price, LEVEL_TOLERANCE);
+
+        if handle.direction < 0.0 {
+            // Bullish cup-and-handle: rims are highs, cup is the low between them,
+            // handle is a shallow low above the cup but below the right rim.
+            if rims_match && handle.price > extreme.price && handle.price < rim_right.price {
+                return Some(1.0);
+            }
+        } else if rims_match && handle.price < extreme.price && handle.price > rim_right.price {
+            // Inverse: rims are lows, cap is the high, handle a shallow high.
+            return Some(-1.0);
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // Four confirmed pivots; the earliest confirmation of the fourth is bar 5.
+        5
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "CupAndHandle"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = CupAndHandle::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = CupAndHandle::new();
+        assert_eq!(indicator.name(), "CupAndHandle");
+        assert_eq!(indicator.warmup_period(), 5);
+        assert!(!indicator.is_ready());
+        assert!(!CupAndHandle::default().is_ready());
+    }
+
+    #[test]
+    fn cup_and_handle_is_plus_one() {
+        // Rims 120/121, cup 90 (deep), handle 110 (shallow, above the cup).
+        let out = run(&[120.0, 90.0, 121.0, 110.0]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+    }
+
+    #[test]
+    fn inverse_cup_and_handle_is_minus_one() {
+        // Lead high then rims 100/101, cap 130, handle 110 (below cap, above rim).
+        let out = run(&[140.0, 100.0, 130.0, 101.0, 110.0]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn deep_handle_is_not_cup_and_handle() {
+        // Handle (85) below the cup low (90) → a double bottom, not cup-and-handle.
+        let out = run(&[120.0, 90.0, 121.0, 85.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn inverse_with_mismatched_rims_does_not_trigger() {
+        // Inverse shape (ends high) but the rims (100 / 90) diverge → enters the
+        // inverse branch yet reports no pattern.
+        let out = run(&[140.0, 100.0, 130.0, 90.0, 110.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = CupAndHandle::new();
+        for c in candles_for_pivots(&[120.0, 90.0, 121.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[120.0, 90.0, 121.0, 110.0]);
+        let mut a = CupAndHandle::new();
+        let mut b = CupAndHandle::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,152 @@
+//! Cypher harmonic pattern.
+
+use crate::indicators::pattern_swing::{ratios_in, xabcd, SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Cypher — a 5-point (X-A-B-C-D) harmonic pattern whose C leg is measured
+/// against XA (not AB) and whose D retraces the XC leg by `0.786`:
+///
+/// ```text
+/// AB / XA ∈ [0.382, 0.618]
+/// BC / XA ∈ [1.13, 1.414]  (C extends beyond A, measured on XA)
+/// CD / XC ∈ [0.74, 0.83]   (≈ 0.786 retracement of XC — the D completion)
+/// ```
+///
+/// Output is `+1.0` (bullish, D a swing low), `-1.0` (bearish, D a swing high),
+/// or `0.0`; never `None`. See `crates/wickra-core/src/indicators/cypher.rs`.
+#[derive(Debug, Clone)]
+pub struct Cypher {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl Cypher {
+    /// Construct a new Cypher detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 5),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for Cypher {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for Cypher {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 5 {
+            return Some(0.0);
+        }
+        let p = xabcd(pivots);
+        let xa = (p.a - p.x).abs();
+        let ab = (p.b - p.a).abs();
+        let bc = (p.c - p.b).abs();
+        let xc = (p.c - p.x).abs();
+        let cd = (p.d - p.c).abs();
+        let matched = ratios_in(&[
+            (ab / xa, 0.382, 0.618),
+            (bc / xa, 1.13, 1.414),
+            (cd / xc, 0.74, 0.83),
+        ]);
+        if matched {
+            return Some(if p.bullish { 1.0 } else { -1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        6
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "Cypher"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = Cypher::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = Cypher::new();
+        assert_eq!(indicator.name(), "Cypher");
+        assert_eq!(indicator.warmup_period(), 6);
+        assert!(!indicator.is_ready());
+        assert!(!Cypher::default().is_ready());
+    }
+
+    #[test]
+    fn bullish_cypher_is_plus_one() {
+        let out = run(&[150.0, 100.0, 140.0, 120.0, 168.0, 114.55]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn bearish_cypher_is_minus_one() {
+        let out = run(&[150.0, 110.0, 130.0, 82.0, 135.45]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+    }
+
+    #[test]
+    fn out_of_ratio_does_not_trigger() {
+        let out = run(&[150.0, 100.0, 140.0, 110.0, 135.0, 105.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = Cypher::new();
+        for c in candles_for_pivots(&[150.0, 100.0, 140.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[150.0, 100.0, 140.0, 120.0, 168.0, 114.55]);
+        let mut a = Cypher::new();
+        let mut b = Cypher::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,202 @@
+//! Day-of-Week Profile — the mean bar return for each weekday.
+
+use crate::calendar::civil_from_timestamp;
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+const DAYS: usize = 7;
+
+/// Day-of-Week Profile output: the per-weekday mean return.
+///
+/// `bins[i]` is the mean simple return of all bars whose local weekday was `i`,
+/// with Monday as `0` through Sunday as `6`. Weekdays with no bars read `0.0`.
+#[derive(Debug, Clone, PartialEq)]
+pub struct DayOfWeekProfileOutput {
+    /// Per-weekday mean return, Monday first. Always length 7.
+    pub bins: Vec<f64>,
+}
+
+/// Mean bar return bucketed by local weekday (Monday `0` .. Sunday `6`).
+///
+/// Each bar's simple return `close / previous_close - 1` is accumulated into the
+/// bucket of its local weekday (the wall-clock day of
+/// [`Candle::timestamp`](crate::Candle) shifted by `utc_offset_minutes`), and the
+/// profile reports the running mean per weekday. The first bar produces no output.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, DayOfWeekProfile};
+///
+/// let day = 24 * 3_600_000;
+/// let mut prof = DayOfWeekProfile::new(0);
+/// // 1970-01-01 was a Thursday (weekday 3).
+/// assert!(prof.update(Candle::new(100.0, 100.0, 100.0, 100.0, 1.0, 0).unwrap()).is_none());
+/// let out = prof.update(Candle::new(101.0, 101.0, 101.0, 101.0, 1.0, day).unwrap()).unwrap();
+/// assert_eq!(out.bins.len(), 7);
+/// ```
+#[derive(Debug, Clone)]
+pub struct DayOfWeekProfile {
+    utc_offset_minutes: i32,
+    prev_close: Option<f64>,
+    sum: [f64; DAYS],
+    count: [u64; DAYS],
+    last: Option<DayOfWeekProfileOutput>,
+}
+
+impl DayOfWeekProfile {
+    /// Construct a Day-of-Week Profile with the given UTC offset (minutes).
+    pub const fn new(utc_offset_minutes: i32) -> Self {
+        Self {
+            utc_offset_minutes,
+            prev_close: None,
+            sum: [0.0; DAYS],
+            count: [0; DAYS],
+            last: None,
+        }
+    }
+
+    /// Configured UTC offset in minutes.
+    pub const fn utc_offset_minutes(&self) -> i32 {
+        self.utc_offset_minutes
+    }
+
+    /// Most recent profile if at least one return has been recorded.
+    pub fn value(&self) -> Option<&DayOfWeekProfileOutput> {
+        self.last.as_ref()
+    }
+
+    fn snapshot(&self) -> DayOfWeekProfileOutput {
+        let bins = self
+            .sum
+            .iter()
+            .zip(&self.count)
+            .map(|(total, n)| if *n > 0 { total / *n as f64 } else { 0.0 })
+            .collect();
+        DayOfWeekProfileOutput { bins }
+    }
+}
+
+impl Indicator for DayOfWeekProfile {
+    type Input = Candle;
+    type Output = DayOfWeekProfileOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<DayOfWeekProfileOutput> {
+        let civil = civil_from_timestamp(candle.timestamp, self.utc_offset_minutes);
+        let result = if let Some(prev) = self.prev_close {
+            let ret = if prev == 0.0 {
+                0.0
+            } else {
+                candle.close / prev - 1.0
+            };
+            let day = civil.weekday as usize;
+            self.sum[day] += ret;
+            self.count[day] += 1;
+            let out = self.snapshot();
+            self.last = Some(out.clone());
+            Some(out)
+        } else {
+            None
+        };
+        self.prev_close = Some(candle.close);
+        result
+    }
+
+    fn reset(&mut self) {
+        self.prev_close = None;
+        self.sum = [0.0; DAYS];
+        self.count = [0; DAYS];
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "DayOfWeekProfile"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    const DAY: i64 = 24 * 3_600_000;
+
+    fn c(close: f64, ts: i64) -> Candle {
+        Candle::new(close, close, close, close, 1.0, ts).unwrap()
+    }
+
+    #[test]
+    fn metadata_and_accessors() {
+        let prof = DayOfWeekProfile::new(60);
+        assert_eq!(prof.utc_offset_minutes(), 60);
+        assert_eq!(prof.name(), "DayOfWeekProfile");
+        assert_eq!(prof.warmup_period(), 2);
+        assert!(!prof.is_ready());
+        assert!(prof.value().is_none());
+    }
+
+    #[test]
+    fn buckets_by_weekday() {
+        let mut prof = DayOfWeekProfile::new(0);
+        // 1970-01-01 Thursday (3); 01-02 Friday (4).
+        assert!(prof.update(c(100.0, 0)).is_none());
+        let out = prof.update(c(101.0, DAY)).unwrap(); // Friday return +0.01
+        assert_eq!(out.bins.len(), 7);
+        assert_relative_eq!(out.bins[4], 0.01); // Friday
+        assert_relative_eq!(out.bins[3], 0.0); // Thursday had no return
+        assert!(prof.is_ready());
+    }
+
+    #[test]
+    fn averages_same_weekday_across_weeks() {
+        let mut prof = DayOfWeekProfile::new(0);
+        prof.update(c(100.0, 0)); // Thu
+        prof.update(c(101.0, DAY)); // Fri +0.01
+                                    // Jump to next Friday (7 days later from day 0 -> +7 days, weekday 4).
+        prof.update(c(100.0, 7 * DAY)); // Thu+? actually day 7 -> weekday (7+3)%7=3 Thu
+        let out = prof.update(c(103.0, 8 * DAY)).unwrap(); // day 8 -> Fri, return
+                                                           // Friday now has two samples; both positive.
+        assert!(out.bins[4] > 0.0);
+    }
+
+    #[test]
+    fn zero_prev_close_uses_zero_return() {
+        let mut prof = DayOfWeekProfile::new(0);
+        prof.update(c(0.0, 0));
+        let out = prof.update(c(5.0, DAY)).unwrap();
+        assert_relative_eq!(out.bins[4], 0.0); // Friday, guarded return 0
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut prof = DayOfWeekProfile::new(0);
+        prof.update(c(100.0, 0));
+        prof.update(c(101.0, DAY));
+        prof.reset();
+        assert!(!prof.is_ready());
+        assert!(prof.value().is_none());
+        assert!(prof.update(c(100.0, 2 * DAY)).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..30)
+            .map(|i| c(100.0 + f64::from(i % 5), i64::from(i) * DAY))
+            .collect();
+        let mut a = DayOfWeekProfile::new(0);
+        let mut b = DayOfWeekProfile::new(0);
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,218 @@
+//! Derivative Oscillator (Constance Brown).
+
+use crate::error::{Error, Result};
+use crate::indicators::ema::Ema;
+use crate::indicators::rsi::Rsi;
+use crate::indicators::sma::Sma;
+use crate::traits::Indicator;
+
+/// Derivative Oscillator — Constance Brown's double-smoothed RSI histogram.
+///
+/// The RSI is smoothed twice with EMAs, then a simple moving average of that
+/// double-smoothed line is subtracted as a signal, leaving a zero-centered
+/// histogram:
+///
+/// ```text
+/// rsi   = RSI(price, rsi_period)
+/// s1    = EMA(rsi, smooth1)
+/// s2    = EMA(s1,  smooth2)          // double-smoothed RSI
+/// signal = SMA(s2, signal_period)
+/// DerivativeOscillator = s2 - signal
+/// ```
+///
+/// The double EMA smoothing strips the RSI's high-frequency noise, and
+/// subtracting the SMA signal removes the residual level, so the result
+/// oscillates around zero: positive (and rising) bars mark accelerating bullish
+/// momentum, negative bars bearish. Brown's defaults are `rsi_period = 14`,
+/// `smooth1 = 5`, `smooth2 = 3`, `signal_period = 9`.
+///
+/// The first value lands after `rsi_period + smooth1 + smooth2 + signal_period − 2`
+/// inputs, the point at which the whole RSI → EMA → EMA → SMA chain is seeded.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativeOscillator, Indicator};
+///
+/// let mut indicator = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+/// let mut last = None;
+/// for i in 0..120 {
+///     last = indicator.update(100.0 + (f64::from(i) * 0.2).sin() * 5.0);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct DerivativeOscillator {
+    rsi: Rsi,
+    ema1: Ema,
+    ema2: Ema,
+    signal: Sma,
+    warmup: usize,
+}
+
+impl DerivativeOscillator {
+    /// Construct a Derivative Oscillator with the RSI, two EMA smoothing, and
+    /// SMA signal periods.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if any period is `0`.
+    pub fn new(
+        rsi_period: usize,
+        smooth1: usize,
+        smooth2: usize,
+        signal_period: usize,
+    ) -> Result<Self> {
+        if rsi_period == 0 || smooth1 == 0 || smooth2 == 0 || signal_period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            rsi: Rsi::new(rsi_period)?,
+            ema1: Ema::new(smooth1)?,
+            ema2: Ema::new(smooth2)?,
+            signal: Sma::new(signal_period)?,
+            // RSI seeds at rsi_period + 1, then each stage adds (len - 1).
+            warmup: rsi_period + smooth1 + smooth2 + signal_period - 2,
+        })
+    }
+
+    /// Total warmup length (also returned by `warmup_period`).
+    pub const fn warmup(&self) -> usize {
+        self.warmup
+    }
+}
+
+impl Indicator for DerivativeOscillator {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        let rsi = self.rsi.update(input)?;
+        let s1 = self.ema1.update(rsi)?;
+        let s2 = self.ema2.update(s1)?;
+        let signal = self.signal.update(s2)?;
+        Some(s2 - signal)
+    }
+
+    fn reset(&mut self) {
+        self.rsi.reset();
+        self.ema1.reset();
+        self.ema2.reset();
+        self.signal.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.warmup
+    }
+
+    fn is_ready(&self) -> bool {
+        self.signal.is_ready()
+    }
+
+    fn name(&self) -> &'static str {
+        "DerivativeOscillator"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_periods() {
+        assert!(matches!(
+            DerivativeOscillator::new(0, 5, 3, 9),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            DerivativeOscillator::new(14, 0, 3, 9),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            DerivativeOscillator::new(14, 5, 0, 9),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            DerivativeOscillator::new(14, 5, 3, 0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    /// Cover the const accessor `warmup` and the Indicator-impl `warmup_period`
+    /// + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let d = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        // 14 + 5 + 3 + 9 - 2 = 29.
+        assert_eq!(d.warmup(), 29);
+        assert_eq!(d.warmup_period(), 29);
+        assert_eq!(d.name(), "DerivativeOscillator");
+    }
+
+    #[test]
+    fn first_emission_matches_warmup_period() {
+        let prices: Vec<f64> = (0..60)
+            .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 6.0)
+            .collect();
+        let mut d = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        let out = d.batch(&prices);
+        let warmup = d.warmup_period();
+        for (i, v) in out.iter().enumerate().take(warmup - 1) {
+            assert!(v.is_none(), "index {i} must be None during warmup");
+        }
+        assert!(
+            out[warmup - 1].is_some(),
+            "first value must land at warmup_period - 1"
+        );
+    }
+
+    #[test]
+    fn matches_manual_chain() {
+        // Equals RSI -> EMA -> EMA, minus the SMA signal of that line.
+        let prices: Vec<f64> = (0..80)
+            .map(|i| 100.0 + (f64::from(i) * 0.4).sin() * 8.0)
+            .collect();
+        let mut d = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        let mut rsi = Rsi::new(14).unwrap();
+        let mut e1 = Ema::new(5).unwrap();
+        let mut e2 = Ema::new(3).unwrap();
+        let mut sig = Sma::new(9).unwrap();
+        for (i, &p) in prices.iter().enumerate() {
+            let got = d.update(p);
+            let want = rsi
+                .update(p)
+                .and_then(|r| e1.update(r))
+                .and_then(|x| e2.update(x))
+                .and_then(|s2| sig.update(s2).map(|s| s2 - s));
+            assert_eq!(got.is_some(), want.is_some(), "readiness mismatch at {i}");
+            if let (Some(a), Some(b)) = (got, want) {
+                assert_relative_eq!(a, b, epsilon = 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut d = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        d.batch(&(0..60).map(|i| 100.0 + f64::from(i)).collect::<Vec<_>>());
+        assert!(d.is_ready());
+        d.reset();
+        assert!(!d.is_ready());
+        assert_eq!(d.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (0..80)
+            .map(|i| 50.0 + (f64::from(i) * 0.5).sin() * 10.0)
+            .collect();
+        let mut a = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        let mut b = DerivativeOscillator::new(14, 5, 3, 9).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,169 @@
+//! Disparity Index.
+
+use crate::error::Result;
+use crate::indicators::sma::Sma;
+use crate::traits::Indicator;
+
+/// Disparity Index — the percentage gap between price and its moving average.
+///
+/// ```text
+/// Disparity = 100 * (price - SMA(price, period)) / SMA(price, period)
+/// ```
+///
+/// Originating in Japanese technical analysis (*kairi*), the disparity index
+/// expresses how far price has stretched from its `period`-bar simple moving
+/// average, as a percentage of that average. Positive readings mean price is
+/// above the mean (potentially overbought / strong), negative readings mean it
+/// is below (potentially oversold / weak); the magnitude measures how
+/// over-extended the move is.
+///
+/// The first output lands once the inner SMA is ready (input `period`). If the
+/// moving average is exactly zero the gap percentage is undefined and the index
+/// returns `0.0`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DisparityIndex, Indicator};
+///
+/// let mut indicator = DisparityIndex::new(14).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + f64::from(i));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct DisparityIndex {
+    period: usize,
+    sma: Sma,
+}
+
+impl DisparityIndex {
+    /// Construct a disparity index over `period` inputs.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`crate::Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        Ok(Self {
+            period,
+            sma: Sma::new(period)?,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for DisparityIndex {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        let mean = self.sma.update(input)?;
+        if mean == 0.0 {
+            return Some(0.0);
+        }
+        Some(100.0 * (input - mean) / mean)
+    }
+
+    fn reset(&mut self) {
+        self.sma.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.sma.is_ready()
+    }
+
+    fn name(&self) -> &'static str {
+        "DisparityIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(DisparityIndex::new(0).is_err());
+    }
+
+    /// Cover the const accessor `period` and the Indicator-impl `warmup_period`
+    /// + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let di = DisparityIndex::new(14).unwrap();
+        assert_eq!(di.period(), 14);
+        assert_eq!(di.warmup_period(), 14);
+        assert_eq!(di.name(), "DisparityIndex");
+    }
+
+    #[test]
+    fn warmup_then_known_value() {
+        // SMA(3) of [2, 4, 6] = 4; price 6 -> 100 * (6 - 4) / 4 = 50.
+        let mut di = DisparityIndex::new(3).unwrap();
+        assert_eq!(di.update(2.0), None);
+        assert_eq!(di.update(4.0), None);
+        assert_relative_eq!(di.update(6.0).unwrap(), 50.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn constant_series_is_zero() {
+        // Price equals its own mean -> zero disparity.
+        let mut di = DisparityIndex::new(5).unwrap();
+        for v in di.batch(&[42.0; 20]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn negative_when_below_mean() {
+        // SMA(3) of [10, 8, 6] = 8; price 6 -> 100 * (6 - 8) / 8 = -25.
+        let mut di = DisparityIndex::new(3).unwrap();
+        let v = di.batch(&[10.0, 8.0, 6.0]);
+        assert_relative_eq!(v[2].unwrap(), -25.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn zero_mean_returns_zero() {
+        // A window summing to zero (mean 0) makes the percentage undefined; the
+        // index returns 0.0 rather than a non-finite value.
+        let mut di = DisparityIndex::new(2).unwrap();
+        assert_eq!(di.update(-3.0), None);
+        // SMA(2) of [-3, 3] = 0 -> guarded to 0.0.
+        assert_relative_eq!(di.update(3.0).unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut di = DisparityIndex::new(5).unwrap();
+        di.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        assert!(di.is_ready());
+        di.reset();
+        assert!(!di.is_ready());
+        assert_eq!(di.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=30)
+            .map(|i| 50.0 + (f64::from(i) * 0.3).sin() * 10.0)
+            .collect();
+        let mut a = DisparityIndex::new(7).unwrap();
+        let mut b = DisparityIndex::new(7).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,235 @@
+//! Gatev distance (sum of squared deviations) between two normalised series.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Sum of squared deviations between two price series, normalised to a common
+/// start — the classic Gatev et al. pairs-selection distance.
+///
+/// Each `update` takes one `(a, b)` price pair. Over the trailing window of
+/// `period` pairs each series is rebased to `1` at the window's first bar and
+/// the squared gap between the two normalised paths is summed:
+///
+/// ```text
+/// ãᵢ = aᵢ / a_first        b̃ᵢ = bᵢ / b_first
+/// SSD = Σ (ãᵢ − b̃ᵢ)²
+/// ```
+///
+/// Rebasing puts the two series on the same scale (both start at `1`), so the
+/// distance measures how far their *relative* paths drift apart. A **small**
+/// SSD means the two assets track each other tightly — the screen Gatev,
+/// Goetzmann and Rouwenhorst use to pick tradeable pairs; a large SSD means
+/// they have decoupled. The output is always `≥ 0`. If either series is `0` at
+/// the start of the window the normalisation is undefined and the indicator
+/// returns `0`.
+///
+/// Each `update` is `O(period)`, bounded by the fixed window.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DistanceSsd, Indicator};
+///
+/// let mut d = DistanceSsd::new(20).unwrap();
+/// let mut last = None;
+/// for t in 0..40 {
+///     let base = 100.0 + f64::from(t);
+///     // Two near-identical paths ⇒ tiny distance.
+///     last = d.update((base, base * 1.0001));
+/// }
+/// assert!(last.unwrap() < 1e-3);
+/// ```
+#[derive(Debug, Clone)]
+pub struct DistanceSsd {
+    period: usize,
+    window: VecDeque<(f64, f64)>,
+}
+
+impl DistanceSsd {
+    /// Construct a new Gatev distance estimator.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` — a distance needs at
+    /// least two points.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "distance SSD needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured look-back window.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for DistanceSsd {
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(input);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let &(a_first, b_first) = self.window.front().expect("window is full");
+        if a_first == 0.0 || b_first == 0.0 {
+            // Cannot rebase a series that starts at zero.
+            return Some(0.0);
+        }
+        let ssd = self
+            .window
+            .iter()
+            .map(|&(a, b)| {
+                let gap = a / a_first - b / b_first;
+                gap * gap
+            })
+            .sum();
+        Some(ssd)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "DistanceSsd"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(DistanceSsd::new(1).is_err());
+        assert!(DistanceSsd::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let d = DistanceSsd::new(20).unwrap();
+        assert_eq!(d.period(), 20);
+        assert_eq!(d.warmup_period(), 20);
+        assert_eq!(d.name(), "DistanceSsd");
+        assert!(!d.is_ready());
+    }
+
+    #[test]
+    fn warmup_returns_none() {
+        let mut d = DistanceSsd::new(3).unwrap();
+        assert_eq!(d.update((1.0, 1.0)), None);
+        assert_eq!(d.update((2.0, 2.0)), None);
+        assert!(d.update((3.0, 3.0)).is_some());
+        assert!(d.is_ready());
+    }
+
+    #[test]
+    fn identical_normalised_paths_have_zero_distance() {
+        // b = 2·a ⇒ both rebase to the same path ⇒ SSD = 0.
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|t| {
+                let a = 100.0 + f64::from(t);
+                (a, 2.0 * a)
+            })
+            .collect();
+        let last = DistanceSsd::new(10)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn diverging_paths_have_positive_distance() {
+        let pairs: Vec<(f64, f64)> = (0..20)
+            .map(|t| (100.0 + f64::from(t), 100.0 + 3.0 * f64::from(t)))
+            .collect();
+        let last = DistanceSsd::new(10)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last > 0.0, "ssd {last}");
+    }
+
+    #[test]
+    fn hand_computed_value() {
+        // Window of three pairs, a_first = b_first = 1:
+        //   (1,1) → 0; (2,4) → (2−4)² = 4; (3,9) → (3−9)² = 36 ⇒ SSD = 40.
+        let pairs = [(1.0, 1.0), (2.0, 4.0), (3.0, 9.0)];
+        let last = DistanceSsd::new(3)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 40.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn zero_start_returns_zero() {
+        // First bar of the window has a = 0 ⇒ rebasing undefined ⇒ 0.
+        let pairs = [(0.0, 1.0), (2.0, 2.0), (3.0, 3.0)];
+        let last = DistanceSsd::new(3)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut d = DistanceSsd::new(4).unwrap();
+        d.batch(&[(1.0, 1.0), (2.0, 2.0), (3.0, 4.0), (4.0, 5.0), (5.0, 6.0)]);
+        assert!(d.is_ready());
+        d.reset();
+        assert!(!d.is_ready());
+        assert_eq!(d.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..60)
+            .map(|t| {
+                let a = 100.0 + f64::from(t);
+                (a, 100.0 + 1.2 * f64::from(t) + (f64::from(t) * 0.5).sin())
+            })
+            .collect();
+        let batch = DistanceSsd::new(15).unwrap().batch(&pairs);
+        let mut d = DistanceSsd::new(15).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| d.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,188 @@
+//! Double Top / Double Bottom reversal chart pattern.
+
+use crate::indicators::pattern_swing::{
+    approx_equal, SwingTracker, LEVEL_TOLERANCE, SWING_THRESHOLD,
+};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Double Top / Double Bottom — a two-peak (or two-trough) reversal pattern.
+///
+/// The detector tracks confirmed swing pivots (a non-repainting percent-threshold
+/// zig-zag, [`SWING_THRESHOLD`] = 5%). A pattern is recognised on the bar that
+/// confirms the **second** matching extreme:
+///
+/// ```text
+/// double top    : … High₁ , Low , High₂   with  High₁ ≈ High₂   → -1 (bearish)
+/// double bottom : … Low₁  , High , Low₂    with  Low₁  ≈ Low₂    → +1 (bullish)
+/// ```
+///
+/// Two extremes count as the same level when they are within
+/// [`LEVEL_TOLERANCE`] (3%) of each other. Because pivots strictly alternate
+/// high/low, the trough between the twin tops (or the peak between the twin
+/// bottoms) is guaranteed to sit beyond both, so no extra separation check is
+/// needed.
+///
+/// Output is `+1.0` for a double bottom, `-1.0` for a double top, and `0.0` on
+/// every other bar (including warmup and bars that confirm a pivot which does
+/// not complete the pattern). Like the candlestick family this detector never
+/// returns `None`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, DoubleTopBottom, Indicator};
+///
+/// let mut indicator = DoubleTopBottom::new();
+/// for (i, &(high, low)) in [
+///     (100.0, 99.5),
+///     (120.0, 119.5),
+///     (110.0, 100.0), // confirms the first top at 120
+///     (120.0, 119.0), // confirms the trough at 100
+///     (115.0, 110.0), // confirms the second top at 120 → double top
+/// ]
+/// .iter()
+/// .enumerate()
+/// {
+///     let c = Candle::new(low, high, low, low, 1.0, i as i64).unwrap();
+///     let signal = indicator.update(c).unwrap();
+///     if i == 4 {
+///         assert_eq!(signal, -1.0);
+///     }
+/// }
+/// ```
+#[derive(Debug, Clone)]
+pub struct DoubleTopBottom {
+    swing: SwingTracker,
+    has_emitted: bool,
+}
+
+impl DoubleTopBottom {
+    /// Construct a new Double Top / Double Bottom detector.
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 3),
+            has_emitted: false,
+        }
+    }
+}
+
+impl Default for DoubleTopBottom {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for DoubleTopBottom {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        self.has_emitted = true;
+        if !self.swing.update(candle) {
+            return Some(0.0);
+        }
+        let pivots = self.swing.pivots();
+        if pivots.len() < 3 {
+            return Some(0.0);
+        }
+        let first = pivots[pivots.len() - 3];
+        let last = pivots[pivots.len() - 1];
+        if approx_equal(first.price, last.price, LEVEL_TOLERANCE) {
+            // `last` is the just-confirmed extreme: a high → double top (bearish),
+            // a low → double bottom (bullish).
+            return Some(if last.direction > 0.0 { -1.0 } else { 1.0 });
+        }
+        Some(0.0)
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+        self.has_emitted = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // The first complete pattern needs three confirmed pivots; the earliest
+        // bar that can confirm a third pivot is the fifth.
+        5
+    }
+
+    fn is_ready(&self) -> bool {
+        self.has_emitted
+    }
+
+    fn name(&self) -> &'static str {
+        "DoubleTopBottom"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+
+    fn run(pivots: &[f64]) -> Vec<f64> {
+        let mut indicator = DoubleTopBottom::new();
+        candles_for_pivots(pivots)
+            .into_iter()
+            .map(|c| indicator.update(c).unwrap())
+            .collect()
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = DoubleTopBottom::new();
+        assert_eq!(indicator.name(), "DoubleTopBottom");
+        assert_eq!(indicator.warmup_period(), 5);
+        assert!(!indicator.is_ready());
+        assert!(!DoubleTopBottom::default().is_ready());
+    }
+
+    #[test]
+    fn double_top_is_minus_one() {
+        // Twin highs 120 / 120 with a 100 trough → double top on the second.
+        let out = run(&[120.0, 100.0, 120.0]);
+        assert_eq!(*out.last().unwrap(), -1.0);
+        // All earlier bars are warmup / non-completing.
+        assert!(out[..out.len() - 1].iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn double_bottom_is_plus_one() {
+        // Lead high, then twin lows 100 / 99 around a 120 peak → double bottom.
+        let out = run(&[130.0, 100.0, 120.0, 99.0]);
+        assert_eq!(*out.last().unwrap(), 1.0);
+    }
+
+    #[test]
+    fn unequal_tops_do_not_trigger() {
+        // Second top 140 diverges from the first (120) → no pattern.
+        let out = run(&[120.0, 100.0, 140.0]);
+        assert_eq!(*out.last().unwrap(), 0.0);
+        assert!(out.iter().all(|&x| x == 0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = DoubleTopBottom::new();
+        for c in candles_for_pivots(&[120.0, 100.0, 120.0]) {
+            let _ = indicator.update(c);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert_eq!(indicator.update(c), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[120.0, 100.0, 120.0]);
+        let mut a = DoubleTopBottom::new();
+        let mut b = DoubleTopBottom::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,232 @@
+//! Directional Movement Index (DX), Wilder-smoothed.
+
+use crate::error::{Error, Result};
+use crate::indicators::adx::directional_movement;
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Wilder's Directional Movement Index (`DX`).
+///
+/// `DX = 100 · |+DI − −DI| / (+DI + −DI)`, the un-smoothed precursor to
+/// [`Adx`](crate::Adx) (which is the Wilder average of `DX`). Both directional
+/// indicators are derived from Wilder-smoothed `+DM`, `−DM` and true range over
+/// `period` bars, so the first value is emitted after `period + 1` candles.
+///
+/// `DX` ranges over `[0, 100]`: high when one side of the directional system
+/// clearly dominates (a strong trend) and near zero when `+DI` and `−DI` are
+/// balanced (a range). When both directional indicators are zero — a perfectly
+/// flat market — the index returns `0`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, Dx};
+///
+/// let mut indicator = Dx::new(5).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let base = 100.0 + f64::from(i);
+///     let candle =
+///         Candle::new(base, base + 2.0, base - 2.0, base + 1.0, 10.0, i64::from(i)).unwrap();
+///     last = indicator.update(candle);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct Dx {
+    period: usize,
+    prev: Option<Candle>,
+    plus_dm_seed: f64,
+    minus_dm_seed: f64,
+    tr_seed: f64,
+    seed_count: usize,
+    plus_dm_smooth: Option<f64>,
+    minus_dm_smooth: Option<f64>,
+    tr_smooth: Option<f64>,
+}
+
+impl Dx {
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            prev: None,
+            plus_dm_seed: 0.0,
+            minus_dm_seed: 0.0,
+            tr_seed: 0.0,
+            seed_count: 0,
+            plus_dm_smooth: None,
+            minus_dm_smooth: None,
+            tr_smooth: None,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for Dx {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let Some(prev) = self.prev else {
+            self.prev = Some(candle);
+            return None;
+        };
+        self.prev = Some(candle);
+
+        let (plus_dm, minus_dm) = directional_movement(&prev, &candle);
+        let tr = candle.true_range(Some(prev.close));
+        let n = self.period as f64;
+
+        let (plus_v, minus_v, tr_v) = if let (Some(p), Some(m), Some(t)) =
+            (self.plus_dm_smooth, self.minus_dm_smooth, self.tr_smooth)
+        {
+            let p_new = p - p / n + plus_dm;
+            let m_new = m - m / n + minus_dm;
+            let t_new = t - t / n + tr;
+            self.plus_dm_smooth = Some(p_new);
+            self.minus_dm_smooth = Some(m_new);
+            self.tr_smooth = Some(t_new);
+            (p_new, m_new, t_new)
+        } else {
+            self.plus_dm_seed += plus_dm;
+            self.minus_dm_seed += minus_dm;
+            self.tr_seed += tr;
+            self.seed_count += 1;
+            if self.seed_count < self.period {
+                return None;
+            }
+            self.plus_dm_smooth = Some(self.plus_dm_seed);
+            self.minus_dm_smooth = Some(self.minus_dm_seed);
+            self.tr_smooth = Some(self.tr_seed);
+            (self.plus_dm_seed, self.minus_dm_seed, self.tr_seed)
+        };
+
+        let (plus_di, minus_di) = if tr_v == 0.0 {
+            (0.0, 0.0)
+        } else {
+            (100.0 * plus_v / tr_v, 100.0 * minus_v / tr_v)
+        };
+        let di_sum = plus_di + minus_di;
+        let dx = if di_sum == 0.0 {
+            0.0
+        } else {
+            100.0 * (plus_di - minus_di).abs() / di_sum
+        };
+        Some(dx)
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        self.plus_dm_seed = 0.0;
+        self.minus_dm_seed = 0.0;
+        self.tr_seed = 0.0;
+        self.seed_count = 0;
+        self.plus_dm_smooth = None;
+        self.minus_dm_smooth = None;
+        self.tr_smooth = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.tr_smooth.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "DX"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn c(h: f64, l: f64, cl: f64) -> Candle {
+        Candle::new(cl, h, l, cl, 1.0, 0).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(Dx::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_report_config() {
+        let dx = Dx::new(7).unwrap();
+        assert_eq!(dx.period(), 7);
+        assert_eq!(dx.name(), "DX");
+        assert_eq!(dx.warmup_period(), 7);
+        assert!(!dx.is_ready());
+    }
+
+    #[test]
+    fn strong_trend_drives_dx_high() {
+        // A clean uptrend has one-sided directional movement, so DX is large.
+        let candles: Vec<Candle> = (0..12)
+            .map(|i| {
+                let base = 100.0 + f64::from(i) * 2.0;
+                c(base + 1.0, base - 0.5, base + 0.5)
+            })
+            .collect();
+        let mut dx = Dx::new(3).unwrap();
+        let out: Vec<Option<f64>> = dx.batch(&candles);
+        assert_eq!(out[0], None);
+        assert!(out[3].is_some());
+        let last = out.into_iter().flatten().last().unwrap();
+        assert!(last > 50.0 && last <= 100.0);
+        assert!(dx.is_ready());
+    }
+
+    #[test]
+    fn flat_market_returns_zero() {
+        // Both directional indicators collapse to zero -> DX is zero.
+        let candles: Vec<Candle> = (0..6).map(|_| c(50.0, 50.0, 50.0)).collect();
+        let mut dx = Dx::new(3).unwrap();
+        let last = dx.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn balanced_directional_movement_is_low() {
+        // Alternating up and down bars of equal magnitude keep +DI and -DI close,
+        // so DX stays well below a trending reading.
+        let candles: Vec<Candle> = (0..30)
+            .map(|i| {
+                let base = if i % 2 == 0 { 100.0 } else { 101.0 };
+                c(base + 1.0, base - 1.0, base)
+            })
+            .collect();
+        let mut dx = Dx::new(5).unwrap();
+        let last = dx.batch(&candles).into_iter().flatten().last().unwrap();
+        assert!((0.0..=100.0).contains(&last));
+    }
+
+    #[test]
+    fn reset_restores_initial_state() {
+        let candles: Vec<Candle> = (0..6)
+            .map(|i| {
+                let base = 100.0 + f64::from(i) * 2.0;
+                c(base + 1.0, base - 0.5, base + 0.5)
+            })
+            .collect();
+        let mut dx = Dx::new(3).unwrap();
+        let _ = dx.batch(&candles);
+        assert!(dx.is_ready());
+        dx.reset();
+        assert!(!dx.is_ready());
+        assert_eq!(dx.update(candles[0]), None);
+    }
+}

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

@@ -0,0 +1,301 @@
+//! Dynamic Momentum Index (Chande's volatility-adaptive RSI).
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::indicators::sma::Sma;
+use crate::indicators::std_dev::StdDev;
+use crate::traits::Indicator;
+
+// Chande's definitional constants.
+const STD_PERIOD: usize = 5; // volatility window
+const STD_AVG_PERIOD: usize = 10; // smoothing of the volatility
+const MIN_PERIOD: usize = 5; // fastest RSI lookback
+const MAX_PERIOD: usize = 30; // slowest RSI lookback
+
+/// Dynamic Momentum Index — Tushar Chande's RSI whose lookback shrinks in
+/// volatile markets and lengthens in calm ones.
+///
+/// A standard RSI uses a fixed period; the DMI varies it from the recent
+/// volatility so the oscillator stays responsive when the market is fast and
+/// smooth when it is quiet:
+///
+/// ```text
+/// vol     = StdDev(close, 5)
+/// vol_avg = SMA(vol, 10)
+/// Vi      = vol / vol_avg                       (volatility index)
+/// td      = clamp(round(period / Vi), 5, 30)    (dynamic lookback)
+/// avg_gain, avg_loss = simple means of the last `td` price changes
+/// DMI     = 100 * avg_gain / (avg_gain + avg_loss)
+/// ```
+///
+/// High volatility (`Vi > 1`) shortens `td` toward `5` (faster); low volatility
+/// lengthens it toward `30` (slower). The averages of gains and losses are
+/// simple means over the last `td` changes (not Wilder-smoothed), recomputed as
+/// the window length flexes. Output is bounded in `[0, 100]`; a flat market
+/// returns the neutral `50`.
+///
+/// The first value lands after `MAX_PERIOD + 1 = 31` inputs, so the change
+/// buffer always holds enough history for any dynamic lookback up to `30`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DynamicMomentumIndex, Indicator};
+///
+/// let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = dmi.update(100.0 + (f64::from(i) * 0.2).sin() * 5.0);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct DynamicMomentumIndex {
+    period: usize,
+    vol: StdDev,
+    vol_avg: Sma,
+    prev_close: Option<f64>,
+    /// The last `MAX_PERIOD` price changes, oldest at the front.
+    changes: VecDeque<f64>,
+    last_vol_avg: Option<f64>,
+    last_value: Option<f64>,
+}
+
+impl DynamicMomentumIndex {
+    /// Construct a DMI with the given base RSI period (Chande uses 14).
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            vol: StdDev::new(STD_PERIOD)?,
+            vol_avg: Sma::new(STD_AVG_PERIOD)?,
+            prev_close: None,
+            changes: VecDeque::with_capacity(MAX_PERIOD),
+            last_vol_avg: None,
+            last_value: None,
+        })
+    }
+
+    /// Configured base period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last_value
+    }
+
+    /// Dynamic lookback for the current volatility, clamped to `[5, 30]`.
+    fn dynamic_period(&self, vol: f64, vol_avg: f64) -> usize {
+        if vol_avg <= 0.0 || vol <= 0.0 {
+            // No measurable volatility -> slowest (calmest) lookback.
+            return MAX_PERIOD;
+        }
+        let vi = vol / vol_avg;
+        let td = (self.period as f64 / vi).round();
+        // td is finite and positive here; clamp into the valid band.
+        (td as usize).clamp(MIN_PERIOD, MAX_PERIOD)
+    }
+}
+
+impl Indicator for DynamicMomentumIndex {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        if !input.is_finite() {
+            return self.last_value;
+        }
+        // Track the smoothed volatility on every close.
+        if let Some(v) = self.vol.update(input) {
+            self.last_vol_avg = self.vol_avg.update(v);
+        }
+
+        // Record the price change.
+        if let Some(prev) = self.prev_close {
+            let change = input - prev;
+            if self.changes.len() == MAX_PERIOD {
+                self.changes.pop_front();
+            }
+            self.changes.push_back(change);
+        }
+        self.prev_close = Some(input);
+
+        let vol = self.vol.value()?;
+        let vol_avg = self.last_vol_avg?;
+        if self.changes.len() < MAX_PERIOD {
+            return None;
+        }
+
+        let td = self.dynamic_period(vol, vol_avg);
+        // Average gains and losses over the last `td` changes.
+        let mut sum_gain = 0.0;
+        let mut sum_loss = 0.0;
+        for &c in self.changes.iter().skip(MAX_PERIOD - td) {
+            if c > 0.0 {
+                sum_gain += c;
+            } else if c < 0.0 {
+                sum_loss -= c;
+            }
+        }
+        let denom = sum_gain + sum_loss;
+        let v = if denom == 0.0 {
+            50.0
+        } else {
+            // Ratio first, then scale, so `100 * g / g` cannot round above 100.
+            100.0 * (sum_gain / denom)
+        };
+        self.last_value = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.vol.reset();
+        self.vol_avg.reset();
+        self.prev_close = None;
+        self.changes.clear();
+        self.last_vol_avg = None;
+        self.last_value = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // The change buffer (MAX_PERIOD changes => MAX_PERIOD + 1 inputs) is the
+        // binding constraint; the volatility chain (5 + 10 - 1 = 14) is shorter.
+        MAX_PERIOD + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last_value.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "DynamicMomentumIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(
+            DynamicMomentumIndex::new(0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    /// Cover the const accessors `period` + `value` and the Indicator-impl
+    /// `warmup_period` + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let dmi = DynamicMomentumIndex::new(14).unwrap();
+        assert_eq!(dmi.period(), 14);
+        assert_eq!(dmi.value(), None);
+        assert_eq!(dmi.warmup_period(), 31);
+        assert_eq!(dmi.name(), "DynamicMomentumIndex");
+    }
+
+    #[test]
+    fn first_emission_matches_warmup_period() {
+        let prices: Vec<f64> = (0..50)
+            .map(|i| 100.0 + (f64::from(i) * 0.4).sin() * 6.0)
+            .collect();
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        let out = dmi.batch(&prices);
+        for (i, v) in out.iter().enumerate().take(30) {
+            assert!(v.is_none(), "index {i} must be None during warmup");
+        }
+        assert!(out[30].is_some(), "first value at warmup_period - 1 = 30");
+    }
+
+    #[test]
+    fn pure_uptrend_is_one_hundred() {
+        // Every change positive -> avg_loss 0 -> 100, regardless of dynamic period.
+        let prices: Vec<f64> = (1..=60).map(f64::from).collect();
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        let last = dmi.batch(&prices).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 100.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn flat_market_is_neutral() {
+        // Constant prices: no volatility (dynamic period -> max) and no changes
+        // -> neutral 50.
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        let last = dmi.batch(&[42.0; 50]).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 50.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn output_stays_in_range() {
+        let prices: Vec<f64> = (0..120)
+            .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 10.0 + (f64::from(i) * 0.07).cos() * 4.0)
+            .collect();
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        for v in dmi.batch(&prices).into_iter().flatten() {
+            assert!((0.0..=100.0).contains(&v), "DMI {v} left [0, 100]");
+        }
+    }
+
+    #[test]
+    fn high_volatility_shortens_period() {
+        let dmi = DynamicMomentumIndex::new(14).unwrap();
+        // Vi = 2 (vol twice its average) -> td = round(14 / 2) = 7.
+        assert_eq!(dmi.dynamic_period(2.0, 1.0), 7);
+        // Vi = 0.5 (calm) -> td = round(14 / 0.5) = 28.
+        assert_eq!(dmi.dynamic_period(0.5, 1.0), 28);
+        // Extreme calm clamps to MAX_PERIOD; extreme volatility clamps to MIN.
+        assert_eq!(dmi.dynamic_period(0.1, 1.0), MAX_PERIOD);
+        assert_eq!(dmi.dynamic_period(100.0, 1.0), MIN_PERIOD);
+        // Zero volatility -> slowest lookback.
+        assert_eq!(dmi.dynamic_period(0.0, 1.0), MAX_PERIOD);
+        assert_eq!(dmi.dynamic_period(1.0, 0.0), MAX_PERIOD);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        let ready = dmi
+            .batch(&(0..40).map(|i| 100.0 + f64::from(i)).collect::<Vec<_>>())
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(dmi.update(f64::NAN), Some(ready));
+        assert_eq!(dmi.update(f64::INFINITY), Some(ready));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut dmi = DynamicMomentumIndex::new(14).unwrap();
+        dmi.batch(&(0..40).map(|i| 100.0 + f64::from(i)).collect::<Vec<_>>());
+        assert!(dmi.is_ready());
+        dmi.reset();
+        assert!(!dmi.is_ready());
+        assert_eq!(dmi.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (0..80)
+            .map(|i| 50.0 + (f64::from(i) * 0.5).sin() * 10.0)
+            .collect();
+        let mut a = DynamicMomentumIndex::new(14).unwrap();
+        let mut b = DynamicMomentumIndex::new(14).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,202 @@
+//! Exponential Hull Moving Average (EHMA).
+
+use crate::error::{Error, Result};
+use crate::indicators::ema::Ema;
+use crate::traits::Indicator;
+
+/// Exponential Hull Moving Average: the Hull construction built from EMAs
+/// instead of WMAs.
+///
+/// ```text
+/// EHMA = EMA( 2 · EMA(price, period/2) − EMA(price, period), round(sqrt(period)) )
+/// ```
+///
+/// Alan Hull's [`Hma`](crate::Hma) uses weighted moving averages; replacing them
+/// with exponential moving averages keeps the same lag-reduction trick — a fast
+/// half-length average minus a full-length one, smoothed over `sqrt(period)` —
+/// while inheriting the EMA's strictly recursive O(1) update and infinite
+/// (exponentially decaying) memory. The result is marginally smoother than the
+/// WMA-based Hull at the cost of a little more lag.
+///
+/// The half period is `(period / 2).max(1)` and the smoothing period is
+/// `round(sqrt(period)).max(1)`, matching the rounding used by [`Hma`].
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Ehma};
+///
+/// let mut indicator = Ehma::new(9).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + f64::from(i));
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct Ehma {
+    period: usize,
+    half_ema: Ema,
+    full_ema: Ema,
+    smooth_ema: Ema,
+}
+
+impl Ehma {
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        let half = (period / 2).max(1);
+        let smooth = (period as f64).sqrt().round() as usize;
+        let smooth = smooth.max(1);
+        Ok(Self {
+            period,
+            half_ema: Ema::new(half)?,
+            full_ema: Ema::new(period)?,
+            smooth_ema: Ema::new(smooth)?,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for Ehma {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        // Feed both component EMAs on every input so they warm up in parallel;
+        // gating the longer one behind the shorter would delay the first
+        // emission past `warmup_period()`.
+        let h = self.half_ema.update(input);
+        let f = self.full_ema.update(input);
+        let (h, f) = (h?, f?);
+        let diff = 2.0 * h - f;
+        self.smooth_ema.update(diff)
+    }
+
+    fn reset(&mut self) {
+        self.half_ema.reset();
+        self.full_ema.reset();
+        self.smooth_ema.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        // full_ema seeds at `period`, then smooth_ema needs another
+        // (round(sqrt(period)) - 1) values to seed.
+        let sm = (self.period as f64).sqrt().round() as usize;
+        self.period + sm.max(1) - 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.smooth_ema.is_ready()
+    }
+
+    fn name(&self) -> &'static str {
+        "EHMA"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn constant_series_yields_constant_ehma() {
+        let mut ehma = Ehma::new(9).unwrap();
+        let out = ehma.batch(&[10.0_f64; 80]);
+        let last = out.iter().rev().flatten().next().unwrap();
+        assert_relative_eq!(*last, 10.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=100).map(|i| f64::from(i) * 0.7).collect();
+        let mut a = Ehma::new(9).unwrap();
+        let mut b = Ehma::new(9).unwrap();
+        assert_eq!(
+            a.batch(&prices),
+            prices.iter().map(|p| b.update(*p)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ehma = Ehma::new(9).unwrap();
+        ehma.batch(&(1..=80).map(f64::from).collect::<Vec<_>>());
+        assert!(ehma.is_ready());
+        ehma.reset();
+        assert!(!ehma.is_ready());
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(Ehma::new(0).is_err());
+    }
+
+    /// Cover the const accessor `period` and the Indicator-impl `name`.
+    /// `warmup_period` is covered by `first_emission_matches_warmup_period`.
+    #[test]
+    fn accessors_and_metadata() {
+        let ehma = Ehma::new(9).unwrap();
+        assert_eq!(ehma.period(), 9);
+        assert_eq!(ehma.name(), "EHMA");
+    }
+
+    #[test]
+    fn first_emission_matches_warmup_period() {
+        let prices: Vec<f64> = (1..=40).map(f64::from).collect();
+        let mut ehma = Ehma::new(9).unwrap();
+        let out = ehma.batch(&prices);
+        let warmup = ehma.warmup_period();
+        // full EMA seeds at 9, smooth EMA round(sqrt(9))=3 needs 2 more -> 11.
+        assert_eq!(warmup, 11);
+        for (i, v) in out.iter().enumerate().take(warmup - 1) {
+            assert!(v.is_none(), "index {i} must be None during warmup");
+        }
+        assert!(
+            out[warmup - 1].is_some(),
+            "first EHMA value must land at warmup_period - 1"
+        );
+    }
+
+    #[test]
+    fn matches_independent_emas() {
+        // The two component EMAs run as independent siblings on the price
+        // stream; EHMA must equal feeding three standalone EMAs and combining.
+        let prices: Vec<f64> = (1..=50)
+            .map(|i| (f64::from(i) * 0.3).sin() * 10.0 + 50.0)
+            .collect();
+        let mut ehma = Ehma::new(9).unwrap();
+        let mut half = Ema::new(4).unwrap(); // (9 / 2).max(1)
+        let mut full = Ema::new(9).unwrap();
+        let mut smooth = Ema::new(3).unwrap(); // round(sqrt(9))
+        for (i, &p) in prices.iter().enumerate() {
+            let got = ehma.update(p);
+            let want = match (half.update(p), full.update(p)) {
+                (Some(h), Some(f)) => smooth.update(2.0 * h - f),
+                _ => None,
+            };
+            assert_eq!(got.is_some(), want.is_some(), "readiness mismatch at {i}");
+            if let (Some(a), Some(b)) = (got, want) {
+                assert_relative_eq!(a, b, epsilon = 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn period_one_collapses_to_pass_through() {
+        // period 1: half=1, full=1, smooth=round(sqrt(1))=1; every EMA seeds on
+        // the first input, so EHMA(1) passes the price straight through.
+        let mut ehma = Ehma::new(1).unwrap();
+        assert_relative_eq!(ehma.update(5.0).unwrap(), 5.0, epsilon = 1e-12);
+        assert_relative_eq!(ehma.update(8.0).unwrap(), 8.0, epsilon = 1e-12);
+    }
+}

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

@@ -0,0 +1,192 @@
+//! Elder Ray — Bull Power and Bear Power.
+
+use crate::error::Result;
+use crate::indicators::ema::Ema;
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// One Elder Ray reading: the bull and bear power for a bar.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct ElderRayOutput {
+    /// `high − EMA(close)`: how far buyers pushed price above the trend mean.
+    pub bull_power: f64,
+    /// `low − EMA(close)`: how far sellers pushed price below the trend mean
+    /// (negative in a normal market).
+    pub bear_power: f64,
+}
+
+/// Elder Ray — Alexander Elder's Bull Power / Bear Power oscillator.
+///
+/// An EMA of the close marks the market's consensus of value; the bar's high and
+/// low relative to it measure how far the bulls and bears could push price away
+/// from that consensus:
+///
+/// ```text
+/// ema       = EMA(close, period)
+/// BullPower = high - ema
+/// BearPower = low  - ema
+/// ```
+///
+/// Bull Power is normally positive (the high prints above the mean) and Bear
+/// Power normally negative (the low prints below it). Their behaviour relative
+/// to zero and to the EMA's slope drives Elder's signals: e.g. in an uptrend
+/// (rising EMA), a bounce in a negative-but-rising Bear Power is a buy setup.
+///
+/// The first reading lands once the inner EMA is seeded, at bar `period`.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, ElderRay, Indicator};
+///
+/// let mut er = ElderRay::new(13).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let base = 100.0 + f64::from(i);
+///     let c = Candle::new(base, base + 2.0, base - 2.0, base + 0.5, 1.0, i64::from(i)).unwrap();
+///     last = er.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct ElderRay {
+    period: usize,
+    ema: Ema,
+}
+
+impl ElderRay {
+    /// Construct an Elder Ray with the given EMA period.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`crate::Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        Ok(Self {
+            period,
+            ema: Ema::new(period)?,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for ElderRay {
+    type Input = Candle;
+    type Output = ElderRayOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<ElderRayOutput> {
+        let ema = self.ema.update(candle.close)?;
+        Some(ElderRayOutput {
+            bull_power: candle.high - ema,
+            bear_power: candle.low - ema,
+        })
+    }
+
+    fn reset(&mut self) {
+        self.ema.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ema.is_ready()
+    }
+
+    fn name(&self) -> &'static str {
+        "ElderRay"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn candle(high: f64, low: f64, close: f64) -> Candle {
+        Candle::new(close, high, low, close, 1.0, 0).unwrap()
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(ElderRay::new(0).is_err());
+    }
+
+    /// Cover the const accessor `period` and the Indicator-impl `warmup_period`
+    /// + `name`.
+    #[test]
+    fn accessors_and_metadata() {
+        let er = ElderRay::new(13).unwrap();
+        assert_eq!(er.period(), 13);
+        assert_eq!(er.warmup_period(), 13);
+        assert_eq!(er.name(), "ElderRay");
+    }
+
+    #[test]
+    fn warmup_then_known_value() {
+        // EMA(3) seeds at bar 3 with SMA([10,12,14]) = 12 (closes).
+        // bar 3: high 16, low 13 -> bull = 16 - 12 = 4, bear = 13 - 12 = 1.
+        let mut er = ElderRay::new(3).unwrap();
+        assert_eq!(er.update(candle(11.0, 9.0, 10.0)), None);
+        assert_eq!(er.update(candle(13.0, 11.0, 12.0)), None);
+        let v = er.update(candle(16.0, 13.0, 14.0)).unwrap();
+        assert_relative_eq!(v.bull_power, 4.0, epsilon = 1e-12);
+        assert_relative_eq!(v.bear_power, 1.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn matches_manual_ema() {
+        let bars: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + (f64::from(i) * 0.3).sin() * 5.0;
+                candle(base + 2.0, base - 2.0, base)
+            })
+            .collect();
+        let mut er = ElderRay::new(13).unwrap();
+        let mut ema = Ema::new(13).unwrap();
+        for (i, c) in bars.iter().enumerate() {
+            let got = er.update(*c);
+            let want = ema.update(c.close).map(|e| (c.high - e, c.low - e));
+            assert_eq!(got.is_some(), want.is_some(), "readiness mismatch at {i}");
+            if let (Some(g), Some((b, be))) = (got, want) {
+                assert_relative_eq!(g.bull_power, b, epsilon = 1e-9);
+                assert_relative_eq!(g.bear_power, be, epsilon = 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut er = ElderRay::new(5).unwrap();
+        er.batch(
+            &(0..20)
+                .map(|i| candle(f64::from(i) + 1.0, f64::from(i) - 1.0, f64::from(i)))
+                .collect::<Vec<_>>(),
+        );
+        assert!(er.is_ready());
+        er.reset();
+        assert!(!er.is_ready());
+        assert_eq!(er.update(candle(2.0, 0.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let bars: Vec<Candle> = (0..30)
+            .map(|i| {
+                let base = 50.0 + f64::from(i);
+                candle(base + 1.5, base - 1.5, base)
+            })
+            .collect();
+        let mut a = ElderRay::new(7).unwrap();
+        let mut b = ElderRay::new(7).unwrap();
+        assert_eq!(
+            a.batch(&bars),
+            bars.iter().map(|c| b.update(*c)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -25,7 +25,15 @@ use crate::traits::Indicator;
 pub struct Ema {
     period: usize,
     alpha: f64,
-    state: Option<f64>,
+    /// `1 - alpha`, precomputed so the recurrence avoids a subtraction per tick.
+    /// Cached value, so the steady-state output is bit-for-bit unchanged.
+    one_minus_alpha: f64,
+    /// Latest EMA value, valid only once `seeded` is true. Stored as a bare `f64`
+    /// (plus the `seeded` flag) rather than `Option<f64>` so the steady-state
+    /// recurrence reads and writes 8 bytes with no enum-tag handling per tick.
+    current: f64,
+    /// Whether `current` holds a real value yet (warmup complete).
+    seeded: bool,
     warmup_buf: Vec<f64>,
 }
 
@@ -43,7 +51,9 @@ impl Ema {
         Ok(Self {
             period,
             alpha,
-            state: None,
+            one_minus_alpha: 1.0 - alpha,
+            current: 0.0,
+            seeded: false,
             warmup_buf: Vec::with_capacity(period),
         })
     }
@@ -66,7 +76,9 @@ impl Ema {
         Ok(Self {
             period: 1,
             alpha,
-            state: None,
+            one_minus_alpha: 1.0 - alpha,
+            current: 0.0,
+            seeded: false,
             warmup_buf: Vec::with_capacity(1),
         })
     }
@@ -83,21 +95,28 @@ impl Ema {
 
     /// Current value if available.
     pub const fn value(&self) -> Option<f64> {
-        self.state
+        if self.seeded {
+            Some(self.current)
+        } else {
+            None
+        }
     }
 
     /// Internal helper that feeds a value without finiteness validation. The caller
     /// guarantees `input.is_finite()`. Used by MACD which has already validated.
     pub(crate) fn step_unchecked(&mut self, input: f64) -> Option<f64> {
-        if let Some(prev) = self.state {
-            let new = self.alpha.mul_add(input, (1.0 - self.alpha) * prev);
-            self.state = Some(new);
+        if self.seeded {
+            let new = self
+                .alpha
+                .mul_add(input, self.one_minus_alpha * self.current);
+            self.current = new;
             return Some(new);
         }
         self.warmup_buf.push(input);
         if self.warmup_buf.len() == self.period {
             let seed = self.warmup_buf.iter().copied().sum::<f64>() / self.period as f64;
-            self.state = Some(seed);
+            self.current = seed;
+            self.seeded = true;
             return Some(seed);
         }
         None
@@ -110,13 +129,14 @@ impl Indicator for Ema {
 
     fn update(&mut self, input: f64) -> Option<f64> {
         if !input.is_finite() {
-            return self.state;
+            return self.value();
         }
         self.step_unchecked(input)
     }
 
     fn reset(&mut self) {
-        self.state = None;
+        self.current = 0.0;
+        self.seeded = false;
         self.warmup_buf.clear();
     }
 
@@ -125,7 +145,7 @@ impl Indicator for Ema {
     }
 
     fn is_ready(&self) -> bool {
-        self.state.is_some()
+        self.seeded
     }
 
     fn name(&self) -> &'static str {

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

@@ -0,0 +1,264 @@
+//! EWMA Volatility — `RiskMetrics` exponentially-weighted volatility.
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// EWMA Volatility — the `RiskMetrics` exponentially-weighted estimate of the
+/// volatility of log returns.
+///
+/// ```text
+/// r_t  = ln(price_t / price_{t−1})
+/// σ²_t = λ · σ²_{t−1} + (1 − λ) · r²_t
+/// EWMA = √σ²_t
+/// ```
+///
+/// Unlike [`HistoricalVolatility`](crate::HistoricalVolatility) — an equally
+/// weighted, mean-centred sample standard deviation over a fixed window — the
+/// EWMA estimator weights recent squared returns geometrically by the decay
+/// factor `λ`. The most recent return carries weight `1 − λ`, the one before it
+/// `λ(1 − λ)`, and so on, so the estimate reacts to a volatility shock
+/// immediately and then forgets it at rate `λ`. This is the J.P. Morgan
+/// `RiskMetrics` one-parameter model; the standard daily decay is `λ = 0.94`
+/// (monthly `0.97`). No mean is subtracted: squared returns *are* the variance
+/// contribution, which matches the `RiskMetrics` assumption of a zero conditional
+/// mean over short horizons.
+///
+/// The recursion is seeded with the first squared return (`σ²₁ = r²₁`) and emits
+/// from the first return onward, so the very first reading is a one-observation
+/// estimate that the decay then refines. Each `update` is O(1).
+///
+/// Non-finite and non-positive prices are ignored (the log return would be
+/// undefined): the tick is dropped, state is left untouched, and the last value
+/// is returned.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{EwmaVolatility, Indicator};
+///
+/// let mut indicator = EwmaVolatility::new(0.94).unwrap();
+/// let mut last = None;
+/// for i in 0..80 {
+///     last = indicator.update(100.0 + (f64::from(i) * 0.3).sin() * 5.0);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct EwmaVolatility {
+    lambda: f64,
+    prev_price: Option<f64>,
+    /// Exponentially-weighted variance of log returns; `None` until seeded.
+    variance: Option<f64>,
+    last: Option<f64>,
+}
+
+impl EwmaVolatility {
+    /// Construct a new EWMA-volatility indicator.
+    ///
+    /// `lambda` is the decay factor, strictly between `0` and `1` (`RiskMetrics`
+    /// uses `0.94` for daily data). Larger `lambda` means a longer memory and a
+    /// smoother estimate.
+    ///
+    /// # Errors
+    /// Returns [`Error::InvalidParameter`] if `lambda` is not finite or not in
+    /// the open interval `(0, 1)`.
+    pub fn new(lambda: f64) -> Result<Self> {
+        if !lambda.is_finite() || lambda <= 0.0 || lambda >= 1.0 {
+            return Err(Error::InvalidParameter {
+                message: "EWMA volatility lambda must be in the open interval (0, 1)",
+            });
+        }
+        Ok(Self {
+            lambda,
+            prev_price: None,
+            variance: None,
+            last: None,
+        })
+    }
+
+    /// Configured decay factor.
+    pub const fn lambda(&self) -> f64 {
+        self.lambda
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for EwmaVolatility {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, input: f64) -> Option<f64> {
+        // Non-finite / non-positive prices are skipped: `ln(input / prev)` is
+        // undefined, so the tick must not enter the variance recursion.
+        if !input.is_finite() || input <= 0.0 {
+            return self.last;
+        }
+        let Some(prev) = self.prev_price else {
+            self.prev_price = Some(input);
+            return None;
+        };
+        self.prev_price = Some(input);
+        // `prev` came from `self.prev_price`, gated by the guard above, so it is
+        // finite and positive — the log return is always well-defined.
+        let r = (input / prev).ln();
+        let var = match self.variance {
+            // Seed the recursion with the first squared return.
+            None => r * r,
+            Some(prev_var) => self.lambda * prev_var + (1.0 - self.lambda) * r * r,
+        };
+        self.variance = Some(var);
+        // `var` is a convex combination of non-negative terms, but rounding can
+        // leave a tiny negative residual when every return is ~0; clamp first.
+        let vol = var.max(0.0).sqrt();
+        self.last = Some(vol);
+        Some(vol)
+    }
+
+    fn reset(&mut self) {
+        self.prev_price = None;
+        self.variance = None;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        // The first log return needs a previous price; the estimate is seeded
+        // and emitted on that first return.
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "EwmaVolatility"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_invalid_lambda() {
+        for bad in [0.0, 1.0, -0.5, 1.5, f64::NAN, f64::INFINITY] {
+            assert!(matches!(
+                EwmaVolatility::new(bad),
+                Err(Error::InvalidParameter { .. })
+            ));
+        }
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let ewma = EwmaVolatility::new(0.94).unwrap();
+        assert_relative_eq!(ewma.lambda(), 0.94);
+        assert_eq!(ewma.warmup_period(), 2);
+        assert_eq!(ewma.name(), "EwmaVolatility");
+        assert!(!ewma.is_ready());
+        assert_eq!(ewma.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        assert_eq!(ewma.update(100.0), None);
+        let out = ewma.update(110.0);
+        assert!(out.is_some());
+        assert!(ewma.is_ready());
+    }
+
+    #[test]
+    fn known_value() {
+        // r1 = ln(110/100), r2 = ln(99/110). Seed σ²₁ = r1²; then
+        // σ²₂ = λ·r1² + (1−λ)·r2².
+        let lambda = 0.94;
+        let mut ewma = EwmaVolatility::new(lambda).unwrap();
+        let out = ewma.batch(&[100.0, 110.0, 99.0]);
+        let r1 = (110.0_f64 / 100.0).ln();
+        let r2 = (99.0_f64 / 110.0).ln();
+        assert_relative_eq!(out[1].unwrap(), r1.abs(), epsilon = 1e-12);
+        let var2 = lambda * r1 * r1 + (1.0 - lambda) * r2 * r2;
+        assert_relative_eq!(out[2].unwrap(), var2.sqrt(), epsilon = 1e-12);
+    }
+
+    #[test]
+    fn constant_series_yields_zero() {
+        let mut ewma = EwmaVolatility::new(0.9).unwrap();
+        for v in ewma.batch(&[100.0; 40]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn output_is_non_negative() {
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        let prices: Vec<f64> = (1..=200)
+            .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 12.0)
+            .collect();
+        for v in ewma.batch(&prices).into_iter().flatten() {
+            assert!(v >= 0.0, "EWMA volatility must be non-negative, got {v}");
+        }
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        let out = ewma.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let last = *out.last().unwrap();
+        assert!(last.is_some());
+        assert_eq!(ewma.update(f64::NAN), last);
+        assert_eq!(ewma.update(f64::INFINITY), last);
+    }
+
+    #[test]
+    fn skips_non_positive_prices() {
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        let warmup = ewma.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        let baseline = warmup.last().copied().flatten().expect("warmed up");
+        assert_eq!(ewma.update(-5.0), Some(baseline));
+        assert_eq!(ewma.update(0.0), Some(baseline));
+        // State untouched: a clone advanced by the same real tick agrees.
+        let mut control = ewma.clone();
+        let after = ewma.update(21.0).expect("ready");
+        assert_eq!(control.update(21.0).expect("ready"), after);
+    }
+
+    #[test]
+    fn skips_non_positive_before_first_price() {
+        // The skip guard fires before any previous price exists.
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        assert_eq!(ewma.update(0.0), None);
+        assert_eq!(ewma.update(f64::NAN), None);
+        assert_eq!(ewma.update(100.0), None);
+        assert!(ewma.update(110.0).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut ewma = EwmaVolatility::new(0.94).unwrap();
+        ewma.batch(&(1..=20).map(f64::from).collect::<Vec<_>>());
+        assert!(ewma.is_ready());
+        ewma.reset();
+        assert!(!ewma.is_ready());
+        assert_eq!(ewma.value(), None);
+        assert_eq!(ewma.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let prices: Vec<f64> = (1..=120)
+            .map(|i| 100.0 + (f64::from(i) * 0.25).sin() * 9.0)
+            .collect();
+        let batch = EwmaVolatility::new(0.94).unwrap().batch(&prices);
+        let mut b = EwmaVolatility::new(0.94).unwrap();
+        let streamed: Vec<_> = prices.iter().map(|p| b.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,208 @@
+//! Expectancy — expected return per unit of average loss (R-multiple).
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Expectancy — the expected return per trade expressed in units of average
+/// loss (the "R-multiple" expectancy) over the last `period` returns.
+///
+/// ```text
+/// mean    = average of the `period` returns
+/// avgLoss = average of the absolute losing returns (rᵢ < 0)
+/// E       = mean / avgLoss          (0 when there are no losing returns)
+/// ```
+///
+/// Feed a stream of per-trade or per-bar returns. Expectancy answers "how much
+/// do I make per trade for every unit I typically risk": `E = 0.3` means the
+/// system nets `0.3R` per trade on average, where `R` is the average loss.
+/// Dividing the mean return by the average loss makes the figure comparable
+/// across systems with different bet sizes — unlike the raw mean return (which
+/// is just an SMA of the series). A positive `E` is a profitable edge, a
+/// negative `E` a losing one.
+///
+/// When the window contains **no** losing returns there is no risk reference to
+/// normalise against, so the indicator returns `0` (undefined R-multiple)
+/// rather than dividing by zero.
+///
+/// Each `update` is O(1): the running sum and the loss aggregates are
+/// maintained incrementally.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{BatchExt, Indicator, Expectancy};
+///
+/// let mut indicator = Expectancy::new(4).unwrap();
+/// // returns +2, -1, +2, -1: mean 0.5, avg loss 1 -> E = 0.5.
+/// let out = indicator.batch(&[2.0, -1.0, 2.0, -1.0]);
+/// assert_eq!(out[3], Some(0.5));
+/// ```
+#[derive(Debug, Clone)]
+pub struct Expectancy {
+    period: usize,
+    window: VecDeque<f64>,
+    sum: f64,
+    sum_abs_loss: f64,
+    loss_count: usize,
+}
+
+impl Expectancy {
+    /// Construct a new Expectancy over the given window.
+    ///
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+            sum: 0.0,
+            sum_abs_loss: 0.0,
+            loss_count: 0,
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for Expectancy {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("window is non-empty");
+            self.sum -= old;
+            if old < 0.0 {
+                self.sum_abs_loss -= -old;
+                self.loss_count -= 1;
+            }
+        }
+        self.window.push_back(ret);
+        self.sum += ret;
+        if ret < 0.0 {
+            self.sum_abs_loss += -ret;
+            self.loss_count += 1;
+        }
+        if self.window.len() < self.period {
+            return None;
+        }
+        if self.loss_count == 0 {
+            // No losing returns: no risk reference to express the edge in.
+            return Some(0.0);
+        }
+        let mean = self.sum / self.period as f64;
+        let avg_loss = self.sum_abs_loss / self.loss_count as f64;
+        Some(mean / avg_loss)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum = 0.0;
+        self.sum_abs_loss = 0.0;
+        self.loss_count = 0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "Expectancy"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(Expectancy::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let e = Expectancy::new(20).unwrap();
+        assert_eq!(e.period(), 20);
+        assert_eq!(e.warmup_period(), 20);
+        assert_eq!(e.name(), "Expectancy");
+        assert!(!e.is_ready());
+    }
+
+    #[test]
+    fn positive_edge() {
+        // +2, -1, +2, -1: mean 0.5, avgLoss 1 -> 0.5.
+        let mut e = Expectancy::new(4).unwrap();
+        let out = e.batch(&[2.0, -1.0, 2.0, -1.0]);
+        assert_relative_eq!(out[3].unwrap(), 0.5, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn negative_edge() {
+        // +1, -2, +1, -2: mean -0.5, avgLoss 2 -> -0.25.
+        let mut e = Expectancy::new(4).unwrap();
+        let out = e.batch(&[1.0, -2.0, 1.0, -2.0]);
+        assert_relative_eq!(out[3].unwrap(), -0.25, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn no_losses_returns_zero() {
+        // All winning returns: no risk reference -> 0.
+        let mut e = Expectancy::new(5).unwrap();
+        for v in e.batch(&[1.0, 2.0, 3.0, 1.0, 2.0]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn flat_returns_are_not_losses() {
+        // Zeros are not losses: mean (2+0+2+0)/4 = 1, but no losing returns
+        // -> 0 (undefined R-multiple).
+        let mut e = Expectancy::new(4).unwrap();
+        let out = e.batch(&[2.0, 0.0, 2.0, 0.0]);
+        assert_relative_eq!(out[3].unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rolling_window_evicts_old_losses() {
+        // period 4. Window [+2,-1,+2,-1] -> 0.5; then push +3,+3,+3,+3 to evict
+        // all losses -> no losses -> 0.
+        let mut e = Expectancy::new(4).unwrap();
+        let out = e.batch(&[2.0, -1.0, 2.0, -1.0, 3.0, 3.0, 3.0, 3.0]);
+        assert_relative_eq!(out[3].unwrap(), 0.5, epsilon = 1e-12);
+        assert_relative_eq!(out[7].unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut e = Expectancy::new(5).unwrap();
+        e.batch(&[1.0, -1.0, 2.0, -2.0, 1.0]);
+        assert!(e.is_ready());
+        e.reset();
+        assert!(!e.is_ready());
+        assert_eq!(e.update(1.0), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60).map(|i| (f64::from(i) * 0.5).sin() * 2.0).collect();
+        let batch = Expectancy::new(14).unwrap().batch(&rets);
+        let mut b = Expectancy::new(14).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|p| b.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,198 @@
+//! Fibonacci Arcs — semicircular retracement levels centred on the swing end,
+//! decaying back toward it as time elapses.
+
+use crate::indicators::pattern_swing::{SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// The three arc ratios drawn (38.2% / 50% / 61.8%).
+const RATIOS: [f64; 3] = [0.382, 0.5, 0.618];
+
+/// Fibonacci Arc prices evaluated at the current bar.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct FibArcsOutput {
+    /// Price of the 38.2% arc at the current bar.
+    pub arc_382: f64,
+    /// Price of the 50% arc at the current bar.
+    pub arc_500: f64,
+    /// Price of the 61.8% arc at the current bar.
+    pub arc_618: f64,
+}
+
+/// Fibonacci Arcs (`FibArcs`).
+///
+/// Three arcs centred on the end of the most recent confirmed swing leg. Time is
+/// normalised by the leg's bar-width so the construction is chart-scale-free: at
+/// the leg's end bar each arc sits exactly on its retracement level, and as time
+/// elapses the arc curves back toward the swing-end price, reaching it one leg
+/// width later.
+///
+/// ```text
+/// u       = (cur - end_bar) / (end_bar - start_bar)
+/// arc(r)  = end + (start - end) * r * sqrt(max(0, 1 - u^2))
+/// ```
+///
+/// Parameter-free; construction is infallible. Returns `None` until the first
+/// leg is complete.
+///
+/// See `crates/wickra-core/src/indicators/fib_arcs.rs`.
+#[derive(Debug, Clone)]
+pub struct FibArcs {
+    swing: SwingTracker,
+}
+
+impl FibArcs {
+    /// Construct a new Fibonacci Arcs tracker.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 2),
+        }
+    }
+
+    fn arcs(&self) -> Option<FibArcsOutput> {
+        let pivots = self.swing.pivots();
+        let start = pivots.first()?;
+        let end = pivots.get(1)?;
+        // Consecutive pivots occur at strictly increasing bars → span >= 1 bar.
+        let span_bars = (end.bar - start.bar) as f64;
+        let u = (self.swing.current_bar() - end.bar) as f64 / span_bars;
+        let curve = (1.0 - u * u).max(0.0).sqrt();
+        let arc = |r: f64| end.price + (start.price - end.price) * r * curve;
+        Some(FibArcsOutput {
+            arc_382: arc(RATIOS[0]),
+            arc_500: arc(RATIOS[1]),
+            arc_618: arc(RATIOS[2]),
+        })
+    }
+}
+
+impl Default for FibArcs {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for FibArcs {
+    type Input = Candle;
+    type Output = FibArcsOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<FibArcsOutput> {
+        self.swing.update(candle);
+        self.arcs()
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.swing.pivots().len() >= 2
+    }
+
+    fn name(&self) -> &'static str {
+        "FibArcs"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn c(high: f64, low: f64, ts: i64) -> Candle {
+        Candle::new(low, high, low, low, 1.0, ts).unwrap()
+    }
+
+    /// Leg start=200 (bar 0) -> end=100 (bar 2), confirmed at bar 3 so the arc is
+    /// first reported with `u = (3 - 2) / (2 - 0) = 0.5`.
+    fn down_leg() -> Vec<Candle> {
+        vec![
+            c(200.0, 199.0, 0),
+            c(190.0, 160.0, 1), // confirm high @200
+            c(150.0, 100.0, 2), // extend low to 100 (bar 2)
+            c(110.0, 105.0, 3), // confirm low @100 -> two pivots
+        ]
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = FibArcs::new();
+        assert_eq!(indicator.name(), "FibArcs");
+        assert_eq!(indicator.warmup_period(), 2);
+        assert!(!indicator.is_ready());
+        assert!(!FibArcs::default().is_ready());
+    }
+
+    #[test]
+    fn no_output_before_two_pivots() {
+        let mut indicator = FibArcs::new();
+        let outputs: Vec<_> = [c(200.0, 199.0, 0), c(190.0, 150.0, 1)]
+            .into_iter()
+            .map(|x| indicator.update(x))
+            .collect();
+        assert!(outputs.iter().all(Option::is_none));
+        assert!(!indicator.is_ready());
+    }
+
+    #[test]
+    fn arcs_curve_back_toward_the_swing_end() {
+        let mut indicator = FibArcs::new();
+        let mut last = None;
+        for candle in down_leg() {
+            last = indicator.update(candle);
+        }
+        let v = last.unwrap();
+        assert!(indicator.is_ready());
+        // u = 0.5 → curve = sqrt(0.75); arc(r) = 100 + 100 * r * curve.
+        let curve = 0.75_f64.sqrt();
+        assert_relative_eq!(v.arc_382, 100.0 + 100.0 * 0.382 * curve);
+        assert_relative_eq!(v.arc_500, 100.0 + 100.0 * 0.5 * curve);
+        assert_relative_eq!(v.arc_618, 100.0 + 100.0 * 0.618 * curve);
+    }
+
+    #[test]
+    fn arc_clamps_to_zero_beyond_one_leg_width() {
+        // Extend far past the end pivot so u > 1; the curve clamps to 0 and the
+        // arcs collapse onto the swing-end price.
+        let mut indicator = FibArcs::new();
+        for candle in down_leg() {
+            let _ = indicator.update(candle);
+        }
+        // Feed flat bars that neither extend nor confirm a new pivot.
+        let mut last = None;
+        for ts in 4..12 {
+            last = indicator.update(c(108.0, 106.0, ts));
+        }
+        let v = last.unwrap();
+        assert_relative_eq!(v.arc_382, 100.0);
+        assert_relative_eq!(v.arc_618, 100.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = FibArcs::new();
+        for candle in down_leg() {
+            let _ = indicator.update(candle);
+        }
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        assert!(indicator.update(c(100.0, 99.5, 0)).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = down_leg();
+        let mut a = FibArcs::new();
+        let mut b = FibArcs::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,192 @@
+//! Fibonacci Channel — a sloped base trendline plus parallel lines offset by
+//! Fibonacci multiples of the channel width.
+
+use crate::indicators::pattern_swing::{SwingTracker, SWING_THRESHOLD};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// The parallel-line ratios above the base (61.8% / 100% / 161.8% of the width).
+const RATIOS: [f64; 3] = [0.618, 1.0, 1.618];
+
+/// Fibonacci Channel line prices evaluated at the current bar.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct FibChannelOutput {
+    /// The base trendline price at the current bar.
+    pub base: f64,
+    /// Base + 61.8% of the channel width.
+    pub level_618: f64,
+    /// Base + 100% of the width — the opposite channel boundary.
+    pub level_1000: f64,
+    /// Base + 161.8% of the width.
+    pub level_1618: f64,
+}
+
+/// Fibonacci Channel (`FibChannel`).
+///
+/// From the last three confirmed pivots, the two same-direction outer pivots
+/// define a sloped base trendline and the opposite middle pivot sets the channel
+/// width (its signed distance from the base line). Parallel lines are then offset
+/// by Fibonacci multiples of that width and reported at the current bar.
+///
+/// ```text
+/// slope     = (p2 - p0) / (bar2 - bar0)
+/// base(bar) = p0 + slope * (bar - bar0)
+/// width     = p1 - base(bar1)
+/// level(r)  = base(cur) + r * width
+/// ```
+///
+/// Parameter-free; construction is infallible. Returns `None` until three pivots
+/// have confirmed.
+///
+/// See `crates/wickra-core/src/indicators/fib_channel.rs`.
+#[derive(Debug, Clone)]
+pub struct FibChannel {
+    swing: SwingTracker,
+}
+
+impl FibChannel {
+    /// Construct a new Fibonacci Channel tracker.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, 3),
+        }
+    }
+
+    fn channel(&self) -> Option<FibChannelOutput> {
+        let pivots = self.swing.pivots();
+        let p0 = pivots.first()?;
+        let p1 = pivots.get(1)?;
+        let p2 = pivots.get(2)?;
+        // p0 and p2 are the same-direction outer pivots; their bars differ
+        // strictly, so the slope denominator is non-zero.
+        let slope = (p2.price - p0.price) / (p2.bar - p0.bar) as f64;
+        let base_at = |bar: usize| p0.price + slope * (bar - p0.bar) as f64;
+        let width = p1.price - base_at(p1.bar);
+        let base = base_at(self.swing.current_bar());
+        Some(FibChannelOutput {
+            base,
+            level_618: base + RATIOS[0] * width,
+            level_1000: base + RATIOS[1] * width,
+            level_1618: base + RATIOS[2] * width,
+        })
+    }
+}
+
+impl Default for FibChannel {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for FibChannel {
+    type Input = Candle;
+    type Output = FibChannelOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<FibChannelOutput> {
+        self.swing.update(candle);
+        self.channel()
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.swing.pivots().len() >= 3
+    }
+
+    fn name(&self) -> &'static str {
+        "FibChannel"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn c(high: f64, low: f64, ts: i64) -> Candle {
+        Candle::new(low, high, low, low, 1.0, ts).unwrap()
+    }
+
+    /// Pivots: high 200 (bar 0), low 100 (bar 1), high 220 (bar 3); confirmed at
+    /// bar 4 so the channel is first reported at current bar 4.
+    fn three_pivots() -> Vec<Candle> {
+        vec![
+            c(200.0, 199.0, 0),
+            c(190.0, 100.0, 1), // confirm high @200, low candidate @100
+            c(110.0, 108.0, 2), // confirm low @100, high candidate @110
+            c(220.0, 210.0, 3), // extend high to 220 (bar 3)
+            c(200.0, 150.0, 4), // confirm high @220 -> three pivots
+        ]
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = FibChannel::new();
+        assert_eq!(indicator.name(), "FibChannel");
+        assert_eq!(indicator.warmup_period(), 3);
+        assert!(!indicator.is_ready());
+        assert!(!FibChannel::default().is_ready());
+    }
+
+    #[test]
+    fn no_output_before_three_pivots() {
+        let mut indicator = FibChannel::new();
+        let outputs: Vec<_> = [c(200.0, 199.0, 0), c(190.0, 100.0, 1), c(110.0, 108.0, 2)]
+            .into_iter()
+            .map(|x| indicator.update(x))
+            .collect();
+        // Only two pivots confirm within these three bars.
+        assert!(outputs.iter().all(Option::is_none));
+        assert!(!indicator.is_ready());
+    }
+
+    #[test]
+    fn channel_levels_from_three_pivots() {
+        let mut indicator = FibChannel::new();
+        let mut last = None;
+        for candle in three_pivots() {
+            last = indicator.update(candle);
+        }
+        let v = last.unwrap();
+        assert!(indicator.is_ready());
+        // Base through highs (0,200) and (3,220); width from low (1,100); cur = 4.
+        let slope = (220.0 - 200.0) / 3.0;
+        let base_cur = 200.0 + slope * 4.0;
+        let width = 100.0 - (200.0 + slope * 1.0);
+        assert_relative_eq!(v.base, base_cur);
+        assert_relative_eq!(v.level_1000, base_cur + width);
+        assert_relative_eq!(v.level_618, base_cur + 0.618 * width);
+        assert_relative_eq!(v.level_1618, base_cur + 1.618 * width);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = FibChannel::new();
+        for candle in three_pivots() {
+            let _ = indicator.update(candle);
+        }
+        assert!(indicator.is_ready());
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        assert!(indicator.update(c(100.0, 99.5, 0)).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = three_pivots();
+        let mut a = FibChannel::new();
+        let mut b = FibChannel::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}

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

@@ -0,0 +1,181 @@
+//! Fibonacci Confluence — the strongest retracement cluster across recent legs.
+
+use crate::indicators::pattern_swing::{
+    approx_equal, SwingTracker, LEVEL_TOLERANCE, SWING_THRESHOLD,
+};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// How many recent pivots to consider; six pivots yield up to five legs.
+const PIVOT_HISTORY: usize = 6;
+
+/// The retracement ratios contributed by each leg to the confluence search.
+const RATIOS: [f64; 3] = [0.382, 0.5, 0.618];
+
+/// The strongest Fibonacci confluence zone found across recent swing legs.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct FibConfluenceOutput {
+    /// Mean price of the densest cluster of retracement levels.
+    pub price: f64,
+    /// Number of retracement levels that fall inside the cluster (its strength).
+    pub strength: f64,
+}
+
+/// Fibonacci Confluence (`FibConfluence`).
+///
+/// Computes the 38.2% / 50% / 61.8% retracement prices of every leg among the
+/// last six confirmed pivots, then reports the densest price cluster — where
+/// levels from different legs stack up, the zone the market is most likely to
+/// react to. `price` is the cluster mean; `strength` is how many levels it
+/// gathers.
+///
+/// Parameter-free; construction is infallible. Returns `None` until at least two
+/// legs (three pivots) exist.
+///
+/// See `crates/wickra-core/src/indicators/fib_confluence.rs`.
+#[derive(Debug, Clone)]
+pub struct FibConfluence {
+    swing: SwingTracker,
+}
+
+impl FibConfluence {
+    /// Construct a new Fibonacci Confluence tracker.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self {
+            swing: SwingTracker::new(SWING_THRESHOLD, PIVOT_HISTORY),
+        }
+    }
+
+    fn confluence(&self) -> Option<FibConfluenceOutput> {
+        let pivots = self.swing.pivots();
+        if pivots.len() < 3 {
+            return None;
+        }
+        let levels: Vec<f64> = pivots
+            .windows(2)
+            .flat_map(|leg| {
+                let (start, end) = (leg[0].price, leg[1].price);
+                RATIOS.map(|r| end + r * (start - end))
+            })
+            .collect();
+        // The `len < 3` guard guarantees at least two legs, hence a non-empty
+        // level set, so `max_by` always yields a cluster.
+        let (count, total) = levels
+            .iter()
+            .map(|&center| {
+                let members: Vec<f64> = levels
+                    .iter()
+                    .copied()
+                    .filter(|&x| approx_equal(x, center, LEVEL_TOLERANCE))
+                    .collect();
+                (members.len(), members.iter().sum::<f64>())
+            })
+            .max_by(|a, b| a.0.cmp(&b.0))
+            .expect("at least two legs guarantee a non-empty level set");
+        Some(FibConfluenceOutput {
+            price: total / count as f64,
+            strength: count as f64,
+        })
+    }
+}
+
+impl Default for FibConfluence {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl Indicator for FibConfluence {
+    type Input = Candle;
+    type Output = FibConfluenceOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<FibConfluenceOutput> {
+        self.swing.update(candle);
+        self.confluence()
+    }
+
+    fn reset(&mut self) {
+        self.swing.reset();
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.swing.pivots().len() >= 3
+    }
+
+    fn name(&self) -> &'static str {
+        "FibConfluence"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::indicators::pattern_swing::candles_for_pivots;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn accessors_and_metadata() {
+        let indicator = FibConfluence::new();
+        assert_eq!(indicator.name(), "FibConfluence");
+        assert_eq!(indicator.warmup_period(), 3);
+        assert!(!indicator.is_ready());
+        assert!(!FibConfluence::default().is_ready());
+    }
+
+    #[test]
+    fn no_output_before_two_legs() {
+        let mut indicator = FibConfluence::new();
+        let outputs: Vec<_> = candles_for_pivots(&[200.0, 100.0])
+            .into_iter()
+            .map(|c| indicator.update(c))
+            .collect();
+        assert!(outputs.iter().all(Option::is_none));
+        assert!(!indicator.is_ready());
+    }
+
+    #[test]
+    fn picks_the_densest_cluster() {
+        // Legs 200->100 and 100->160. The 38.2% of each (138.2 and ~137.08)
+        // sit within 3% of each other and form the densest cluster (strength 2).
+        let mut indicator = FibConfluence::new();
+        let mut last = None;
+        for candle in candles_for_pivots(&[200.0, 100.0, 160.0]) {
+            last = indicator.update(candle);
+        }
+        let v = last.unwrap();
+        assert!(indicator.is_ready());
+        assert_relative_eq!(v.strength, 2.0);
+        let want = (138.2 + (160.0 + 0.382 * (100.0 - 160.0))) / 2.0;
+        assert_relative_eq!(v.price, want, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut indicator = FibConfluence::new();
+        for candle in candles_for_pivots(&[200.0, 100.0, 160.0]) {
+            let _ = indicator.update(candle);
+        }
+        assert!(indicator.is_ready());
+        indicator.reset();
+        assert!(!indicator.is_ready());
+        let c = Candle::new(99.5, 100.0, 99.5, 99.5, 1.0, 0).unwrap();
+        assert!(indicator.update(c).is_none());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles = candles_for_pivots(&[200.0, 100.0, 160.0, 120.0]);
+        let mut a = FibConfluence::new();
+        let mut b = FibConfluence::new();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+}