release: bump 0.7.2 -> 0.7.3 (#219)

Version bump **0.7.2 → 0.7.3** for the B18 Risk / Performance batch (9 new indicators, 498 → 507).

Bumps `Cargo.toml` (+ `wickra-core` dep), `Cargo.lock`, `pyproject.toml`, the Node `package.json` and its six platform packages, both `package-lock.json` files, and the CHANGELOG (`[Unreleased]` → `[0.7.3]` with compare URLs).

.github/workflows/ci.yml

@@ -53,6 +53,22 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # CARGO_NET_RETRY rides out short blips, but a longer runner DNS outage
+        # outlasts cargo's rapid in-process retries: the crates.io index fetch
+        # the first cargo step does ("Could not resolve host: index.crates.io")
+        # then fails the whole job. Pre-fetch the dependency graph here with real
+        # backoff so clippy/build/test resolve from the warmed local cache.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Format check
         run: cargo fmt --all -- --check
 
@@ -232,6 +248,19 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # See the rust job: pre-fetch with backoff so the clippy index update
+        # can't fail the job on a transient "Could not resolve host" DNS blip.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Clippy (bindings, all targets)
         run: cargo clippy -p wickra-node -p wickra-python --all-targets -- -D warnings
 
@@ -272,6 +301,19 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # See the rust job: pre-fetch with backoff so the first cargo step can't
+        # fail the job on a transient "Could not resolve host" DNS blip.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Build on MSRV
         run: cargo build ${{ matrix.packages }} --verbose
 

BENCHMARKS.md

@@ -26,15 +26,15 @@ was built to expose.
 
 | Indicator        | **★ Wickra** | talipp           | TA-Lib (recompute)    |
 |------------------|------------------:|------------------|-----------------------|
-| SMA(20)          | **0.063 µs ★**    | 0.59 µs (9×)     | 204 µs (3 300×)       |
-| EMA(20)          | **0.060 µs ★**    | 0.72 µs (12×)    | 212 µs (3 500×)       |
-| RSI(14)          | **0.065 µs ★**    | 1.06 µs (16×)    | 230 µs (3 600×)       |
-| MACD(12, 26, 9)  | **0.078 µs ★**    | 4.22 µs (54×)    | 245 µs (3 100×)       |
-| Bollinger(20, 2) | **0.088 µs ★**    | 5.15 µs (58×)    | 229 µs (2 600×)       |
+| SMA(20)          | **0.089 µs ★**    | 0.96 µs (11×)    | 422 µs (4 700×)       |
+| EMA(20)          | **0.111 µs ★**    | 1.19 µs (11×)    | 430 µs (3 900×)       |
+| RSI(14)          | **0.061 µs ★**    | 0.95 µs (16×)    | 298 µs (4 900×)       |
+| MACD(12, 26, 9)  | **0.079 µs ★**    | 3.30 µs (42×)    | 327 µs (4 100×)       |
+| Bollinger(20, 2) | **0.089 µs ★**    | 4.97 µs (56×)    | 296 µs (3 300×)       |
 
-Against the only other incremental Python peer Wickra is **9–58× faster**;
-against the recompute-on-every-tick libraries it is **2 600–14 000× faster**
-(`finta` RSI hits 14 000×). tulipy / pandas-ta land in the same recompute band
+Against the only other incremental Python peer Wickra is **11–56× faster**;
+against the recompute-on-every-tick libraries it is **2 800–19 000× faster**
+(`finta` RSI hits 19 000×). tulipy / pandas-ta land in the same recompute band
 as TA-Lib.
 
 **Rust — per-tick latency** (whole 50 000-bar series, lower = faster):
@@ -63,17 +63,17 @@ field everywhere.
 
 **Python** (20 000-bar pass, µs/op, lower = faster):
 
-| Indicator        | Wickra   | TA-Lib | tulipy | pandas-ta |
-|------------------|---------:|-------:|-------:|----------:|
-| SMA(20)          | 22.7     | **15.4** | 15.9 | 33.7      |
-| EMA(20)          | 30.8     | **30.3** | 31.1 | 48.8      |
-| RSI(14)          | 58.9     | 72.5   | **38.5** | 94.8    |
-| MACD(12, 26, 9)  | 71.7     | 99.1   | **33.5** | 207.6   |
-| Bollinger(20, 2) | 84.9     | 65.7   | **32.3** | 336.4   |
-| ATR(14)          | 52.0     | 79.4   | **31.9** | —        |
+| Indicator        | Wickra   | TA-Lib   | tulipy   | pandas-ta | finta    |
+|------------------|---------:|---------:|---------:|----------:|---------:|
+| SMA(20)          | 22.2     | **15.6** | 15.9     | 32.7      | 290.1    |
+| EMA(20)          | 30.5     | **30.4** | 30.9     | 46.7      | 198.5    |
+| RSI(14)          | 52.3     | 72.0     | **34.2** | 88.8      | 812.3    |
+| MACD(12, 26, 9)  | 129.8    | 111.1    | **38.4** | 286.8     | 716.7    |
+| Bollinger(20, 2) | 87.2     | 74.6     | **37.9** | 474.3     | 1255.5   |
+| ATR(14)          | 74.7     | 87.3     | **35.5** | —         | 3496.4   |
 
-Wickra beats TA-Lib on RSI, MACD and ATR and the whole Python field on every
-row; tulipy's SIMD C stays ahead on the heavier indicators.
+Wickra beats pandas-ta and finta on every row and TA-Lib on RSI and ATR;
+tulipy's SIMD C (and TA-Lib on SMA/EMA) lead the remaining rows.
 
 **Rust** (50 000-bar pass, µs, lower = faster). Only Wickra and `kand` expose a
 batch API; `ta-rs` and `yata` are streaming-only:

CHANGELOG.md

@@ -7,6 +7,44 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.7.3] - 2026-06-08
+- **M2Measure** — M2 measure (Modigliani; Sharpe expressed in benchmark return units) (`M2Measure`).
+- **UpsidePotentialRatio** — Upside Potential Ratio (upside mean over downside deviation) (`UpsidePotentialRatio`).
+- **GainToPainRatio** — Gain-to-Pain Ratio (sum of returns over sum of losses) (`GainToPainRatio`).
+- **CommonSenseRatio** — Common Sense Ratio (tail ratio times gain-to-pain) (`CommonSenseRatio`).
+- **KRatio** — K-Ratio (Kestner; equity-curve slope over its standard error) (`KRatio`).
+- **TailRatio** — Tail Ratio (95th over absolute 5th return percentile) (`TailRatio`).
+- **MartinRatio** — Martin Ratio (Ulcer Performance Index; return over RMS drawdown) (`MartinRatio`).
+- **BurkeRatio** — Burke Ratio (return over root-sum-squared drawdowns) (`BurkeRatio`).
+- **SterlingRatio** — Sterling Ratio (mean return over average drawdown) (`SterlingRatio`).
+
+## [0.7.2] - 2026-06-08
+- **Composite Profile** — multi-session composite volume profile exposing POC, VAH and VAL (`CompositeProfile`).
+- **High/Low Volume Nodes** — highest- and lowest-volume price nodes in the profile (`HighLowVolumeNodes`).
+- **Profile Shape** — profile shape classification (b/P/D normal) as a numeric code (`ProfileShape`).
+- **Single Prints** — count of single-print (low-activity) price levels in the profile (`SinglePrints`).
+- **Naked POC** — most recent untouched (naked) point of control level (`NakedPoc`).
+
+## [0.7.1] - 2026-06-08
+- **Open-Interest Momentum** — rate-of-change of open interest over a rolling window (`OpenInterestMomentum`).
+- **Funding-Implied APR** — annualised funding rate (per-interval funding times intervals per year) (`FundingImpliedApr`).
+- **Perpetual Premium Index** — relative premium of the mark price over the index price (`PerpetualPremiumIndex`).
+- **OI-to-Volume Ratio** — open interest divided by taker volume (position turnover proxy) (`OiToVolumeRatio`).
+- **Estimated Leverage Ratio** — open interest divided by aggregate long+short position size (leverage proxy) (`EstimatedLeverageRatio`).
+
+## [0.7.0] - 2026-06-08
+- **Hasbrouck Information Share** — variance-ratio proxy for each venue's share of price discovery (Hasbrouck information share) (`HasbrouckInformationShare`).
+- **PIN** — probability of informed trading from rolling buy/sell imbalance (EKOP single-window estimator) (`Pin`).
+- **Trade-Sign Autocorrelation** — lag-1 autocorrelation of the signed trade aggressor (order-flow persistence) (`TradeSignAutocorrelation`).
+
+## [0.6.9] - 2026-06-08
+- **Tristar** — a three-doji star reversal: three consecutive dojis with the middle gapped above (bearish) or below (bullish) its neighbours (`Tristar`).
+- **Harami Cross** — a Harami whose second candle is a contained doji, a stronger reversal than a plain Harami (`HaramiCross`).
+- **Tower Top/Bottom** — a tall bar, a small pause bar, then a tall opposite bar marking a reversal (`TowerTopBottom`).
+- **Frying Pan Bottom** — a rounded (U-shaped) accumulation base over the lookback window, confirmed when price recovers above the rim (`FryPanBottom`).
+- **Dumpling Top** — a rounded (dome-shaped) distribution top over the lookback window, confirmed when price breaks below the start (`DumplingTop`).
+- **New Price Lines** — flags a run of N consecutive new closing highs (+1) or lows (-1), the eight/ten-new-price-lines exhaustion gauge (`NewPriceLines`).
+
 ## [0.6.8] - 2026-06-08
 - **Smoothed Heikin-Ashi** — a Heikin-Ashi candle computed from EMA-smoothed OHLC, damping noise into a cleaner trend candle (`SmoothedHeikinAshi`).
 - **Heikin-Ashi Oscillator** — the Heikin-Ashi candle body (`ha_close − ha_open`), optionally EMA-smoothed, as a zero-line oscillator (`HeikinAshiOscillator`).
@@ -1369,7 +1407,12 @@ 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/v0.6.8...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.7.3...HEAD
+[0.7.3]: https://github.com/wickra-lib/wickra/compare/v0.7.2...v0.7.3
+[0.7.2]: https://github.com/wickra-lib/wickra/compare/v0.7.1...v0.7.2
+[0.7.1]: https://github.com/wickra-lib/wickra/compare/v0.7.0...v0.7.1
+[0.7.0]: https://github.com/wickra-lib/wickra/compare/v0.6.9...v0.7.0
+[0.6.9]: https://github.com/wickra-lib/wickra/compare/v0.6.8...v0.6.9
 [0.6.8]: https://github.com/wickra-lib/wickra/compare/v0.6.7...v0.6.8
 [0.6.7]: https://github.com/wickra-lib/wickra/compare/v0.6.6...v0.6.7
 [0.6.6]: https://github.com/wickra-lib/wickra/compare/v0.6.5...v0.6.6

Cargo.lock

@@ -1944,7 +1944,7 @@ dependencies = [
 
 [[package]]
 name = "wickra"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "approx",
  "criterion",
@@ -1955,7 +1955,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-bench"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "criterion",
  "kand",
@@ -1967,7 +1967,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-core"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "approx",
  "proptest",
@@ -1977,7 +1977,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-data"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "approx",
  "csv",
@@ -1994,7 +1994,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-examples"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "serde_json",
  "tokio",
@@ -2004,7 +2004,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-node"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "napi",
  "napi-build",
@@ -2014,7 +2014,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-python"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "numpy",
  "pyo3",
@@ -2023,7 +2023,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-wasm"
-version = "0.6.8"
+version = "0.7.3"
 dependencies = [
  "console_error_panic_hook",
  "js-sys",

Cargo.toml

@@ -13,7 +13,7 @@ members = [
 exclude = ["fuzz"]
 
 [workspace.package]
-version = "0.6.8"
+version = "0.7.3"
 authors = ["kingchenc <support@wickra.org>"]
 edition = "2021"
 rust-version = "1.86"
@@ -25,7 +25,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
 categories = ["finance", "mathematics", "science"]
 
 [workspace.dependencies]
-wickra-core = { path = "crates/wickra-core", version = "0.6.8" }
+wickra-core = { path = "crates/wickra-core", version = "0.7.3" }
 
 thiserror = "2"
 rayon = "1.10"

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=479" 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=507" 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)
@@ -48,7 +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 479 indicators; start at the
+  every one of the 507 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),
@@ -66,7 +66,7 @@ an afterthought — **live, tick-by-tick data** — without giving up the breadt
 a full batch library, and without making you reimplement your indicators four
 times to get there.
 
-- **The biggest streaming-native catalogue, period.** 479 indicators across 24
+- **The biggest streaming-native catalogue, period.** 507 indicators across 24
   families — candlesticks, harmonic & chart patterns, market profile, market
   breadth, Renko/Kagi/Point&Figure bars, Ehlers DSP cycles, risk/performance
   metrics — every single one updating in **O(1) per tick**. TA-Lib ships ~150 and
@@ -77,8 +77,8 @@ times to get there.
 - **Correct by construction, not by hope.** Every `update` validates its input,
   runs a real warmup, and returns an `Option` so a single bad tick can't silently
   poison state. `batch == streaming` is **bit-exact, fuzzed and 100 %-line-covered
-  for all 479 indicators**.
-- **Orders of magnitude faster where it counts.** In streaming Wickra is **9–58×**
+  for all 507 indicators**.
+- **Orders of magnitude faster where it counts.** In streaming Wickra is **11–56×**
   faster than the only other incremental peer and **thousands of times** faster
   than recompute-on-every-tick libraries. On batch it wins several rows outright
   and trades the simple recurrences (SMA, EMA, MACD) for its guarantees — and
@@ -95,7 +95,7 @@ Every other library forces one of those compromises. Wickra doesn't:
 
 | Library          | Install     | Streaming   | Languages                   | Indicators | Active |
 |------------------|-------------|-------------|-----------------------------|-----------:|--------|
-| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Python · Node · WASM · Rust** | **479** | **yes** |
+| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Python · Node · WASM · Rust** | **507** | **yes** |
 | kand             | clean       | yes         | Python · WASM · Rust        |       ~60  | yes    |
 | ta-rs            | clean       | yes         | Rust only                   |       ~30  | stale  |
 | yata             | clean       | partial     | Rust only                   |       ~35  | yes    |
@@ -118,7 +118,7 @@ useful version of that itch is the one other people can build on too.
 ## Benchmarks
 
 Wickra updates every indicator in **O(1)** per tick. In **streaming** — the
-workload it is built for — it is **9–58× faster** than the only other incremental
+workload it is built for — it is **11–56× faster** than the only other incremental
 peer and **thousands of times** faster than recompute-on-every-tick libraries.
 **Batch** is competitive: it wins several rows outright and trades a few µs
 elsewhere for `None`-warmup, NaN-safety and bit-exact `batch == streaming`.
@@ -128,7 +128,7 @@ Full tables (Rust + Python, streaming + batch) and how to reproduce them live in
 
 ## Indicators
 
-479 streaming-first indicators across twenty-four families. Every one passes the
+507 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).
@@ -149,13 +149,13 @@ warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
 | 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, TD Camouflage, TD Clop, TD Clopwin, TD Propulsion, TD Trap, TD D-Wave, TD Moving Averages |
 | Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi, Heikin-Ashi Oscillator, Three Line Break, Smoothed Heikin-Ashi, Equivolume, CandleVolume |
 | 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 |
+| 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, Tristar, Harami Cross, Tower Top/Bottom, Dumpling Top, New Price Lines, Frying Pan Bottom |
 | 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 |
+| 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, Trade-Sign Autocorrelation, Hasbrouck Information Share |
+| 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, Estimated Leverage Ratio, OI-to-Volume Ratio, Perpetual Premium Index, Funding-Implied APR, Open-Interest Momentum |
+| Market Profile       | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range, Naked POC, Single Prints, Profile Shape, High/Low Volume Nodes, Composite Profile |
 | 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 |
@@ -237,7 +237,7 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 479 indicators
+│   ├── wickra-core/         core engine + all 507 indicators
 │   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
 │   ├── wickra-data/         CSV reader, tick aggregator, live exchange feeds
 │   └── wickra-bench/        internal cross-library benchmark harness (not published)

bindings/node/__tests__/indicators.test.js

@@ -28,6 +28,15 @@ function num(v) {
 // --- Scalar indicators: update(value) vs batch(prices) ---
 
 const scalarFactories = {
+  M2Measure: () => new wickra.M2Measure(20, 0.0, 0.02),
+  UpsidePotentialRatio: () => new wickra.UpsidePotentialRatio(20, 0.0),
+  GainToPainRatio: () => new wickra.GainToPainRatio(12),
+  CommonSenseRatio: () => new wickra.CommonSenseRatio(20),
+  KRatio: () => new wickra.KRatio(30),
+  TailRatio: () => new wickra.TailRatio(20),
+  MartinRatio: () => new wickra.MartinRatio(14),
+  BurkeRatio: () => new wickra.BurkeRatio(12),
+  SterlingRatio: () => new wickra.SterlingRatio(12),
   AUTOCORRPGRAM: () => new wickra.AUTOCORRPGRAM(10, 48),
   EVENBETTERSINE: () => new wickra.EVENBETTERSINE(40, 10),
   BANDPASS: () => new wickra.BANDPASS(20, 0.3),
@@ -386,6 +395,15 @@ const candleScalar = {
   TDDWave: { make: () => new wickra.TDDWave(2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   HeikinAshiOscillator: { make: () => new wickra.HeikinAshiOscillator(5), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   ThreeLineBreak: { make: () => new wickra.ThreeLineBreak(3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Tristar: { make: () => new wickra.Tristar(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HaramiCross: { make: () => new wickra.HaramiCross(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TowerTopBottom: { make: () => new wickra.TowerTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DumplingTop: { make: () => new wickra.DumplingTop(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  NewPriceLines: { make: () => new wickra.NewPriceLines(5), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  FryPanBottom: { make: () => new wickra.FryPanBottom(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  NakedPoc: { make: () => new wickra.NakedPoc(20, 24), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
+  SinglePrints: { make: () => new wickra.SinglePrints(20, 24), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  ProfileShape: { make: () => new wickra.ProfileShape(20, 24), step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
 };
 
 for (const [name, d] of Object.entries(candleScalar)) {
@@ -491,6 +509,8 @@ const multi = {
   SmoothedHeikinAshi: { make: () => new wickra.SmoothedHeikinAshi(5), 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) },
   Equivolume: { make: () => new wickra.Equivolume(20), fields: ['height', 'width'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
   CandleVolume: { make: () => new wickra.CandleVolume(20), fields: ['body', 'width'], step: (ind, i) => ind.update(open[i], close[i], volume[i]), batch: (ind) => ind.batch(open, close, volume) },
+  HighLowVolumeNodes: { make: () => new wickra.HighLowVolumeNodes(20, 24), fields: ['hvn', 'lvn'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
+  CompositeProfile: { make: () => new wickra.CompositeProfile(20, 24, 0.7), fields: ['poc', 'vah', 'val'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
 };
 
 for (const [name, d] of Object.entries(multi)) {
@@ -661,6 +681,7 @@ const pairFactories = {
   GrangerCausality: () => new wickra.GrangerCausality(60, 1),
   SpreadAr1Coefficient: () => new wickra.SpreadAr1Coefficient(40),
   KendallTau: () => new wickra.KendallTau(20),
+  HasbrouckInformationShare: () => new wickra.HasbrouckInformationShare(2),
 };
 
 for (const [name, make] of Object.entries(pairFactories)) {
@@ -1264,7 +1285,7 @@ test('vpin / amihud / roll reference + streaming matches batch', () => {
   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)]) {
+  for (const make of [() => new wickra.Vpin(8, 5), () => new wickra.AmihudIlliquidity(14), () => new wickra.RollMeasure(14), () => new wickra.TradeSignAutocorrelation(10), () => new wickra.Pin(10)]) {
     const batch = make().batch(price, size, isBuy);
     const streamer = make();
     assert.equal(batch.length, n);
@@ -1273,6 +1294,16 @@ test('vpin / amihud / roll reference + streaming matches batch', () => {
       assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
     }
   }
+  // Trade-sign autocorrelation: alternating signs -> -1, all buys -> +1.
+  let tsac = null;
+  const tsacInd = new wickra.TradeSignAutocorrelation(10);
+  for (let i = 0; i < 20; i++) tsac = tsacInd.update(100, 1, i % 2 === 0);
+  assert.ok(Math.abs(tsac - -1.0) < 1e-12);
+  // PIN: one-sided flow -> 1, balanced flow -> 0.
+  let pin = null;
+  const pinInd = new wickra.Pin(10);
+  for (let i = 0; i < 20; i++) pin = pinInd.update(100, 1, true);
+  assert.ok(Math.abs(pin - 1.0) < 1e-12);
 });
 
 test('price-impact indicators reference values', () => {
@@ -1426,6 +1457,56 @@ test('derivatives reject bad input', () => {
   assert.throws(() => new wickra.FundingBasis().update(100, 0));
 });
 
+test('B16 derivatives reference values', () => {
+  // Estimated leverage: oi / (long + short) = 200 / 100 = 2.
+  assert.ok(Math.abs(new wickra.EstimatedLeverageRatio().update(200, 60, 40) - 2.0) < 1e-12);
+  // OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
+  assert.ok(Math.abs(new wickra.OiToVolumeRatio().update(100, 30, 20) - 2.0) < 1e-12);
+  // Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
+  assert.ok(Math.abs(new wickra.PerpetualPremiumIndex().update(100.5, 100.0) - 0.005) < 1e-12);
+  // Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
+  assert.ok(Math.abs(new wickra.FundingImpliedApr(1095).update(0.0001) - 0.1095) < 1e-12);
+  // Open-interest momentum (period 2): warmup then ROC% = 100*(120 - 100)/100 = 20.
+  const oim = new wickra.OpenInterestMomentum(2);
+  assert.equal(oim.update(100), null);
+  assert.equal(oim.update(110), null);
+  assert.ok(Math.abs(oim.update(120) - 20.0) < 1e-12);
+});
+
+test('B16 derivatives streaming matches batch', () => {
+  const n = 30;
+  const oi = Array.from({ length: n }, (_, i) => 1000 + 50 * Math.sin(i * 0.3));
+  const longSz = Array.from({ length: n }, (_, i) => 600 + 20 * Math.cos(i * 0.2));
+  const shortSz = Array.from({ length: n }, (_, i) => 400 + 15 * Math.sin(i * 0.4));
+  const buy = Array.from({ length: n }, (_, i) => 300 + 10 * Math.sin(i * 0.5));
+  const sell = Array.from({ length: n }, (_, i) => 250 + 12 * Math.cos(i * 0.35));
+  const index = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.2));
+  const mark = Array.from({ length: n }, (_, i) => index[i] + 0.05 * Math.cos(i * 0.3));
+  const rate = Array.from({ length: n }, (_, i) => 0.0001 * Math.sin(i * 0.3));
+  const cmp = (batch, s, i) =>
+    assert.ok((s === null && Number.isNaN(batch[i])) || Math.abs(s - batch[i]) < 1e-12, `mismatch at ${i}`);
+
+  let b = new wickra.EstimatedLeverageRatio().batch(oi, longSz, shortSz);
+  let st = new wickra.EstimatedLeverageRatio();
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], longSz[i], shortSz[i]), i);
+
+  b = new wickra.OiToVolumeRatio().batch(oi, buy, sell);
+  st = new wickra.OiToVolumeRatio();
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], buy[i], sell[i]), i);
+
+  b = new wickra.PerpetualPremiumIndex().batch(mark, index);
+  st = new wickra.PerpetualPremiumIndex();
+  for (let i = 0; i < n; i++) cmp(b, st.update(mark[i], index[i]), i);
+
+  b = new wickra.FundingImpliedApr(1095).batch(rate);
+  st = new wickra.FundingImpliedApr(1095);
+  for (let i = 0; i < n; i++) cmp(b, st.update(rate[i]), i);
+
+  b = new wickra.OpenInterestMomentum(10).batch(oi);
+  st = new wickra.OpenInterestMomentum(10);
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i]), i);
+});
+
 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.

bindings/node/index.d.ts

@@ -409,6 +409,15 @@ export interface VolumeProfileValue {
   priceHigh: number
   bins: Array<number>
 }
+export interface HighLowVolumeNodesValue {
+  hvn: number
+  lvn: number
+}
+export interface CompositeProfileValue {
+  poc: number
+  vah: number
+  val: number
+}
 export interface TpoProfileValue {
   priceLow: number
   priceHigh: number
@@ -1167,6 +1176,87 @@ export declare class UNIVERSALOSC {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type SterlingRatioNode = SterlingRatio
+export declare class SterlingRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type BurkeRatioNode = BurkeRatio
+export declare class BurkeRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type MartinRatioNode = MartinRatio
+export declare class MartinRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type TailRatioNode = TailRatio
+export declare class TailRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type KRatioNode = KRatio
+export declare class KRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type CommonSenseRatioNode = CommonSenseRatio
+export declare class CommonSenseRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type GainToPainRatioNode = GainToPainRatio
+export declare class GainToPainRatio {
+  constructor(period: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type UpsidePotentialRatioNode = UpsidePotentialRatio
+export declare class UpsidePotentialRatio {
+  constructor(period: number, mar: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type M2MeasureNode = M2Measure
+export declare class M2Measure {
+  constructor(period: number, riskFree: number, benchmarkStddev: number)
+  update(value: number): number | null
+  batch(prices: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type BandpassFilterNode = BANDPASS
 export declare class BANDPASS {
   constructor(period: number, bandwidth: number)
@@ -1449,6 +1539,19 @@ export declare class BetaNeutralSpread {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type HasbrouckInformationShareNode = HasbrouckInformationShare
+export declare class HasbrouckInformationShare {
+  constructor(period: number)
+  update(x: number, y: number): number | null
+  /**
+   * Batch over two equally-sized arrays. Returns a length-`n` array
+   * with `NaN` for warmup positions.
+   */
+  batch(x: Array<number>, y: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type PairSpreadZScoreNode = PairSpreadZScore
 /**
  * Pair spread z-score: two ctor params (`betaPeriod`, `zPeriod`), one `(a, b)`
@@ -3421,6 +3524,33 @@ export declare class CandleVolume {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type FryPanBottomNode = FryPanBottom
+export declare class FryPanBottom {
+  constructor(period: number)
+  update(high: number, low: number, close: number): number | null
+  batch(high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type DumplingTopNode = DumplingTop
+export declare class DumplingTop {
+  constructor(period: number)
+  update(high: number, low: number, close: number): number | null
+  batch(high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type NewPriceLinesNode = NewPriceLines
+export declare class NewPriceLines {
+  constructor(count: number)
+  update(high: number, low: number, close: number): number | null
+  batch(high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type ValueAreaNode = ValueArea
 export declare class ValueArea {
   constructor(period: number, binCount: number, valueAreaPct: number)
@@ -3430,6 +3560,51 @@ export declare class ValueArea {
   update(high: number, low: number, volume: number): ValueAreaValue | null
   batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
 }
+export type NakedPocNode = NakedPoc
+export declare class NakedPoc {
+  constructor(sessionLen: number, binCount: number)
+  update(high: number, low: number, close: number, volume: number): number | null
+  batch(high: Array<number>, low: Array<number>, close: Array<number>, volume: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type SinglePrintsNode = SinglePrints
+export declare class SinglePrints {
+  constructor(period: number, binCount: number)
+  update(high: number, low: number): number | null
+  batch(high: Array<number>, low: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type ProfileShapeNode = ProfileShape
+export declare class ProfileShape {
+  constructor(period: number, binCount: number)
+  update(high: number, low: number, volume: number): number | null
+  batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type HighLowVolumeNodesNode = HighLowVolumeNodes
+export declare class HighLowVolumeNodes {
+  constructor(period: number, binCount: number)
+  update(high: number, low: number, volume: number): HighLowVolumeNodesValue | null
+  batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type CompositeProfileNode = CompositeProfile
+export declare class CompositeProfile {
+  constructor(period: number, binCount: number, valueAreaPct: number)
+  update(high: number, low: number, volume: number): CompositeProfileValue | null
+  batch(high: Array<number>, low: Array<number>, volume: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type VolumeProfileNode = VolumeProfile
 export declare class VolumeProfile {
   constructor(period: number, binCount: number)
@@ -4198,6 +4373,33 @@ export declare class TDTrap {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type TristarNode = Tristar
+export declare class Tristar {
+  constructor()
+  update(open: number, high: number, low: number, close: number): number | null
+  batch(open: Array<number>, high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type HaramiCrossNode = HaramiCross
+export declare class HaramiCross {
+  constructor()
+  update(open: number, high: number, low: number, close: number): number | null
+  batch(open: Array<number>, high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type TowerTopBottomNode = TowerTopBottom
+export declare class TowerTopBottom {
+  constructor()
+  update(open: number, high: number, low: number, close: number): number | null
+  batch(open: Array<number>, high: Array<number>, low: Array<number>, close: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type OrderBookImbalanceTop1Node = OrderBookImbalanceTop1
 export declare class OrderBookImbalanceTop1 {
   constructor()
@@ -4279,6 +4481,24 @@ export declare class TradeImbalance {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type TradeSignAutocorrelationNode = TradeSignAutocorrelation
+export declare class TradeSignAutocorrelation {
+  constructor(period: number)
+  update(price: number, size: number, isBuy: boolean): number | null
+  batch(price: Array<number>, size: Array<number>, isBuy: Array<boolean>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type PinNode = Pin
+export declare class Pin {
+  constructor(window: number)
+  update(price: number, size: number, isBuy: boolean): number | null
+  batch(price: Array<number>, size: Array<number>, isBuy: Array<boolean>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type OrderFlowImbalanceNode = OrderFlowImbalance
 export declare class OrderFlowImbalance {
   constructor(period: number)
@@ -4459,6 +4679,51 @@ export declare class CalendarSpread {
   isReady(): boolean
   warmupPeriod(): number
 }
+export type EstimatedLeverageRatioNode = EstimatedLeverageRatio
+export declare class EstimatedLeverageRatio {
+  constructor()
+  update(openInterest: number, longSize: number, shortSize: number): number | null
+  batch(openInterest: Array<number>, longSize: Array<number>, shortSize: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type OiToVolumeRatioNode = OiToVolumeRatio
+export declare class OiToVolumeRatio {
+  constructor()
+  update(openInterest: number, takerBuyVolume: number, takerSellVolume: number): number | null
+  batch(openInterest: Array<number>, takerBuyVolume: Array<number>, takerSellVolume: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type PerpetualPremiumIndexNode = PerpetualPremiumIndex
+export declare class PerpetualPremiumIndex {
+  constructor()
+  update(markPrice: number, indexPrice: number): number | null
+  batch(markPrice: Array<number>, indexPrice: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type FundingImpliedAprNode = FundingImpliedApr
+export declare class FundingImpliedApr {
+  constructor(intervalsPerYear: number)
+  update(fundingRate: number): number | null
+  batch(fundingRate: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
+export type OpenInterestMomentumNode = OpenInterestMomentum
+export declare class OpenInterestMomentum {
+  constructor(period: number)
+  update(openInterest: number): number | null
+  batch(openInterest: Array<number>): Array<number>
+  reset(): void
+  isReady(): boolean
+  warmupPeriod(): number
+}
 export type AdvanceDeclineNode = AdvanceDecline
 export declare class AdvanceDecline {
   constructor()

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-darwin-arm64",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-arm64.node",
   "files": [

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-darwin-x64",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-x64.node",
   "files": [

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-linux-arm64-gnu",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-arm64-gnu.node",
   "files": [

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-linux-x64-gnu",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-x64-gnu.node",
   "files": [

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-win32-arm64-msvc",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-arm64-msvc.node",
   "files": [

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

@@ -1,6 +1,6 @@
 {
   "name": "wickra-win32-x64-msvc",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-x64-msvc.node",
   "files": [

bindings/node/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "wickra",
-      "version": "0.6.8",
+      "version": "0.7.3",
       "license": "MIT OR Apache-2.0",
       "devDependencies": {
         "@napi-rs/cli": "^2.18.0"
@@ -15,12 +15,12 @@
         "node": ">= 18"
       },
       "optionalDependencies": {
-        "wickra-darwin-arm64": "0.6.8",
-        "wickra-darwin-x64": "0.6.8",
-        "wickra-linux-arm64-gnu": "0.6.8",
-        "wickra-linux-x64-gnu": "0.6.8",
-        "wickra-win32-arm64-msvc": "0.6.8",
-        "wickra-win32-x64-msvc": "0.6.8"
+        "wickra-darwin-arm64": "0.7.3",
+        "wickra-darwin-x64": "0.7.3",
+        "wickra-linux-arm64-gnu": "0.7.3",
+        "wickra-linux-x64-gnu": "0.7.3",
+        "wickra-win32-arm64-msvc": "0.7.3",
+        "wickra-win32-x64-msvc": "0.7.3"
       }
     },
     "node_modules/@napi-rs/cli": {
@@ -41,8 +41,8 @@
       }
     },
     "node_modules/wickra-darwin-arm64": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.7.3.tgz",
       "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
       "cpu": [
         "arm64"
@@ -57,8 +57,8 @@
       }
     },
     "node_modules/wickra-darwin-x64": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.7.3.tgz",
       "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
       "cpu": [
         "x64"
@@ -73,8 +73,8 @@
       }
     },
     "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.7.3.tgz",
       "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
       "cpu": [
         "arm64"
@@ -89,8 +89,8 @@
       }
     },
     "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.7.3.tgz",
       "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
       "cpu": [
         "x64"
@@ -105,8 +105,8 @@
       }
     },
     "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.7.3.tgz",
       "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
       "cpu": [
         "arm64"
@@ -121,8 +121,8 @@
       }
     },
     "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.6.8",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.6.8.tgz",
+      "version": "0.7.3",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.7.3.tgz",
       "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
       "cpu": [
         "x64"

bindings/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra",
-  "version": "0.6.8",
+  "version": "0.7.3",
   "description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
   "author": "kingchenc <support@wickra.org>",
   "main": "index.js",
@@ -47,12 +47,12 @@
     "node": ">= 18"
   },
   "optionalDependencies": {
-    "wickra-linux-x64-gnu": "0.6.8",
-    "wickra-linux-arm64-gnu": "0.6.8",
-    "wickra-darwin-x64": "0.6.8",
-    "wickra-darwin-arm64": "0.6.8",
-    "wickra-win32-x64-msvc": "0.6.8",
-    "wickra-win32-arm64-msvc": "0.6.8"
+    "wickra-linux-x64-gnu": "0.7.3",
+    "wickra-linux-arm64-gnu": "0.7.3",
+    "wickra-darwin-x64": "0.7.3",
+    "wickra-darwin-arm64": "0.7.3",
+    "wickra-win32-x64-msvc": "0.7.3",
+    "wickra-win32-arm64-msvc": "0.7.3"
   },
   "scripts": {
     "build": "napi build --platform --release",

bindings/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "wickra"
-version = "0.6.8"
+version = "0.7.3"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
 license = "MIT OR Apache-2.0"

bindings/python/python/wickra/__init__.py

@@ -25,6 +25,15 @@ from __future__ import annotations
 
 from ._wickra import (
     __version__,
+    M2Measure,
+    UpsidePotentialRatio,
+    GainToPainRatio,
+    CommonSenseRatio,
+    KRatio,
+    TailRatio,
+    MartinRatio,
+    BurkeRatio,
+    SterlingRatio,
     AUTOCORRPGRAM,
     EVENBETTERSINE,
     BANDPASS,
@@ -350,6 +359,11 @@ from ._wickra import (
     Equivolume,
     CandleVolume,
     # Market Profile
+    CompositeProfile,
+    HighLowVolumeNodes,
+    ProfileShape,
+    SinglePrints,
+    NakedPoc,
     ValueArea,
     VolumeProfile,
     TpoProfile,
@@ -360,6 +374,12 @@ from ._wickra import (
     KagiBars,
     PointAndFigureBars,
     # Candlestick patterns
+    TowerTopBottom,
+    HaramiCross,
+    Tristar,
+    FryPanBottom,
+    DumplingTop,
+    NewPriceLines,
     Doji,
     Hammer,
     InvertedHammer,
@@ -458,6 +478,8 @@ from ._wickra import (
     QuotedSpread,
     DepthSlope,
     # Microstructure: trade flow
+    Pin,
+    TradeSignAutocorrelation,
     RollMeasure,
     AmihudIlliquidity,
     Vpin,
@@ -465,12 +487,18 @@ from ._wickra import (
     CumulativeVolumeDelta,
     TradeImbalance,
     # Microstructure: price impact
+    HasbrouckInformationShare,
     EffectiveSpread,
     RealizedSpread,
     KylesLambda,
     # Microstructure: footprint
     Footprint,
     # Derivatives
+    OpenInterestMomentum,
+    FundingImpliedApr,
+    PerpetualPremiumIndex,
+    OiToVolumeRatio,
+    EstimatedLeverageRatio,
     FundingRate,
     FundingRateMean,
     FundingRateZScore,
@@ -533,6 +561,15 @@ from ._wickra import (
 )
 
 __all__ = [
+    "M2Measure",
+    "UpsidePotentialRatio",
+    "GainToPainRatio",
+    "CommonSenseRatio",
+    "KRatio",
+    "TailRatio",
+    "MartinRatio",
+    "BurkeRatio",
+    "SterlingRatio",
     "AUTOCORRPGRAM",
     "EVENBETTERSINE",
     "BANDPASS",
@@ -859,6 +896,11 @@ __all__ = [
     "Equivolume",
     "CandleVolume",
     # Market Profile
+    "CompositeProfile",
+    "HighLowVolumeNodes",
+    "ProfileShape",
+    "SinglePrints",
+    "NakedPoc",
     "ValueArea",
     "VolumeProfile",
     "TpoProfile",
@@ -869,6 +911,12 @@ __all__ = [
     "KagiBars",
     "PointAndFigureBars",
     # Candlestick patterns
+    "TowerTopBottom",
+    "HaramiCross",
+    "Tristar",
+    "FryPanBottom",
+    "DumplingTop",
+    "NewPriceLines",
     "Doji",
     "Hammer",
     "InvertedHammer",
@@ -967,6 +1015,8 @@ __all__ = [
     "QuotedSpread",
     "DepthSlope",
     # Microstructure: trade flow
+    "Pin",
+    "TradeSignAutocorrelation",
     "RollMeasure",
     "AmihudIlliquidity",
     "Vpin",
@@ -974,12 +1024,18 @@ __all__ = [
     "CumulativeVolumeDelta",
     "TradeImbalance",
     # Microstructure: price impact
+    "HasbrouckInformationShare",
     "EffectiveSpread",
     "RealizedSpread",
     "KylesLambda",
     # Microstructure: footprint
     "Footprint",
     # Derivatives
+    "OpenInterestMomentum",
+    "FundingImpliedApr",
+    "PerpetualPremiumIndex",
+    "OiToVolumeRatio",
+    "EstimatedLeverageRatio",
     "FundingRate",
     "FundingRateMean",
     "FundingRateZScore",

bindings/python/tests/test_new_indicators.py

@@ -45,6 +45,15 @@ def ohlcv() -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
 # --- Scalar (f64 -> f64) indicators ---------------------------------------
 
 SCALAR = [
+    (ta.M2Measure, (20, 0.0, 0.02)),
+    (ta.UpsidePotentialRatio, (20, 0.0)),
+    (ta.GainToPainRatio, (12,)),
+    (ta.CommonSenseRatio, (20,)),
+    (ta.KRatio, (30,)),
+    (ta.TailRatio, (20,)),
+    (ta.MartinRatio, (14,)),
+    (ta.BurkeRatio, (12,)),
+    (ta.SterlingRatio, (12,)),
     (ta.AUTOCORRPGRAM, (10, 48)),
     (ta.EVENBETTERSINE, (40, 10)),
     (ta.BANDPASS, (20, 0.3)),
@@ -217,6 +226,7 @@ def test_scalar_streaming_matches_batch(cls, args, sine_prices):
 # --- Two-series (asset, benchmark) indicators -----------------------------
 
 PAIR = [
+    (ta.HasbrouckInformationShare, (2,)),
     (ta.KendallTau, (20,)),
     (ta.SpreadAr1Coefficient, (40,)),
     (ta.GrangerCausality, (60, 1)),
@@ -382,6 +392,42 @@ def test_relative_strength_streaming_matches_batch():
 # 6-tuple candle; the batch helper takes only the columns it needs.
 
 CANDLE_SCALAR = {
+    "ProfileShape": (
+        lambda: ta.ProfileShape(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+    ),
+    "SinglePrints": (
+        lambda: ta.SinglePrints(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+    ),
+    "NakedPoc": (
+        lambda: ta.NakedPoc(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, c, v),
+    ),
+    "FryPanBottom": (
+        lambda: ta.FryPanBottom(9),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "NewPriceLines": (
+        lambda: ta.NewPriceLines(5),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "DumplingTop": (
+        lambda: ta.DumplingTop(9),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "TowerTopBottom": (
+        lambda: ta.TowerTopBottom(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "HaramiCross": (
+        lambda: ta.HaramiCross(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "Tristar": (
+        lambda: ta.Tristar(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
     "ThreeLineBreak": (
         lambda: ta.ThreeLineBreak(3),
         lambda ind, h, l, c, v: ind.batch(h, l, c),
@@ -984,6 +1030,16 @@ def test_candle_scalar_streaming_matches_batch(name, ohlcv):
 # --- Candle-input, multi-output indicators --------------------------------
 
 MULTI = {
+    "CompositeProfile": (
+        lambda: ta.CompositeProfile(20, 24, 0.7),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        3,
+    ),
+    "HighLowVolumeNodes": (
+        lambda: ta.HighLowVolumeNodes(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        2,
+    ),
     "CandleVolume": (
         lambda: ta.CandleVolume(20),
         lambda ind, h, l, c, v: ind.batch(c, c, v),
@@ -3278,6 +3334,54 @@ def test_equivolume_reference():
 def test_candle_volume_reference():
     t = ta.CandleVolume(20)
 
+
+def test_tristar_reference():
+    t = ta.Tristar()
+    assert t.update((100.0, 101.0, 99.0, 100.02, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 106.0, 104.0, 105.02, 1.0, 1)) == pytest.approx(0.0)
+    assert t.update((100.0, 101.0, 99.0, 100.02, 1.0, 2)) == pytest.approx(-1.0)
+
+
+def test_harami_cross_reference():
+    t = ta.HaramiCross()
+    assert t.update((110.0, 110.2, 99.8, 100.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 106.0, 104.0, 105.02, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_tower_top_bottom_reference():
+    t = ta.TowerTopBottom()
+    assert t.update((100.0, 110.1, 99.9, 110.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 107.0, 103.0, 105.1, 1.0, 1)) == pytest.approx(0.0)
+    assert t.update((110.0, 110.1, 99.9, 100.0, 1.0, 2)) == pytest.approx(-1.0)
+
+
+
+def test_hasbrouck_information_share_reference():
+    t = ta.HasbrouckInformationShare(2)
+    assert t.update(7.0, 9.0) is None
+    assert t.update(7.0, 9.0) is None
+    assert t.update(7.0, 9.0) == pytest.approx(0.5)
+
+
+def test_naked_poc_reference():
+    t = ta.NakedPoc(20, 24)
+
+
+def test_single_prints_reference():
+    t = ta.SinglePrints(20, 24)
+
+
+def test_profile_shape_reference():
+    t = ta.ProfileShape(20, 24)
+
+
+def test_high_low_volume_nodes_reference():
+    t = ta.HighLowVolumeNodes(20, 24)
+
+
+def test_composite_profile_reference():
+    t = ta.CompositeProfile(20, 24, 0.7)
+
 # --- Lifecycle ------------------------------------------------------------
 
 
@@ -3618,6 +3722,8 @@ def test_tradeflow_indicators_streaming_equals_batch():
         lambda: ta.Vpin(8.0, 5),
         lambda: ta.AmihudIlliquidity(14),
         lambda: ta.RollMeasure(14),
+        lambda: ta.TradeSignAutocorrelation(10),
+        lambda: ta.Pin(10),
     ):
         batch = make().batch(price, size, is_buy)
         streamer = make()
@@ -3629,6 +3735,34 @@ def test_tradeflow_indicators_streaming_equals_batch():
         assert _eq_nan(batch, streamed)
 
 
+def test_trade_sign_autocorrelation_reference():
+    # Perfectly alternating aggressor signs -> lag-1 autocorrelation -1.
+    t = ta.TradeSignAutocorrelation(10)
+    last = None
+    for i in range(20):
+        last = t.update(100.0, 1.0, i % 2 == 0)
+    assert last == pytest.approx(-1.0)
+    # All buys -> perfectly persistent flow -> +1.
+    t2 = ta.TradeSignAutocorrelation(10)
+    for _ in range(20):
+        last2 = t2.update(100.0, 1.0, True)
+    assert last2 == pytest.approx(1.0)
+
+
+def test_pin_reference():
+    # One-sided flow (all buys) -> maximally informed -> PIN 1.
+    p = ta.Pin(10)
+    last = None
+    for _ in range(20):
+        last = p.update(100.0, 1.0, True)
+    assert last == pytest.approx(1.0)
+    # Balanced flow -> uninformed -> PIN 0.
+    p2 = ta.Pin(10)
+    for i in range(20):
+        last2 = p2.update(100.0, 1.0, i % 2 == 0)
+    assert last2 == pytest.approx(0.0)
+
+
 def test_price_impact_indicators_streaming_equals_batch():
     n = 40
     mid = np.array([100.0 + 0.5 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
@@ -3999,6 +4133,71 @@ def test_basis_indicators_streaming_equals_batch():
     assert _eq_nan(batch, streamed)
 
 
+def test_b16_derivatives_reference():
+    # Estimated leverage: oi / (long + short) = 200 / 100 = 2.
+    assert ta.EstimatedLeverageRatio().update(200.0, 60.0, 40.0) == pytest.approx(2.0)
+    # OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
+    assert ta.OiToVolumeRatio().update(100.0, 30.0, 20.0) == pytest.approx(2.0)
+    # Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
+    assert ta.PerpetualPremiumIndex().update(100.5, 100.0) == pytest.approx(0.005)
+    # Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
+    assert ta.FundingImpliedApr(1095.0).update(0.0001) == pytest.approx(0.1095)
+    # Open-interest momentum (period 2): warmup then ROC% = 100*(120-100)/100 = 20.
+    oim = ta.OpenInterestMomentum(2)
+    assert oim.update(100.0) is None
+    assert oim.update(110.0) is None
+    assert oim.update(120.0) == pytest.approx(20.0)
+
+
+def test_b16_derivatives_streaming_equals_batch():
+    n = 40
+    oi = np.array([1000.0 + 50.0 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
+    long_sz = np.array([600.0 + 20.0 * math.cos(i * 0.2) for i in range(n)], dtype=np.float64)
+    short_sz = np.array([400.0 + 15.0 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
+    buy = np.array([300.0 + 10.0 * math.sin(i * 0.5) for i in range(n)], dtype=np.float64)
+    sell = np.array([250.0 + 12.0 * math.cos(i * 0.35) for i in range(n)], dtype=np.float64)
+    index = np.array([100.0 + math.sin(i * 0.2) for i in range(n)], dtype=np.float64)
+    mark = np.array([index[i] + 0.05 * math.cos(i * 0.3) for i in range(n)], dtype=np.float64)
+    rate = np.array([0.0001 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
+
+    # EstimatedLeverageRatio; update(open_interest, long_size, short_size).
+    batch = ta.EstimatedLeverageRatio().batch(oi, long_sz, short_sz)
+    streamer = ta.EstimatedLeverageRatio()
+    streamed = np.array(
+        [streamer.update(oi[i], long_sz[i], short_sz[i]) for i in range(n)], dtype=np.float64
+    )
+    assert batch.shape == (n,)
+    assert _eq_nan(batch, streamed)
+
+    # OiToVolumeRatio; update(open_interest, taker_buy_volume, taker_sell_volume).
+    batch = ta.OiToVolumeRatio().batch(oi, buy, sell)
+    streamer = ta.OiToVolumeRatio()
+    streamed = np.array(
+        [streamer.update(oi[i], buy[i], sell[i]) for i in range(n)], dtype=np.float64
+    )
+    assert _eq_nan(batch, streamed)
+
+    # PerpetualPremiumIndex; update(mark_price, index_price).
+    batch = ta.PerpetualPremiumIndex().batch(mark, index)
+    streamer = ta.PerpetualPremiumIndex()
+    streamed = np.array(
+        [streamer.update(mark[i], index[i]) for i in range(n)], dtype=np.float64
+    )
+    assert _eq_nan(batch, streamed)
+
+    # FundingImpliedApr; update(funding_rate).
+    batch = ta.FundingImpliedApr(1095.0).batch(rate)
+    streamer = ta.FundingImpliedApr(1095.0)
+    streamed = np.array([streamer.update(rate[i]) for i in range(n)], dtype=np.float64)
+    assert _eq_nan(batch, streamed)
+
+    # OpenInterestMomentum; update(open_interest).
+    batch = ta.OpenInterestMomentum(10).batch(oi)
+    streamer = ta.OpenInterestMomentum(10)
+    streamed = np.array([streamer.update(oi[i]) for i in range(n)], dtype=np.float64)
+    assert _eq_nan(batch, streamed)
+
+
 # --- Alt-Chart Bars ------------------------------------------------------
 
 

bindings/wasm/src/lib.rs

@@ -563,6 +563,11 @@ wasm_pair_indicator!(
     "BetaNeutralSpread",
     wc::BetaNeutralSpread
 );
+wasm_pair_indicator!(
+    WasmHasbrouckInformationShare,
+    "HasbrouckInformationShare",
+    wc::HasbrouckInformationShare
+);
 
 // ---------- PairSpreadZScore (two params) ----------
 
@@ -8521,6 +8526,298 @@ impl WasmValueArea {
     }
 }
 
+// Naked POC: most recent untouched point-of-control level (Candle -> f64).
+#[wasm_bindgen(js_name = NakedPoc)]
+pub struct WasmNakedPoc {
+    inner: wc::NakedPoc,
+}
+
+#[wasm_bindgen(js_class = NakedPoc)]
+impl WasmNakedPoc {
+    #[wasm_bindgen(constructor)]
+    pub fn new(session_len: usize, bin_count: usize) -> Result<WasmNakedPoc, JsError> {
+        Ok(Self {
+            inner: wc::NakedPoc::new(session_len, bin_count).map_err(map_err)?,
+        })
+    }
+    pub fn update(
+        &mut self,
+        high: f64,
+        low: f64,
+        close: f64,
+        volume: f64,
+    ) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(make_candle(high, low, close, volume)?))
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        close: &[f64],
+        volume: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != close.len() || close.len() != volume.len() {
+            return Err(JsError::new(
+                "high, low, close, volume must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(close.len());
+        for i in 0..close.len() {
+            out.push(
+                self.inner
+                    .update(make_candle(high[i], low[i], close[i], volume[i])?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// Single Prints: count of single-print price levels (Candle -> f64).
+#[wasm_bindgen(js_name = SinglePrints)]
+pub struct WasmSinglePrints {
+    inner: wc::SinglePrints,
+}
+
+#[wasm_bindgen(js_class = SinglePrints)]
+impl WasmSinglePrints {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize, bin_count: usize) -> Result<WasmSinglePrints, JsError> {
+        Ok(Self {
+            inner: wc::SinglePrints::new(period, bin_count).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, high: f64, low: f64) -> Result<Option<f64>, JsError> {
+        let mid = f64::midpoint(high, low);
+        Ok(self
+            .inner
+            .update(wc::Candle::new(mid, high, low, mid, 0.0, 0).map_err(map_err)?))
+    }
+    pub fn batch(&mut self, high: &[f64], low: &[f64]) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() {
+            return Err(JsError::new("high and low must be equal length"));
+        }
+        let mut out = Vec::with_capacity(high.len());
+        for i in 0..high.len() {
+            let mid = f64::midpoint(high[i], low[i]);
+            out.push(
+                self.inner
+                    .update(wc::Candle::new(mid, high[i], low[i], mid, 0.0, 0).map_err(map_err)?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// Profile Shape: b/P/D classification as a numeric code (Candle -> f64).
+#[wasm_bindgen(js_name = ProfileShape)]
+pub struct WasmProfileShape {
+    inner: wc::ProfileShape,
+}
+
+#[wasm_bindgen(js_class = ProfileShape)]
+impl WasmProfileShape {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize, bin_count: usize) -> Result<WasmProfileShape, JsError> {
+        Ok(Self {
+            inner: wc::ProfileShape::new(period, bin_count).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<Option<f64>, JsError> {
+        let mid = f64::midpoint(high, low);
+        Ok(self
+            .inner
+            .update(wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?))
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        volume: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != volume.len() {
+            return Err(JsError::new("high, low, volume must be equal length"));
+        }
+        let mut out = Vec::with_capacity(high.len());
+        for i in 0..high.len() {
+            let mid = f64::midpoint(high[i], low[i]);
+            out.push(
+                self.inner
+                    .update(
+                        wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0)
+                            .map_err(map_err)?,
+                    )
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// High/Low Volume Nodes: highest- and lowest-volume price nodes (Candle -> struct).
+#[wasm_bindgen(js_name = HighLowVolumeNodes)]
+pub struct WasmHighLowVolumeNodes {
+    inner: wc::HighLowVolumeNodes,
+}
+
+#[wasm_bindgen(js_class = HighLowVolumeNodes)]
+impl WasmHighLowVolumeNodes {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize, bin_count: usize) -> Result<WasmHighLowVolumeNodes, JsError> {
+        Ok(Self {
+            inner: wc::HighLowVolumeNodes::new(period, bin_count).map_err(map_err)?,
+        })
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        volume: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != volume.len() {
+            return Err(JsError::new("high, low, volume must be equal length"));
+        }
+        let n = high.len();
+        let mut out = vec![f64::NAN; n * 2];
+        for i in 0..n {
+            let mid = f64::midpoint(high[i], low[i]);
+            let c = wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
+            if let Some(o) = self.inner.update(c) {
+                out[i * 2] = o.hvn;
+                out[i * 2 + 1] = o.lvn;
+            }
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    /// Streaming update. Returns `{ hvn, lvn }` once warm, else `null`.
+    pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<JsValue, JsError> {
+        let mid = f64::midpoint(high, low);
+        let c = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
+        Ok(match self.inner.update(c) {
+            Some(o) => {
+                let obj = Object::new();
+                Reflect::set(&obj, &"hvn".into(), &o.hvn.into()).ok();
+                Reflect::set(&obj, &"lvn".into(), &o.lvn.into()).ok();
+                obj.into()
+            }
+            None => JsValue::NULL,
+        })
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// Composite Profile: multi-session composite volume profile (Candle -> struct).
+#[wasm_bindgen(js_name = CompositeProfile)]
+pub struct WasmCompositeProfile {
+    inner: wc::CompositeProfile,
+}
+
+#[wasm_bindgen(js_class = CompositeProfile)]
+impl WasmCompositeProfile {
+    #[wasm_bindgen(constructor)]
+    pub fn new(
+        period: usize,
+        bin_count: usize,
+        value_area_pct: f64,
+    ) -> Result<WasmCompositeProfile, JsError> {
+        Ok(Self {
+            inner: wc::CompositeProfile::new(period, bin_count, value_area_pct).map_err(map_err)?,
+        })
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        volume: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != volume.len() {
+            return Err(JsError::new("high, low, volume must be equal length"));
+        }
+        let n = high.len();
+        let mut out = vec![f64::NAN; n * 3];
+        for i in 0..n {
+            let mid = f64::midpoint(high[i], low[i]);
+            let c = wc::Candle::new(mid, high[i], low[i], mid, volume[i], 0).map_err(map_err)?;
+            if let Some(o) = self.inner.update(c) {
+                out[i * 3] = o.poc;
+                out[i * 3 + 1] = o.vah;
+                out[i * 3 + 2] = o.val;
+            }
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    /// Streaming update. Returns `{ poc, vah, val }` once warm, else `null`.
+    pub fn update(&mut self, high: f64, low: f64, volume: f64) -> Result<JsValue, JsError> {
+        let mid = f64::midpoint(high, low);
+        let c = wc::Candle::new(mid, high, low, mid, volume, 0).map_err(map_err)?;
+        Ok(match self.inner.update(c) {
+            Some(o) => {
+                let obj = Object::new();
+                Reflect::set(&obj, &"poc".into(), &o.poc.into()).ok();
+                Reflect::set(&obj, &"vah".into(), &o.vah.into()).ok();
+                Reflect::set(&obj, &"val".into(), &o.val.into()).ok();
+                obj.into()
+            }
+            None => JsValue::NULL,
+        })
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 #[wasm_bindgen(js_name = VolumeProfile)]
 pub struct WasmVolumeProfile {
     inner: wc::VolumeProfile,
@@ -9050,6 +9347,9 @@ wasm_candle_pattern!(WasmTdClop, wc::TdClop, TDClop);
 wasm_candle_pattern!(WasmTdClopwin, wc::TdClopwin, TDClopwin);
 wasm_candle_pattern!(WasmTdPropulsion, wc::TdPropulsion, TDPropulsion);
 wasm_candle_pattern!(WasmTdTrap, wc::TdTrap, TDTrap);
+wasm_candle_pattern!(WasmTristar, wc::Tristar, Tristar);
+wasm_candle_pattern!(WasmHaramiCross, wc::HaramiCross, HaramiCross);
+wasm_candle_pattern!(WasmTowerTopBottom, wc::TowerTopBottom, TowerTopBottom);
 
 // ============================== Microstructure: Order Book ==============================
 //
@@ -9276,6 +9576,66 @@ impl WasmTradeImbalance {
     }
 }
 
+// Trade-sign autocorrelation carries a `period` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = TradeSignAutocorrelation)]
+pub struct WasmTradeSignAutocorrelation {
+    inner: wc::TradeSignAutocorrelation,
+}
+
+#[wasm_bindgen(js_class = TradeSignAutocorrelation)]
+impl WasmTradeSignAutocorrelation {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize) -> Result<WasmTradeSignAutocorrelation, JsError> {
+        Ok(Self {
+            inner: wc::TradeSignAutocorrelation::new(period).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// PIN carries a `window` parameter, so it is hand-written.
+#[wasm_bindgen(js_name = Pin)]
+pub struct WasmPin {
+    inner: wc::Pin,
+}
+
+#[wasm_bindgen(js_class = Pin)]
+impl WasmPin {
+    #[wasm_bindgen(constructor)]
+    pub fn new(window: usize) -> Result<WasmPin, JsError> {
+        Ok(Self {
+            inner: wc::Pin::new(window).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 // Order Flow Imbalance: order-book input with a `period` parameter.
 #[wasm_bindgen(js_name = OrderFlowImbalance)]
 pub struct WasmOrderFlowImbalance {
@@ -9865,6 +10225,50 @@ fn deriv_taker(
     .map_err(map_err)
 }
 
+fn deriv_oi_long_short(
+    open_interest: f64,
+    long_size: f64,
+    short_size: f64,
+) -> Result<wc::DerivativesTick, JsError> {
+    wc::DerivativesTick::new(
+        0.0,
+        1.0,
+        1.0,
+        1.0,
+        open_interest,
+        long_size,
+        short_size,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0,
+    )
+    .map_err(map_err)
+}
+
+fn deriv_oi_taker(
+    open_interest: f64,
+    taker_buy_volume: f64,
+    taker_sell_volume: f64,
+) -> Result<wc::DerivativesTick, JsError> {
+    wc::DerivativesTick::new(
+        0.0,
+        1.0,
+        1.0,
+        1.0,
+        open_interest,
+        0.0,
+        0.0,
+        taker_buy_volume,
+        taker_sell_volume,
+        0.0,
+        0.0,
+        0,
+    )
+    .map_err(map_err)
+}
+
 fn deriv_liquidation(
     long_liquidation: f64,
     short_liquidation: f64,
@@ -10188,6 +10592,195 @@ impl WasmCalendarSpread {
     }
 }
 
+// ---------- Estimated Leverage Ratio ----------
+
+#[wasm_bindgen(js_name = EstimatedLeverageRatio)]
+pub struct WasmEstimatedLeverageRatio {
+    inner: wc::EstimatedLeverageRatio,
+}
+
+impl Default for WasmEstimatedLeverageRatio {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[wasm_bindgen(js_class = EstimatedLeverageRatio)]
+impl WasmEstimatedLeverageRatio {
+    #[wasm_bindgen(constructor)]
+    pub fn new() -> WasmEstimatedLeverageRatio {
+        Self {
+            inner: wc::EstimatedLeverageRatio::new(),
+        }
+    }
+    pub fn update(
+        &mut self,
+        open_interest: f64,
+        long_size: f64,
+        short_size: f64,
+    ) -> Result<Option<f64>, JsError> {
+        Ok(self
+            .inner
+            .update(deriv_oi_long_short(open_interest, long_size, short_size)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- OI-to-Volume Ratio ----------
+
+#[wasm_bindgen(js_name = OiToVolumeRatio)]
+pub struct WasmOiToVolumeRatio {
+    inner: wc::OiToVolumeRatio,
+}
+
+impl Default for WasmOiToVolumeRatio {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[wasm_bindgen(js_class = OiToVolumeRatio)]
+impl WasmOiToVolumeRatio {
+    #[wasm_bindgen(constructor)]
+    pub fn new() -> WasmOiToVolumeRatio {
+        Self {
+            inner: wc::OiToVolumeRatio::new(),
+        }
+    }
+    pub fn update(
+        &mut self,
+        open_interest: f64,
+        taker_buy_volume: f64,
+        taker_sell_volume: f64,
+    ) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(deriv_oi_taker(
+            open_interest,
+            taker_buy_volume,
+            taker_sell_volume,
+        )?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- Perpetual Premium Index ----------
+
+#[wasm_bindgen(js_name = PerpetualPremiumIndex)]
+pub struct WasmPerpetualPremiumIndex {
+    inner: wc::PerpetualPremiumIndex,
+}
+
+impl Default for WasmPerpetualPremiumIndex {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[wasm_bindgen(js_class = PerpetualPremiumIndex)]
+impl WasmPerpetualPremiumIndex {
+    #[wasm_bindgen(constructor)]
+    pub fn new() -> WasmPerpetualPremiumIndex {
+        Self {
+            inner: wc::PerpetualPremiumIndex::new(),
+        }
+    }
+    pub fn update(&mut self, mark_price: f64, index_price: f64) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- Funding-Implied APR ----------
+
+#[wasm_bindgen(js_name = FundingImpliedApr)]
+pub struct WasmFundingImpliedApr {
+    inner: wc::FundingImpliedApr,
+}
+
+#[wasm_bindgen(js_class = FundingImpliedApr)]
+impl WasmFundingImpliedApr {
+    #[wasm_bindgen(constructor)]
+    pub fn new(intervals_per_year: f64) -> Result<WasmFundingImpliedApr, JsError> {
+        Ok(Self {
+            inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, funding_rate: f64) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(deriv_funding(funding_rate)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- Open-Interest Momentum ----------
+
+#[wasm_bindgen(js_name = OpenInterestMomentum)]
+pub struct WasmOpenInterestMomentum {
+    inner: wc::OpenInterestMomentum,
+}
+
+#[wasm_bindgen(js_class = OpenInterestMomentum)]
+impl WasmOpenInterestMomentum {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize) -> Result<WasmOpenInterestMomentum, JsError> {
+        Ok(Self {
+            inner: wc::OpenInterestMomentum::new(period).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, open_interest: f64) -> Result<Option<f64>, JsError> {
+        Ok(self.inner.update(deriv_oi(open_interest)?))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 // ---------- Heikin-Ashi Oscillator ----------
 
 #[wasm_bindgen(js_name = HeikinAshiOscillator)]
@@ -10488,6 +11081,150 @@ impl WasmCandleVolume {
     }
 }
 
+// ---------- Frying Pan Bottom ----------
+
+#[wasm_bindgen(js_name = FryPanBottom)]
+pub struct WasmFryPanBottom {
+    inner: wc::FryPanBottom,
+}
+
+#[wasm_bindgen(js_class = FryPanBottom)]
+impl WasmFryPanBottom {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize) -> Result<WasmFryPanBottom, JsError> {
+        Ok(Self {
+            inner: wc::FryPanBottom::new(period).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, high: f64, low: f64, close: f64) -> Result<Option<f64>, JsError> {
+        let c = make_candle(high, low, close, 0.0)?;
+        Ok(self.inner.update(c))
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        close: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != close.len() {
+            return Err(JsError::new("high, low, close must be equal length"));
+        }
+        let mut out = Vec::with_capacity(high.len());
+        for i in 0..high.len() {
+            let c = make_candle(high[i], low[i], close[i], 0.0)?;
+            out.push(self.inner.update(c).unwrap_or(f64::NAN));
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- Dumpling Top ----------
+
+#[wasm_bindgen(js_name = DumplingTop)]
+pub struct WasmDumplingTop {
+    inner: wc::DumplingTop,
+}
+
+#[wasm_bindgen(js_class = DumplingTop)]
+impl WasmDumplingTop {
+    #[wasm_bindgen(constructor)]
+    pub fn new(period: usize) -> Result<WasmDumplingTop, JsError> {
+        Ok(Self {
+            inner: wc::DumplingTop::new(period).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, high: f64, low: f64, close: f64) -> Result<Option<f64>, JsError> {
+        let c = make_candle(high, low, close, 0.0)?;
+        Ok(self.inner.update(c))
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        close: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != close.len() {
+            return Err(JsError::new("high, low, close must be equal length"));
+        }
+        let mut out = Vec::with_capacity(high.len());
+        for i in 0..high.len() {
+            let c = make_candle(high[i], low[i], close[i], 0.0)?;
+            out.push(self.inner.update(c).unwrap_or(f64::NAN));
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
+// ---------- New Price Lines ----------
+
+#[wasm_bindgen(js_name = NewPriceLines)]
+pub struct WasmNewPriceLines {
+    inner: wc::NewPriceLines,
+}
+
+#[wasm_bindgen(js_class = NewPriceLines)]
+impl WasmNewPriceLines {
+    #[wasm_bindgen(constructor)]
+    pub fn new(count: usize) -> Result<WasmNewPriceLines, JsError> {
+        Ok(Self {
+            inner: wc::NewPriceLines::new(count).map_err(map_err)?,
+        })
+    }
+    pub fn update(&mut self, high: f64, low: f64, close: f64) -> Result<Option<f64>, JsError> {
+        let c = make_candle(high, low, close, 0.0)?;
+        Ok(self.inner.update(c))
+    }
+    pub fn batch(
+        &mut self,
+        high: &[f64],
+        low: &[f64],
+        close: &[f64],
+    ) -> Result<Float64Array, JsError> {
+        if high.len() != low.len() || low.len() != close.len() {
+            return Err(JsError::new("high, low, close must be equal length"));
+        }
+        let mut out = Vec::with_capacity(high.len());
+        for i in 0..high.len() {
+            let c = make_candle(high[i], low[i], close[i], 0.0)?;
+            out.push(self.inner.update(c).unwrap_or(f64::NAN));
+        }
+        Ok(Float64Array::from(out.as_slice()))
+    }
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[wasm_bindgen(js_name = isReady)]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[wasm_bindgen(js_name = warmupPeriod)]
+    pub fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+}
+
 // ---------- Market Breadth (CrossSection input) ----------
 //
 // A breadth tick is the per-symbol state of the whole universe, passed as four
@@ -12018,6 +12755,15 @@ wasm_scalar_indicator!(WasmUniversalOscillator, "UNIVERSALOSC", wc::UniversalOsc
 wasm_scalar_indicator!(WasmBandpassFilter, "BANDPASS", wc::BandpassFilter, period: usize, bandwidth: f64);
 wasm_scalar_indicator!(WasmEvenBetterSinewave, "EVENBETTERSINE", wc::EvenBetterSinewave, hp_period: usize, ssf_length: usize);
 wasm_scalar_indicator!(WasmAutocorrelationPeriodogram, "AUTOCORRPGRAM", wc::AutocorrelationPeriodogram, min_period: usize, max_period: usize);
+wasm_scalar_indicator!(WasmSterlingRatio, "SterlingRatio", wc::SterlingRatio, period: usize);
+wasm_scalar_indicator!(WasmBurkeRatio, "BurkeRatio", wc::BurkeRatio, period: usize);
+wasm_scalar_indicator!(WasmMartinRatio, "MartinRatio", wc::MartinRatio, period: usize);
+wasm_scalar_indicator!(WasmTailRatio, "TailRatio", wc::TailRatio, period: usize);
+wasm_scalar_indicator!(WasmKRatio, "KRatio", wc::KRatio, period: usize);
+wasm_scalar_indicator!(WasmCommonSenseRatio, "CommonSenseRatio", wc::CommonSenseRatio, period: usize);
+wasm_scalar_indicator!(WasmGainToPainRatio, "GainToPainRatio", wc::GainToPainRatio, period: usize);
+wasm_scalar_indicator!(WasmUpsidePotentialRatio, "UpsidePotentialRatio", wc::UpsidePotentialRatio, period: usize, mar: f64);
+wasm_scalar_indicator!(WasmM2Measure, "M2Measure", wc::M2Measure, period: usize, risk_free: f64, benchmark_stddev: f64);
 
 // --- VolatilityCone: Candle in, struct out (current/min/median/max/percentile) ---
 

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

@@ -0,0 +1,218 @@
+//! Burke Ratio — mean return over the square root of the summed squared drawdowns.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Burke Ratio over a trailing window of `period` returns.
+///
+/// ```text
+/// equity_t = Π_{i<=t} (1 + return_i)          (compounded curve)
+/// peak_t   = max_{s<=t} equity_s
+/// dd_t     = (peak_t − equity_t) / peak_t      (fractional drawdown, >= 0)
+/// Burke    = mean(returns) / sqrt( Σ dd_t² )
+/// ```
+///
+/// The Burke Ratio divides the average per-period return by the **Euclidean norm of
+/// the drawdowns** — the square root of the *sum* of squared drawdowns. Squaring
+/// penalises deep drawdowns far more than shallow ones, and summing (rather than
+/// averaging) means the denominator grows with both the depth and the *number* of
+/// drawdowns. This makes Burke the most outlier-sensitive of Wickra's three
+/// drawdown ratios: where the [`SterlingRatio`](crate::SterlingRatio) averages raw
+/// drawdowns and shrugs off a single crater, Burke makes that crater dominate.
+/// The [`MartinRatio`](crate::MartinRatio) sits between them with a root-*mean*
+/// square of percentage drawdowns. A window that never draws down has a zero
+/// denominator and the indicator reports `0.0`.
+///
+/// The first value lands after `period` returns; each `update` rebuilds the equity
+/// curve over the window (O(period)), which is O(1) in the length of the overall
+/// series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, BurkeRatio};
+///
+/// let mut indicator = BurkeRatio::new(12).unwrap();
+/// let mut last = None;
+/// for i in 0..24 {
+///     last = indicator.update((f64::from(i) * 0.5).sin() * 0.05);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct BurkeRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl BurkeRatio {
+    /// Construct a Burke Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "burke ratio needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        #[allow(clippy::cast_precision_loss)]
+        let length = self.window.len() as f64;
+        let mut sum_return = 0.0;
+        let mut sum_drawdown_sq = 0.0;
+        let mut equity = 1.0;
+        let mut peak: f64 = 1.0;
+        for ret in &self.window {
+            sum_return += *ret;
+            equity *= 1.0 + *ret;
+            peak = peak.max(equity);
+            let drawdown = (peak - equity) / peak;
+            sum_drawdown_sq += drawdown * drawdown;
+        }
+        let denom = sum_drawdown_sq.sqrt();
+        if denom > 0.0 {
+            (sum_return / length) / denom
+        } else {
+            0.0
+        }
+    }
+}
+
+impl Indicator for BurkeRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "BurkeRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            BurkeRatio::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let br = BurkeRatio::new(12).unwrap();
+        assert_eq!(br.period(), 12);
+        assert_eq!(br.warmup_period(), 12);
+        assert_eq!(br.name(), "BurkeRatio");
+        assert!(!br.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.1, -0.1, 0.1]: dd = [0, 0.1, 0.01].
+        // Σ dd² = 0.01 + 0.0001 = 0.0101; denom = sqrt(0.0101).
+        // Burke = (0.1/3) / sqrt(0.0101).
+        let mut br = BurkeRatio::new(3).unwrap();
+        let out = br.batch(&[0.1, -0.1, 0.1]);
+        let expected = (0.1_f64 / 3.0) / (0.0101_f64).sqrt();
+        assert_relative_eq!(out[2].unwrap(), expected, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn no_drawdown_is_zero() {
+        let mut br = BurkeRatio::new(3).unwrap();
+        let last = br
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn losing_window_is_negative() {
+        let mut br = BurkeRatio::new(3).unwrap();
+        let last = br
+            .batch(&[-0.05, -0.02, -0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last < 0.0);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut br = BurkeRatio::new(3).unwrap();
+        assert_eq!(br.update(0.1), None);
+        assert_eq!(br.update(f64::NAN), None);
+        assert_eq!(br.update(-0.1), None);
+        assert!(br.update(0.1).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut br = BurkeRatio::new(3).unwrap();
+        br.batch(&[0.1, -0.1, 0.1]);
+        assert!(br.is_ready());
+        br.reset();
+        assert!(!br.is_ready());
+        assert_eq!(br.update(0.1), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.05)
+            .collect();
+        let batch = BurkeRatio::new(12).unwrap().batch(&rets);
+        let mut streamer = BurkeRatio::new(12).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,248 @@
+//! Common Sense Ratio (Schwager / Carver) — profit factor multiplied by the tail ratio.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Common Sense Ratio over a trailing window of `period` returns.
+///
+/// ```text
+/// ProfitFactor = Σ gains / Σ |losses|              over the window
+/// TailRatio    = P95(returns) / |P5(returns)|      over the window
+/// CSR          = ProfitFactor · TailRatio
+/// ```
+///
+/// The Common Sense Ratio fuses two views of a return series into one number. The
+/// [profit factor](crate::ProfitFactor) captures the *body* of the distribution —
+/// how much you make per unit you lose on the average bar. The
+/// [`TailRatio`](crate::TailRatio) captures the *extremes* — whether the largest
+/// gains outweigh the largest losses. Multiplying them produces a ratio that is
+/// only comfortably above `1.0` when a strategy wins on both fronts: a respectable
+/// profit factor can still hide catastrophic left-tail risk, and a fat right tail
+/// means little if the body bleeds. Above `1.0` the strategy is sound on a
+/// common-sense basis; below `1.0` something — body or tail — is working against it.
+///
+/// Percentiles use linear interpolation over the sorted window. A window with no
+/// losses (zero profit-factor denominator) or no left tail (zero P5) reports `0.0`
+/// rather than dividing by zero.
+///
+/// The first value lands after `period` returns; each `update` re-sorts the window
+/// (O(period log period)), which is O(1) in the length of the overall series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, CommonSenseRatio};
+///
+/// let mut indicator = CommonSenseRatio::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update((f64::from(i) * 0.3).sin() * 0.02);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct CommonSenseRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl CommonSenseRatio {
+    /// Construct a Common Sense Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` (percentiles need at least
+    /// two observations).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "common sense ratio needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        let mut gains = 0.0;
+        let mut losses = 0.0;
+        for ret in &self.window {
+            gains += ret.max(0.0);
+            losses += (-ret).max(0.0);
+        }
+        if losses <= 0.0 {
+            return 0.0;
+        }
+        let mut sorted: Vec<f64> = self.window.iter().copied().collect();
+        sorted.sort_unstable_by(f64::total_cmp);
+        let lower_tail = percentile(&sorted, 5.0).abs();
+        if lower_tail <= 0.0 {
+            return 0.0;
+        }
+        let profit_factor = gains / losses;
+        let tail_ratio = percentile(&sorted, 95.0) / lower_tail;
+        profit_factor * tail_ratio
+    }
+}
+
+/// Linear-interpolation percentile of an ascending, non-empty slice.
+fn percentile(sorted: &[f64], pct: f64) -> f64 {
+    let last_index = sorted.len() - 1;
+    #[allow(clippy::cast_precision_loss)]
+    let rank = pct / 100.0 * last_index as f64;
+    let floor = rank.floor();
+    // `rank` lies in `[0, last_index]`, so its floor is a valid in-bounds index.
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    let lower = floor as usize;
+    if lower >= last_index {
+        return sorted[last_index];
+    }
+    let frac = rank - floor;
+    sorted[lower] + frac * (sorted[lower + 1] - sorted[lower])
+}
+
+impl Indicator for CommonSenseRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "CommonSenseRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            CommonSenseRatio::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let csr = CommonSenseRatio::new(20).unwrap();
+        assert_eq!(csr.period(), 20);
+        assert_eq!(csr.warmup_period(), 20);
+        assert_eq!(csr.name(), "CommonSenseRatio");
+        assert!(!csr.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // window [-0.04, -0.02, 0.0, 0.02, 0.04].
+        // gains = 0.06, losses = 0.06 -> profit factor 1.0.
+        // P95 = 0.036, |P5| = 0.036 -> tail ratio 1.0. CSR = 1.0.
+        let mut csr = CommonSenseRatio::new(5).unwrap();
+        let out = csr.batch(&[-0.04, -0.02, 0.0, 0.02, 0.04]);
+        assert_relative_eq!(out[4].unwrap(), 1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn no_losses_is_zero() {
+        let mut csr = CommonSenseRatio::new(3).unwrap();
+        let last = csr
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn flat_window_is_zero() {
+        // All zeros: no losses denominator -> zero (the gains/losses guard fires).
+        let mut csr = CommonSenseRatio::new(4).unwrap();
+        let last = csr.batch(&[0.0; 4]).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut csr = CommonSenseRatio::new(3).unwrap();
+        assert_eq!(csr.update(0.01), None);
+        assert_eq!(csr.update(f64::NAN), None);
+        assert_eq!(csr.update(-0.02), None);
+        assert!(csr.update(0.03).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut csr = CommonSenseRatio::new(3).unwrap();
+        csr.batch(&[-0.01, 0.0, 0.02]);
+        assert!(csr.is_ready());
+        csr.reset();
+        assert!(!csr.is_ready());
+        assert_eq!(csr.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.02)
+            .collect();
+        let batch = CommonSenseRatio::new(15).unwrap().batch(&rets);
+        let mut streamer = CommonSenseRatio::new(15).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn percentile_at_top_returns_last() {
+        // The rank floor reaching the final index returns the largest element.
+        assert_relative_eq!(percentile(&[1.0, 2.0, 3.0], 100.0), 3.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn zero_lower_tail_is_zero() {
+        // One loss but a 5th percentile of exactly zero: the tail term collapses
+        // and the indicator reports 0.0 rather than dividing by zero. With period
+        // 21 the 5% rank lands on sorted index 1, which is 0.0 here.
+        let mut returns = vec![0.0; 21];
+        returns[0] = -0.1;
+        let mut csr = CommonSenseRatio::new(21).unwrap();
+        let last = csr.batch(&returns).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+}

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

@@ -0,0 +1,347 @@
+//! Composite Profile — POC and value area over a long composite window.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Output of [`CompositeProfile`]: the point of control and the value-area bounds.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct CompositeProfileOutput {
+    /// Point of Control — the price (bin centre) with the most volume.
+    pub poc: f64,
+    /// Value-Area High — top of the band holding `value_area_pct` of volume.
+    pub vah: f64,
+    /// Value-Area Low — bottom of that band.
+    pub val: f64,
+}
+
+/// Composite Profile — a multi-session volume profile reduced to its **point of
+/// control** and **value area**, built over a long composite window.
+///
+/// ```text
+/// build a `bins`-bucket volume profile over the last `period` candles
+/// POC = bin with the most volume
+/// expand from the POC, always adding the heavier adjacent bin, until the
+///   accumulated volume reaches `value_area_pct` of the total
+/// VAH / VAL = the highest / lowest price included
+/// ```
+///
+/// A composite profile merges many sessions into one structure to reveal the
+/// dominant value area and control price across a longer horizon — the levels that
+/// matter for swing positioning rather than a single day. The point of control is
+/// the fairest price (heaviest trade); the value area (classically 70% of volume)
+/// brackets where the market spent most of its time. Price inside the value area is
+/// "in balance"; acceptance outside it signals a value migration.
+///
+/// The first value lands after `period` candles; each `update` rebuilds the
+/// profile in O(`period · bins`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, CompositeProfile};
+///
+/// let mut indicator = CompositeProfile::new(100, 50, 0.70).unwrap();
+/// let mut last = None;
+/// for i in 0..150 {
+///     let base = 100.0 + (f64::from(i) * 0.1).sin() * 8.0;
+///     let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct CompositeProfile {
+    period: usize,
+    bins: usize,
+    value_area_pct: f64,
+    window: VecDeque<Candle>,
+    last: Option<CompositeProfileOutput>,
+}
+
+impl CompositeProfile {
+    /// Construct a Composite Profile.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period` or `bins` is zero, or
+    /// [`Error::InvalidParameter`] if `value_area_pct` is not in `(0, 1]`.
+    pub fn new(period: usize, bins: usize, value_area_pct: f64) -> Result<Self> {
+        if period == 0 || bins == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if !value_area_pct.is_finite() || value_area_pct <= 0.0 || value_area_pct > 1.0 {
+            return Err(Error::InvalidParameter {
+                message: "value_area_pct must be in (0, 1]",
+            });
+        }
+        Ok(Self {
+            period,
+            bins,
+            value_area_pct,
+            window: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured `(period, bins, value_area_pct)`.
+    pub const fn params(&self) -> (usize, usize, f64) {
+        (self.period, self.bins, self.value_area_pct)
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<CompositeProfileOutput> {
+        self.last
+    }
+
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn compute(&self) -> CompositeProfileOutput {
+        let mut low = f64::INFINITY;
+        let mut high = f64::NEG_INFINITY;
+        for c in &self.window {
+            low = low.min(c.low);
+            high = high.max(c.high);
+        }
+        let span = high - low;
+        if span <= 0.0 {
+            return CompositeProfileOutput {
+                poc: low,
+                vah: low,
+                val: low,
+            };
+        }
+        let width = span / self.bins as f64;
+        let centre = |idx: usize| low + (idx as f64 + 0.5) * width;
+        let mut hist = vec![0.0; self.bins];
+        for c in &self.window {
+            if c.volume == 0.0 {
+                continue;
+            }
+            let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
+            let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
+            let share = c.volume / (hi_idx - lo_idx + 1) as f64;
+            for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
+                *bin += share;
+            }
+        }
+        let total: f64 = hist.iter().sum();
+        let mut poc = 0;
+        let mut poc_vol = f64::NEG_INFINITY;
+        for (idx, &vol) in hist.iter().enumerate() {
+            if vol > poc_vol {
+                poc_vol = vol;
+                poc = idx;
+            }
+        }
+        let target = total * self.value_area_pct;
+        let mut acc = hist[poc];
+        let mut top = poc;
+        let mut bottom = poc;
+        while acc < target && (top < self.bins - 1 || bottom > 0) {
+            let above = if top < self.bins - 1 {
+                hist[top + 1]
+            } else {
+                f64::NEG_INFINITY
+            };
+            let below = if bottom > 0 {
+                hist[bottom - 1]
+            } else {
+                f64::NEG_INFINITY
+            };
+            if above >= below {
+                top += 1;
+                acc += hist[top];
+            } else {
+                bottom -= 1;
+                acc += hist[bottom];
+            }
+        }
+        CompositeProfileOutput {
+            poc: centre(poc),
+            vah: centre(top),
+            val: centre(bottom),
+        }
+    }
+}
+
+impl Indicator for CompositeProfile {
+    type Input = Candle;
+    type Output = CompositeProfileOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<CompositeProfileOutput> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(candle);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let out = self.compute();
+        self.last = Some(out);
+        Some(out)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "CompositeProfile"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(high: f64, low: f64, volume: f64) -> Candle {
+        Candle::new_unchecked(
+            f64::midpoint(high, low),
+            high,
+            low,
+            f64::midpoint(high, low),
+            volume,
+            0,
+        )
+    }
+
+    #[test]
+    fn rejects_invalid_params() {
+        assert!(matches!(
+            CompositeProfile::new(0, 50, 0.7),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            CompositeProfile::new(100, 0, 0.7),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            CompositeProfile::new(100, 50, 0.0),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            CompositeProfile::new(100, 50, 1.5),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let p = CompositeProfile::new(100, 50, 0.7).unwrap();
+        assert_eq!(p.params(), (100, 50, 0.7));
+        assert_eq!(p.warmup_period(), 100);
+        assert_eq!(p.name(), "CompositeProfile");
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut p = CompositeProfile::new(4, 8, 0.7).unwrap();
+        let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
+        let out = p.batch(&candles);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn value_area_brackets_poc() {
+        let mut p = CompositeProfile::new(20, 30, 0.7).unwrap();
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                c(
+                    110.0 + (f64::from(i) * 0.3).sin() * 8.0,
+                    90.0 + (f64::from(i) * 0.3).cos() * 8.0,
+                    1_000.0,
+                )
+            })
+            .collect();
+        for o in p.batch(&candles).into_iter().flatten() {
+            assert!(o.val <= o.poc && o.poc <= o.vah);
+        }
+    }
+
+    #[test]
+    fn poc_at_heavy_cluster() {
+        // Volume clustered at ~100; thin pokes elsewhere -> POC near 100.
+        let mut p = CompositeProfile::new(6, 30, 0.7).unwrap();
+        let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
+        candles.push(c(140.0, 60.0, 50.0));
+        let out = p.batch(&candles).into_iter().flatten().last().unwrap();
+        assert!(
+            (out.poc - 100.0).abs() < 5.0,
+            "POC should sit at the cluster, got {}",
+            out.poc
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut p = CompositeProfile::new(4, 8, 0.7).unwrap();
+        p.batch(&[c(110.0, 90.0, 1_000.0); 6]);
+        assert!(p.is_ready());
+        p.reset();
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+        assert_eq!(p.update(c(110.0, 90.0, 1_000.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..120)
+            .map(|i| {
+                c(
+                    110.0 + (f64::from(i) * 0.25).sin() * 9.0,
+                    90.0,
+                    1_000.0 + f64::from(i),
+                )
+            })
+            .collect();
+        let batch = CompositeProfile::new(50, 50, 0.7).unwrap().batch(&candles);
+        let mut b = CompositeProfile::new(50, 50, 0.7).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn flat_window_collapses_to_price() {
+        // Zero high-low span returns the price for POC, VAH and VAL.
+        let mut cp = CompositeProfile::new(2, 4, 0.7).unwrap();
+        cp.update(c(50.0, 50.0, 10.0));
+        let out = cp.update(c(50.0, 50.0, 10.0)).unwrap();
+        assert_eq!(out.poc, out.vah);
+        assert_eq!(out.poc, out.val);
+    }
+
+    #[test]
+    fn zero_volume_window_is_handled() {
+        // Non-flat window of zero-volume candles hits the skip path.
+        let mut cp = CompositeProfile::new(2, 4, 0.7).unwrap();
+        cp.update(c(60.0, 40.0, 0.0));
+        assert!(cp.update(c(60.0, 40.0, 0.0)).is_some());
+    }
+
+    #[test]
+    fn value_area_expands_down_from_top_poc() {
+        // POC sits in the top bin; with a wide value-area target the area runs
+        // out of bins above (the ceiling branch) and keeps expanding downward.
+        let mut cp = CompositeProfile::new(2, 3, 0.9).unwrap();
+        cp.update(c(100.0, 0.0, 30.0)); // thin spread across all three bins
+        let out = cp.update(c(100.0, 67.0, 60.0)).unwrap(); // heavy in the top bin
+        assert!(out.val <= out.poc && out.poc <= out.vah);
+    }
+}

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

@@ -0,0 +1,215 @@
+//! Dumpling Top — a rounded top (dome) confirmed by a breakdown.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Dumpling Top — the bearish mirror of the [`FryPanBottom`](crate::FryPanBottom):
+/// a gently rounded **top** (dome) across the window, confirmed by a close back
+/// below where it started.
+///
+/// ```text
+/// over the last `period` closes:
+///   the maximum close sits in the middle third of the window (the "dome")
+///   the latest close is below the first close (the breakdown)
+/// signal = −1 when both hold, else 0
+/// ```
+///
+/// The dumpling top is a distribution pattern: price rounds over at the top as
+/// buying fades, then rolls down through the level it rose from. Detection requires
+/// a *central* high (a symmetric dome, not a one-sided spike) and a close below the
+/// window's opening level. The output is `−1.0` (pattern) or `0.0`.
+///
+/// The first value lands after `period` inputs; each `update` scans the window in
+/// O(`period`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, DumplingTop};
+///
+/// let mut indicator = DumplingTop::new(9).unwrap();
+/// let closes = [100.0, 102.0, 104.0, 105.0, 104.0, 102.0, 99.0, 97.0, 95.0];
+/// let mut last = None;
+/// for &cl in &closes {
+///     let c = Candle::new(cl, cl + 0.5, cl - 0.5, cl, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert_eq!(last, Some(-1.0));
+/// ```
+#[derive(Debug, Clone)]
+pub struct DumplingTop {
+    period: usize,
+    closes: VecDeque<f64>,
+    last: Option<f64>,
+}
+
+impl DumplingTop {
+    /// Construct a Dumpling Top over `period` bars.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 5`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 5 {
+            return Err(Error::InvalidPeriod {
+                message: "dumpling top needs period >= 5",
+            });
+        }
+        Ok(Self {
+            period,
+            closes: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured window period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for DumplingTop {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        if self.closes.len() == self.period {
+            self.closes.pop_front();
+        }
+        self.closes.push_back(candle.close);
+        if self.closes.len() < self.period {
+            return None;
+        }
+        let first = *self.closes.front().expect("non-empty");
+        let last = *self.closes.back().expect("non-empty");
+        let mut max_idx = 0;
+        let mut max_val = f64::NEG_INFINITY;
+        for (i, &v) in self.closes.iter().enumerate() {
+            if v > max_val {
+                max_val = v;
+                max_idx = i;
+            }
+        }
+        let lo = self.period / 4;
+        let hi = self.period - self.period / 4;
+        let dome = max_idx >= lo && max_idx < hi;
+        let broke_down = last < first && last < max_val;
+        let v = if dome && broke_down { -1.0 } else { 0.0 };
+        self.last = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.closes.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "DumplingTop"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(close: f64) -> Candle {
+        Candle::new_unchecked(close, close + 0.5, close - 0.5, close, 1_000.0, 0)
+    }
+
+    #[test]
+    fn rejects_small_period() {
+        assert!(matches!(
+            DumplingTop::new(4),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(DumplingTop::new(5).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let d = DumplingTop::new(9).unwrap();
+        assert_eq!(d.period(), 9);
+        assert_eq!(d.warmup_period(), 9);
+        assert_eq!(d.name(), "DumplingTop");
+        assert!(!d.is_ready());
+        assert_eq!(d.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut d = DumplingTop::new(5).unwrap();
+        let out = d.batch(&[c(100.0), c(101.0), c(102.0), c(101.0), c(99.0), c(98.0)]);
+        for v in out.iter().take(4) {
+            assert!(v.is_none());
+        }
+        assert!(out[4].is_some());
+    }
+
+    #[test]
+    fn rounded_top_then_breakdown_signals() {
+        let mut d = DumplingTop::new(9).unwrap();
+        let closes = [100.0, 102.0, 104.0, 105.0, 104.0, 102.0, 99.0, 97.0, 95.0];
+        let candles: Vec<Candle> = closes.iter().map(|&x| c(x)).collect();
+        let last = d.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, -1.0);
+    }
+
+    #[test]
+    fn one_sided_rise_is_zero() {
+        let mut d = DumplingTop::new(9).unwrap();
+        let candles: Vec<Candle> = (0..9).map(|i| c(100.0 + f64::from(i))).collect();
+        let last = d.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn no_breakdown_is_zero() {
+        let mut d = DumplingTop::new(9).unwrap();
+        let closes = [
+            100.0, 102.0, 104.0, 105.0, 104.0, 103.0, 102.0, 101.0, 100.5,
+        ];
+        let candles: Vec<Candle> = closes.iter().map(|&x| c(x)).collect();
+        let last = d.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut d = DumplingTop::new(5).unwrap();
+        d.batch(&[c(100.0), c(101.0), c(102.0), c(101.0), c(99.0)]);
+        assert!(d.is_ready());
+        d.reset();
+        assert!(!d.is_ready());
+        assert_eq!(d.value(), None);
+        assert_eq!(d.update(c(100.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..60)
+            .map(|i| c(100.0 + (f64::from(i) * 0.3).sin() * 5.0))
+            .collect();
+        let batch = DumplingTop::new(9).unwrap().batch(&candles);
+        let mut b = DumplingTop::new(9).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,155 @@
+//! Estimated Leverage Ratio — open interest per unit of aggregate position size.
+
+use crate::derivatives::DerivativesTick;
+use crate::traits::Indicator;
+
+/// Estimated Leverage Ratio (ELR) — open interest relative to the aggregate
+/// long+short position size, a proxy for how leveraged outstanding positions are.
+///
+/// ```text
+/// ELR = open_interest / (long_size + short_size)
+/// ```
+///
+/// The classic estimated leverage ratio compares open interest (the notional of
+/// outstanding contracts) to the capital backing it. With the size fields of a
+/// [`DerivativesTick`] standing in for the position base, the ratio rises when a
+/// given pool of positions controls more open interest — i.e. when the market is
+/// running hotter leverage. Spikes in ELR mark crowded, fragile conditions where a
+/// move can cascade into liquidations; a falling ELR marks deleveraging.
+///
+/// The ratio is non-negative; a tick with zero aggregate size reports `0` rather
+/// than dividing by zero. It is stateless — each tick yields one value (no warmup).
+/// Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativesTick, Indicator, EstimatedLeverageRatio};
+///
+/// let mut indicator = EstimatedLeverageRatio::new();
+/// let tick = DerivativesTick::new(0.0001, 100.0, 100.0, 100.0, 1_000.0, 400.0, 600.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
+/// let elr = indicator.update(tick).unwrap();
+/// assert!((elr - 1.0).abs() < 1e-12); // 1000 / (400 + 600)
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct EstimatedLeverageRatio {
+    ready: bool,
+}
+
+impl EstimatedLeverageRatio {
+    /// Construct a new Estimated Leverage Ratio. The indicator is parameter-free.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { ready: false }
+    }
+}
+
+impl Indicator for EstimatedLeverageRatio {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        let base = tick.long_size + tick.short_size;
+        let elr = if base > 0.0 {
+            tick.open_interest / base
+        } else {
+            0.0
+        };
+        self.ready = true;
+        Some(elr)
+    }
+
+    fn reset(&mut self) {
+        self.ready = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ready
+    }
+
+    fn name(&self) -> &'static str {
+        "EstimatedLeverageRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn tick(oi: f64, long: f64, short: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(
+            0.0, 100.0, 100.0, 100.0, oi, long, short, 0.0, 0.0, 0.0, 0.0, 0,
+        )
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let e = EstimatedLeverageRatio::new();
+        assert_eq!(e.warmup_period(), 1);
+        assert_eq!(e.name(), "EstimatedLeverageRatio");
+        assert!(!e.is_ready());
+    }
+
+    #[test]
+    fn ratio_reference_value() {
+        let mut e = EstimatedLeverageRatio::new();
+        // 1000 / (400 + 600) = 1.0.
+        assert_relative_eq!(
+            e.update(tick(1_000.0, 400.0, 600.0)).unwrap(),
+            1.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn higher_oi_raises_ratio() {
+        let mut e = EstimatedLeverageRatio::new();
+        let low = e.update(tick(1_000.0, 500.0, 500.0)).unwrap();
+        let high = e.update(tick(3_000.0, 500.0, 500.0)).unwrap();
+        assert!(high > low);
+    }
+
+    #[test]
+    fn zero_base_is_zero() {
+        let mut e = EstimatedLeverageRatio::new();
+        assert_relative_eq!(
+            e.update(tick(1_000.0, 0.0, 0.0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn ready_after_first_update() {
+        let mut e = EstimatedLeverageRatio::new();
+        assert!(!e.is_ready());
+        e.update(tick(1_000.0, 500.0, 500.0));
+        assert!(e.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut e = EstimatedLeverageRatio::new();
+        e.update(tick(1_000.0, 500.0, 500.0));
+        assert!(e.is_ready());
+        e.reset();
+        assert!(!e.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..40)
+            .map(|i| tick(1_000.0 + f64::from(i) * 10.0, 500.0, 500.0))
+            .collect();
+        let batch = EstimatedLeverageRatio::new().batch(&ticks);
+        let mut b = EstimatedLeverageRatio::new();
+        let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,218 @@
+//! Frying Pan Bottom — a rounded bottom (U) confirmed by recovery.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Frying Pan Bottom — a gently rounded bottom across the lookback window: prices
+/// decline, flatten near the centre, then recover above where they started.
+///
+/// ```text
+/// over the last `period` closes:
+///   the minimum close sits in the middle third of the window (the "bowl")
+///   the latest close is above the first close (the rim is recovered)
+/// signal = +1 when both hold, else 0
+/// ```
+///
+/// The frying pan is a bullish accumulation pattern: a saucer-shaped base where
+/// selling dries up, the curve flattens, and price lifts off the rim. Detecting it
+/// requires the low point to be central (a symmetric bowl, not a one-sided drop)
+/// and the close to have climbed back above the window's opening level, confirming
+/// the breakout from the base. The output is `+1.0` (pattern) or `0.0`.
+///
+/// The first value lands after `period` inputs; each `update` scans the window in
+/// O(`period`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, FryPanBottom};
+///
+/// let mut indicator = FryPanBottom::new(9).unwrap();
+/// // A U-shaped base then recovery.
+/// let closes = [100.0, 98.0, 96.0, 95.0, 96.0, 98.0, 101.0, 103.0, 105.0];
+/// let mut last = None;
+/// for &cl in &closes {
+///     let c = Candle::new(cl, cl + 0.5, cl - 0.5, cl, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert_eq!(last, Some(1.0));
+/// ```
+#[derive(Debug, Clone)]
+pub struct FryPanBottom {
+    period: usize,
+    closes: VecDeque<f64>,
+    last: Option<f64>,
+}
+
+impl FryPanBottom {
+    /// Construct a Frying Pan Bottom over `period` bars.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 5` (a bowl needs room for a
+    /// central low between recovering sides).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 5 {
+            return Err(Error::InvalidPeriod {
+                message: "frying pan bottom needs period >= 5",
+            });
+        }
+        Ok(Self {
+            period,
+            closes: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured window period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for FryPanBottom {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        if self.closes.len() == self.period {
+            self.closes.pop_front();
+        }
+        self.closes.push_back(candle.close);
+        if self.closes.len() < self.period {
+            return None;
+        }
+        let first = *self.closes.front().expect("non-empty");
+        let last = *self.closes.back().expect("non-empty");
+        // Index of the minimum close.
+        let mut min_idx = 0;
+        let mut min_val = f64::INFINITY;
+        for (i, &v) in self.closes.iter().enumerate() {
+            if v < min_val {
+                min_val = v;
+                min_idx = i;
+            }
+        }
+        let lo = self.period / 4;
+        let hi = self.period - self.period / 4;
+        let bowl = min_idx >= lo && min_idx < hi;
+        let recovered = last > first && last > min_val;
+        let v = if bowl && recovered { 1.0 } else { 0.0 };
+        self.last = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.closes.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "FryPanBottom"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(close: f64) -> Candle {
+        Candle::new_unchecked(close, close + 0.5, close - 0.5, close, 1_000.0, 0)
+    }
+
+    #[test]
+    fn rejects_small_period() {
+        assert!(matches!(
+            FryPanBottom::new(4),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(FryPanBottom::new(5).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let f = FryPanBottom::new(9).unwrap();
+        assert_eq!(f.period(), 9);
+        assert_eq!(f.warmup_period(), 9);
+        assert_eq!(f.name(), "FryPanBottom");
+        assert!(!f.is_ready());
+        assert_eq!(f.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut f = FryPanBottom::new(5).unwrap();
+        let out = f.batch(&[c(100.0), c(99.0), c(98.0), c(99.0), c(101.0), c(102.0)]);
+        for v in out.iter().take(4) {
+            assert!(v.is_none());
+        }
+        assert!(out[4].is_some());
+    }
+
+    #[test]
+    fn rounded_bottom_then_recovery_signals() {
+        let mut f = FryPanBottom::new(9).unwrap();
+        let closes = [100.0, 98.0, 96.0, 95.0, 96.0, 98.0, 101.0, 103.0, 105.0];
+        let candles: Vec<Candle> = closes.iter().map(|&x| c(x)).collect();
+        let last = f.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 1.0);
+    }
+
+    #[test]
+    fn one_sided_drop_is_zero() {
+        // A straight decline (min at the end) is not a bowl.
+        let mut f = FryPanBottom::new(9).unwrap();
+        let candles: Vec<Candle> = (0..9).map(|i| c(100.0 - f64::from(i))).collect();
+        let last = f.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn no_recovery_is_zero() {
+        // Bowl shape but the last close never climbs above the first.
+        let mut f = FryPanBottom::new(9).unwrap();
+        let closes = [100.0, 98.0, 96.0, 95.0, 96.0, 97.0, 98.0, 99.0, 99.5];
+        let candles: Vec<Candle> = closes.iter().map(|&x| c(x)).collect();
+        let last = f.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut f = FryPanBottom::new(5).unwrap();
+        f.batch(&[c(100.0), c(99.0), c(98.0), c(99.0), c(101.0)]);
+        assert!(f.is_ready());
+        f.reset();
+        assert!(!f.is_ready());
+        assert_eq!(f.value(), None);
+        assert_eq!(f.update(c(100.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..60)
+            .map(|i| c(100.0 + (f64::from(i) * 0.3).sin() * 5.0))
+            .collect();
+        let batch = FryPanBottom::new(9).unwrap().batch(&candles);
+        let mut b = FryPanBottom::new(9).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,164 @@
+//! Funding-Implied APR — the per-interval funding rate annualised.
+
+use crate::derivatives::DerivativesTick;
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Funding-Implied APR — the perpetual's per-interval funding rate scaled to an
+/// annualised rate.
+///
+/// ```text
+/// APR = funding_rate · intervals_per_year
+/// ```
+///
+/// Funding is paid in small per-interval amounts (commonly every 8 hours, i.e.
+/// `1095` intervals per year). Annualising it converts the headline funding number
+/// into the carry cost (or yield) of holding the position for a year, which is far
+/// easier to reason about and to compare against spot lending rates, basis trades,
+/// and other yields. A large positive APR means longs pay a steep carry to shorts
+/// (and vice versa) — the economic incentive behind cash-and-carry and
+/// funding-arbitrage strategies.
+///
+/// The output is a fraction (multiply by `100` for percent) and may be negative.
+/// It is stateless — each tick yields one value (no warmup). Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativesTick, Indicator, FundingImpliedApr};
+///
+/// // 0.01% per 8h funding -> 0.0001 * 1095 ≈ 10.95% APR.
+/// let mut indicator = FundingImpliedApr::new(1095.0).unwrap();
+/// let tick = DerivativesTick::new(0.0001, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
+/// let apr = indicator.update(tick).unwrap();
+/// assert!((apr - 0.1095).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct FundingImpliedApr {
+    intervals_per_year: f64,
+    ready: bool,
+}
+
+impl FundingImpliedApr {
+    /// Construct a Funding-Implied APR with the number of funding intervals per
+    /// year (e.g. `1095` for 8-hour funding, `365` for daily).
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidParameter`] if `intervals_per_year` is not finite
+    /// and positive.
+    pub fn new(intervals_per_year: f64) -> Result<Self> {
+        if !intervals_per_year.is_finite() || intervals_per_year <= 0.0 {
+            return Err(Error::InvalidParameter {
+                message: "intervals_per_year must be finite and positive",
+            });
+        }
+        Ok(Self {
+            intervals_per_year,
+            ready: false,
+        })
+    }
+
+    /// Configured intervals per year.
+    pub const fn intervals_per_year(&self) -> f64 {
+        self.intervals_per_year
+    }
+}
+
+impl Indicator for FundingImpliedApr {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        self.ready = true;
+        Some(tick.funding_rate * self.intervals_per_year)
+    }
+
+    fn reset(&mut self) {
+        self.ready = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ready
+    }
+
+    fn name(&self) -> &'static str {
+        "FundingImpliedApr"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn tick(funding: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(
+            funding, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
+        )
+    }
+
+    #[test]
+    fn rejects_invalid_intervals() {
+        assert!(matches!(
+            FundingImpliedApr::new(0.0),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            FundingImpliedApr::new(-1.0),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let f = FundingImpliedApr::new(1095.0).unwrap();
+        assert_relative_eq!(f.intervals_per_year(), 1095.0, epsilon = 1e-12);
+        assert_eq!(f.warmup_period(), 1);
+        assert_eq!(f.name(), "FundingImpliedApr");
+        assert!(!f.is_ready());
+    }
+
+    #[test]
+    fn apr_reference_value() {
+        let mut f = FundingImpliedApr::new(1095.0).unwrap();
+        assert_relative_eq!(f.update(tick(0.0001)).unwrap(), 0.1095, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn negative_funding_is_negative_apr() {
+        let mut f = FundingImpliedApr::new(1095.0).unwrap();
+        assert!(f.update(tick(-0.0001)).unwrap() < 0.0);
+    }
+
+    #[test]
+    fn zero_funding_is_zero() {
+        let mut f = FundingImpliedApr::new(365.0).unwrap();
+        assert_relative_eq!(f.update(tick(0.0)).unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut f = FundingImpliedApr::new(1095.0).unwrap();
+        f.update(tick(0.0001));
+        assert!(f.is_ready());
+        f.reset();
+        assert!(!f.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..40)
+            .map(|i| tick(0.0001 * (f64::from(i) * 0.3).sin()))
+            .collect();
+        let batch = FundingImpliedApr::new(1095.0).unwrap().batch(&ticks);
+        let mut b = FundingImpliedApr::new(1095.0).unwrap();
+        let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,229 @@
+//! Gain-to-Pain Ratio (Schwager) — sum of returns over the sum of losses.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Gain-to-Pain Ratio — Jack Schwager's measure of return per unit of downside:
+/// the sum of all returns divided by the sum of the absolute *negative* returns.
+///
+/// ```text
+/// GPR = Σ returns / Σ |negative returns|        over the window
+/// ```
+///
+/// Where the [`GainLossRatio`](crate::GainLossRatio) compares *average* win to
+/// *average* loss and the [`ProfitFactor`](crate::ProfitFactor) compares gross
+/// profit to gross loss, the Gain-to-Pain Ratio puts the **net** result over the
+/// total pain endured to earn it. Schwager treats a GPR above `1.0` as good and
+/// above `2.0` as excellent for a monthly return series: the strategy made more
+/// than it lost on the way, and twice as much when GPR is `2`. A flat series, or
+/// one with no losses, has no measurable pain and reports `0` (undefined).
+///
+/// The output is unbounded and may be negative (a net-losing window). The first
+/// value lands after `period` returns; each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, GainToPainRatio};
+///
+/// let mut indicator = GainToPainRatio::new(12).unwrap();
+/// let mut last = None;
+/// for i in 0..24 {
+///     last = indicator.update((f64::from(i) * 0.5).sin() * 0.02);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct GainToPainRatio {
+    period: usize,
+    window: VecDeque<f64>,
+    sum_all: f64,
+    sum_pain: f64,
+}
+
+impl GainToPainRatio {
+    /// Construct a Gain-to-Pain Ratio over `period` returns.
+    ///
+    /// # 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_all: 0.0,
+            sum_pain: 0.0,
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for GainToPainRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return if self.window.len() == self.period {
+                Some(self.compute())
+            } else {
+                None
+            };
+        }
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("non-empty");
+            self.sum_all -= old;
+            if old < 0.0 {
+                self.sum_pain -= -old;
+            }
+        }
+        self.window.push_back(ret);
+        self.sum_all += ret;
+        if ret < 0.0 {
+            self.sum_pain += -ret;
+        }
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum_all = 0.0;
+        self.sum_pain = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "GainToPainRatio"
+    }
+}
+
+impl GainToPainRatio {
+    fn compute(&self) -> f64 {
+        if self.sum_pain > 0.0 {
+            self.sum_all / self.sum_pain
+        } else {
+            0.0
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(GainToPainRatio::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let g = GainToPainRatio::new(12).unwrap();
+        assert_eq!(g.period(), 12);
+        assert_eq!(g.warmup_period(), 12);
+        assert_eq!(g.name(), "GainToPainRatio");
+        assert!(!g.is_ready());
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut g = GainToPainRatio::new(4).unwrap();
+        let out = g.batch(&[0.01, -0.01, 0.02, -0.01, 0.03]);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns: +0.04, -0.02 -> sum_all = 0.02, pain = 0.02 -> GPR = 1.0.
+        let mut g = GainToPainRatio::new(2).unwrap();
+        let out = g.batch(&[0.04, -0.02]);
+        assert_relative_eq!(out[1].unwrap(), 1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn net_losing_window_is_negative() {
+        let mut g = GainToPainRatio::new(3).unwrap();
+        let last = g
+            .batch(&[-0.03, 0.01, -0.02])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last < 0.0);
+    }
+
+    #[test]
+    fn no_pain_is_zero() {
+        let mut g = GainToPainRatio::new(3).unwrap();
+        let last = g
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ignores_non_finite() {
+        let mut g = GainToPainRatio::new(2).unwrap();
+        let ready = g
+            .batch(&[0.04, -0.02])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(g.update(f64::NAN), Some(ready));
+    }
+
+    #[test]
+    fn non_finite_before_ready_is_none() {
+        // A non-finite value arriving before the window fills yields None.
+        let mut g = GainToPainRatio::new(3).unwrap();
+        assert_eq!(g.update(0.02), None);
+        assert_eq!(g.update(f64::NAN), None);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut g = GainToPainRatio::new(2).unwrap();
+        g.batch(&[0.04, -0.02]);
+        assert!(g.is_ready());
+        g.reset();
+        assert!(!g.is_ready());
+        assert_eq!(g.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60).map(|i| (f64::from(i) * 0.3).sin() * 0.02).collect();
+        let batch = GainToPainRatio::new(12).unwrap().batch(&rets);
+        let mut b = GainToPainRatio::new(12).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| b.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,193 @@
+#![allow(clippy::doc_markdown)]
+
+//! Harami Cross — a Harami whose second candle is a Doji.
+//!
+//! A Harami Cross is a stronger Harami: a large real body followed by a Doji whose
+//! body sits *within* the prior body. The Doji's total indecision after a strong
+//! move makes the reversal signal more potent than a plain Harami.
+//!
+//! - **Bullish** (`+1.0`): the prior candle is a large **bearish** body
+//!   (`close < open`) and the current candle is a Doji whose open and close lie
+//!   within the prior body.
+//! - **Bearish** (`-1.0`): the prior candle is a large **bullish** body and the
+//!   current is a contained Doji.
+//! - Otherwise the output is `0.0`.
+//!
+//! A doji is a candle whose body is `<= 0.1 * range`. The two-bar lookback means
+//! the first value lands on the second candle.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+fn is_doji(candle: Candle) -> bool {
+    let body = (candle.close - candle.open).abs();
+    let range = candle.high - candle.low;
+    range > 0.0 && body <= 0.1 * range
+}
+
+/// Harami Cross — large-body-then-contained-doji reversal detector.
+#[derive(Debug, Clone, Default)]
+pub struct HaramiCross {
+    prev: Option<Candle>,
+    last_value: Option<f64>,
+}
+
+impl HaramiCross {
+    /// Construct a new `HaramiCross`.
+    #[must_use]
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// Latest emitted signal if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last_value
+    }
+}
+
+impl Indicator for HaramiCross {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let Some(prev) = self.prev else {
+            self.prev = Some(candle);
+            self.last_value = Some(0.0);
+            return Some(0.0);
+        };
+        let prev_body_low = prev.open.min(prev.close);
+        let prev_body_high = prev.open.max(prev.close);
+        let prev_is_solid = !is_doji(prev);
+        let curr_is_doji = is_doji(candle);
+        let contained = candle.open >= prev_body_low
+            && candle.open <= prev_body_high
+            && candle.close >= prev_body_low
+            && candle.close <= prev_body_high;
+
+        let v = if prev_is_solid && curr_is_doji && contained {
+            if prev.close < prev.open {
+                1.0
+            } else {
+                -1.0
+            }
+        } else {
+            0.0
+        };
+        self.prev = Some(candle);
+        self.last_value = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        self.last_value = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last_value.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "HaramiCross"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn solid(open: f64, close: f64) -> Candle {
+        Candle::new_unchecked(
+            open,
+            open.max(close) + 0.2,
+            open.min(close) - 0.2,
+            close,
+            0.0,
+            0,
+        )
+    }
+
+    fn doji(mid: f64) -> Candle {
+        Candle::new_unchecked(mid, mid + 1.0, mid - 1.0, mid + 0.02, 0.0, 0)
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let h = HaramiCross::new();
+        assert_eq!(h.warmup_period(), 2);
+        assert_eq!(h.name(), "HaramiCross");
+        assert!(!h.is_ready());
+        assert_eq!(h.value(), None);
+    }
+
+    #[test]
+    fn first_bar_seeds_without_signal() {
+        let mut h = HaramiCross::new();
+        assert_eq!(h.update(solid(110.0, 100.0)), Some(0.0));
+        assert!(h.update(doji(105.0)).is_some());
+    }
+
+    #[test]
+    fn bullish_harami_cross() {
+        // prior big bearish body [100, 110]; doji centred at 105 inside it -> +1.
+        let mut h = HaramiCross::new();
+        h.update(solid(110.0, 100.0));
+        assert_eq!(h.update(doji(105.0)), Some(1.0));
+    }
+
+    #[test]
+    fn bearish_harami_cross() {
+        // prior big bullish body [100, 110]; doji inside -> -1.
+        let mut h = HaramiCross::new();
+        h.update(solid(100.0, 110.0));
+        assert_eq!(h.update(doji(105.0)), Some(-1.0));
+    }
+
+    #[test]
+    fn doji_outside_body_is_zero() {
+        let mut h = HaramiCross::new();
+        h.update(solid(110.0, 100.0));
+        // doji centred at 120, outside the prior body -> 0.
+        assert_eq!(h.update(doji(120.0)), Some(0.0));
+    }
+
+    #[test]
+    fn non_doji_second_is_zero() {
+        let mut h = HaramiCross::new();
+        h.update(solid(110.0, 100.0));
+        assert_eq!(h.update(solid(104.0, 106.0)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut h = HaramiCross::new();
+        h.update(solid(110.0, 100.0));
+        h.update(doji(105.0));
+        assert!(h.is_ready());
+        h.reset();
+        assert!(!h.is_ready());
+        assert_eq!(h.update(solid(110.0, 100.0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                if i % 2 == 0 {
+                    solid(110.0, 100.0)
+                } else {
+                    doji(105.0)
+                }
+            })
+            .collect();
+        let batch = HaramiCross::new().batch(&candles);
+        let mut b = HaramiCross::new();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,251 @@
+//! Hasbrouck Information Share — each venue's contribution to price discovery.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Hasbrouck Information Share — the share of price-discovery attributable to the
+/// **first** of two synchronised price series (e.g. the same asset on two venues).
+///
+/// ```text
+/// rx_t = x_t − x_{t−1},  ry_t = y_t − y_{t−1}      (one-step price changes)
+/// IS_x = var(rx) / ( var(rx) + var(ry) )           over the window, ∈ [0, 1]
+/// ```
+///
+/// When the same instrument trades on several venues, Joel Hasbrouck's information
+/// share measures how much each venue contributes to the common efficient price.
+/// The venue whose innovations carry more of the variance leads price discovery.
+/// This streaming form uses the **variance-ratio proxy**: the fraction of total
+/// return variance contributed by series `x`. A reading above `0.5` means venue
+/// `x` is the price leader; below `0.5`, the follower. (The full Hasbrouck measure
+/// estimates a vector error-correction model and reports an upper/lower bound from
+/// the Cholesky ordering; this proxy captures the leading idea without the VECM.)
+///
+/// The output is in `[0, 1]`; if both series are flat it reports the neutral `0.5`.
+/// The first value lands after `period + 1` inputs. Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, HasbrouckInformationShare};
+///
+/// let mut indicator = HasbrouckInformationShare::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     // Venue x moves a lot, venue y barely moves -> x leads.
+///     let x = (f64::from(i) * 0.5).sin() * 10.0;
+///     let y = (f64::from(i) * 0.5).sin() * 1.0;
+///     last = indicator.update((x, y));
+/// }
+/// assert!(last.unwrap() > 0.8);
+/// ```
+#[derive(Debug, Clone)]
+pub struct HasbrouckInformationShare {
+    period: usize,
+    prev: Option<(f64, f64)>,
+    window: VecDeque<(f64, f64)>,
+    sum_x: f64,
+    sum_y: f64,
+    sum_xx: f64,
+    sum_yy: f64,
+}
+
+impl HasbrouckInformationShare {
+    /// Construct a Hasbrouck information share over `period` return pairs.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` (variance needs two
+    /// returns).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "information share needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            prev: None,
+            window: VecDeque::with_capacity(period),
+            sum_x: 0.0,
+            sum_y: 0.0,
+            sum_xx: 0.0,
+            sum_yy: 0.0,
+        })
+    }
+
+    /// Configured window of return pairs.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for HasbrouckInformationShare {
+    type Input = (f64, f64);
+    type Output = f64;
+
+    fn update(&mut self, input: (f64, f64)) -> Option<f64> {
+        let (x, y) = input;
+        let Some((px, py)) = self.prev else {
+            self.prev = Some((x, y));
+            return None;
+        };
+        self.prev = Some((x, y));
+        let (rx, ry) = (x - px, y - py);
+        if self.window.len() == self.period {
+            let (ox, oy) = self.window.pop_front().expect("non-empty");
+            self.sum_x -= ox;
+            self.sum_y -= oy;
+            self.sum_xx -= ox * ox;
+            self.sum_yy -= oy * oy;
+        }
+        self.window.push_back((rx, ry));
+        self.sum_x += rx;
+        self.sum_y += ry;
+        self.sum_xx += rx * rx;
+        self.sum_yy += ry * ry;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let n = self.period as f64;
+        let var_x = (self.sum_xx / n - (self.sum_x / n).powi(2)).max(0.0);
+        let var_y = (self.sum_yy / n - (self.sum_y / n).powi(2)).max(0.0);
+        let total = var_x + var_y;
+        Some(if total > 0.0 { var_x / total } else { 0.5 })
+    }
+
+    fn reset(&mut self) {
+        self.prev = None;
+        self.window.clear();
+        self.sum_x = 0.0;
+        self.sum_y = 0.0;
+        self.sum_xx = 0.0;
+        self.sum_yy = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "HasbrouckInformationShare"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(matches!(
+            HasbrouckInformationShare::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(HasbrouckInformationShare::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let h = HasbrouckInformationShare::new(20).unwrap();
+        assert_eq!(h.period(), 20);
+        assert_eq!(h.warmup_period(), 21);
+        assert_eq!(h.name(), "HasbrouckInformationShare");
+        assert!(!h.is_ready());
+    }
+
+    #[test]
+    fn warmup_needs_period_plus_one() {
+        let mut h = HasbrouckInformationShare::new(3).unwrap();
+        assert_eq!(h.update((1.0, 1.0)), None);
+        assert_eq!(h.update((2.0, 2.0)), None);
+        assert_eq!(h.update((3.0, 2.5)), None);
+        assert!(h.update((4.0, 3.0)).is_some());
+    }
+
+    #[test]
+    fn loud_venue_leads() {
+        // x is far more volatile than y -> x holds nearly all the share.
+        let pairs: Vec<(f64, f64)> = (0..40)
+            .map(|i| {
+                (
+                    (f64::from(i) * 0.5).sin() * 10.0,
+                    (f64::from(i) * 0.5).sin() * 1.0,
+                )
+            })
+            .collect();
+        let last = HasbrouckInformationShare::new(20)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last > 0.8, "the loud venue should lead, got {last}");
+    }
+
+    #[test]
+    fn equal_venues_split_evenly() {
+        // Independent but equal-variance moves -> share near 0.5.
+        let pairs: Vec<(f64, f64)> = (0..200)
+            .map(|i| {
+                (
+                    (f64::from(i) * 0.5).sin() * 5.0,
+                    (f64::from(i) * 0.5).cos() * 5.0,
+                )
+            })
+            .collect();
+        for v in HasbrouckInformationShare::new(40)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+        {
+            assert!((0.0..=1.0).contains(&v));
+        }
+    }
+
+    #[test]
+    fn flat_series_is_half() {
+        let pairs: Vec<(f64, f64)> = (0..20).map(|_| (7.0, 9.0)).collect();
+        let last = HasbrouckInformationShare::new(5)
+            .unwrap()
+            .batch(&pairs)
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.5, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut h = HasbrouckInformationShare::new(4).unwrap();
+        h.batch(&[(1.0, 1.0), (2.0, 2.0), (3.0, 3.0), (4.0, 4.0), (5.0, 5.0)]);
+        assert!(h.is_ready());
+        h.reset();
+        assert!(!h.is_ready());
+        assert_eq!(h.update((1.0, 1.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let pairs: Vec<(f64, f64)> = (0..120)
+            .map(|i| {
+                let t = f64::from(i);
+                (t.sin() * 5.0, (t * 0.5).cos() * 3.0)
+            })
+            .collect();
+        let batch = HasbrouckInformationShare::new(20).unwrap().batch(&pairs);
+        let mut h = HasbrouckInformationShare::new(20).unwrap();
+        let streamed: Vec<_> = pairs.iter().map(|p| h.update(*p)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,307 @@
+//! High/Low Volume Nodes (HVN / LVN) — the busiest and quietest price levels.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Output of [`HighLowVolumeNodes`]: the price of the highest- and lowest-volume
+/// node in the profile.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct HighLowVolumeNodesOutput {
+    /// High Volume Node — the price level (bin centre) with the most volume.
+    pub hvn: f64,
+    /// Low Volume Node — the traded price level with the least volume.
+    pub lvn: f64,
+}
+
+/// High/Low Volume Nodes — the price levels of greatest and least acceptance in a
+/// rolling volume profile.
+///
+/// ```text
+/// build a `bins`-bucket volume profile over the last `period` candles
+/// HVN = bin centre of the bucket with the most volume
+/// LVN = bin centre of the traded bucket with the least volume
+/// ```
+///
+/// A volume profile reveals where the market spent the most effort. A **High Volume
+/// Node** (HVN) is a price the market accepted and traded heavily — it acts as a
+/// magnet and as strong support/resistance. A **Low Volume Node** (LVN) is a price
+/// the market rejected quickly — moves tend to accelerate through LVNs and they
+/// often mark the edges between balance areas. Each candle's volume is spread
+/// across the price bins its high-low range spans (as in
+/// [`VolumeProfile`](crate::VolumeProfile)).
+///
+/// The first value lands after `period` candles; each `update` rebuilds the profile
+/// in O(`period · bins`). A degenerate flat window puts both nodes at the price.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, HighLowVolumeNodes};
+///
+/// let mut indicator = HighLowVolumeNodes::new(20, 24).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let base = 100.0 + (f64::from(i) * 0.3).sin() * 5.0;
+///     let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct HighLowVolumeNodes {
+    period: usize,
+    bins: usize,
+    window: VecDeque<Candle>,
+    last: Option<HighLowVolumeNodesOutput>,
+}
+
+impl HighLowVolumeNodes {
+    /// Construct a High/Low Volume Nodes indicator.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period` or `bins` is zero.
+    pub fn new(period: usize, bins: usize) -> Result<Self> {
+        if period == 0 || bins == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            bins,
+            window: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured `(period, bins)`.
+    pub const fn params(&self) -> (usize, usize) {
+        (self.period, self.bins)
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<HighLowVolumeNodesOutput> {
+        self.last
+    }
+
+    /// Build the volume histogram; returns `(low, bin_width, bins)`.
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn profile(&self) -> (f64, f64, Vec<f64>) {
+        let mut low = f64::INFINITY;
+        let mut high = f64::NEG_INFINITY;
+        for c in &self.window {
+            low = low.min(c.low);
+            high = high.max(c.high);
+        }
+        let mut hist = vec![0.0; self.bins];
+        let span = high - low;
+        if span <= 0.0 {
+            hist[0] = self.window.iter().map(|c| c.volume).sum();
+            return (low, 0.0, hist);
+        }
+        let width = span / self.bins as f64;
+        for c in &self.window {
+            if c.volume == 0.0 {
+                continue;
+            }
+            let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
+            let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
+            let touched = hi_idx - lo_idx + 1;
+            let share = c.volume / touched as f64;
+            for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
+                *bin += share;
+            }
+        }
+        (low, width, hist)
+    }
+}
+
+impl Indicator for HighLowVolumeNodes {
+    type Input = Candle;
+    type Output = HighLowVolumeNodesOutput;
+
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn update(&mut self, candle: Candle) -> Option<HighLowVolumeNodesOutput> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(candle);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let (low, width, hist) = self.profile();
+        let centre = |idx: usize| low + (idx as f64 + 0.5) * width;
+
+        let mut hvn_idx = 0;
+        let mut hvn_vol = f64::NEG_INFINITY;
+        let mut lvn_idx = 0;
+        let mut lvn_vol = f64::INFINITY;
+        for (idx, &vol) in hist.iter().enumerate() {
+            if vol > hvn_vol {
+                hvn_vol = vol;
+                hvn_idx = idx;
+            }
+            if vol > 0.0 && vol < lvn_vol {
+                lvn_vol = vol;
+                lvn_idx = idx;
+            }
+        }
+        // If no traded bin was found (all zero volume), both default to bin 0.
+        if !lvn_vol.is_finite() {
+            lvn_idx = hvn_idx;
+        }
+        let out = HighLowVolumeNodesOutput {
+            hvn: centre(hvn_idx),
+            lvn: centre(lvn_idx),
+        };
+        self.last = Some(out);
+        Some(out)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "HighLowVolumeNodes"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(high: f64, low: f64, volume: f64) -> Candle {
+        Candle::new_unchecked(
+            f64::midpoint(high, low),
+            high,
+            low,
+            f64::midpoint(high, low),
+            volume,
+            0,
+        )
+    }
+
+    #[test]
+    fn rejects_zero_params() {
+        assert!(matches!(
+            HighLowVolumeNodes::new(0, 24),
+            Err(Error::PeriodZero)
+        ));
+        assert!(matches!(
+            HighLowVolumeNodes::new(20, 0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let h = HighLowVolumeNodes::new(20, 24).unwrap();
+        assert_eq!(h.params(), (20, 24));
+        assert_eq!(h.warmup_period(), 20);
+        assert_eq!(h.name(), "HighLowVolumeNodes");
+        assert!(!h.is_ready());
+        assert_eq!(h.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut h = HighLowVolumeNodes::new(4, 8).unwrap();
+        let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
+        let out = h.batch(&candles);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn hvn_at_heavy_price() {
+        // Most bars cluster at ~100 (heavy volume); one bar pokes up to 120 lightly.
+        let mut h = HighLowVolumeNodes::new(6, 24).unwrap();
+        let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
+        candles.push(c(121.0, 119.0, 100.0));
+        let out = h.batch(&candles).into_iter().flatten().last().unwrap();
+        // HVN should sit near the heavy 100 cluster, well below the light 120 poke.
+        assert!(
+            out.hvn < 110.0,
+            "HVN should be at the heavy cluster, got {}",
+            out.hvn
+        );
+        assert!(out.lvn >= out.hvn - 1e9); // lvn is a valid level
+    }
+
+    #[test]
+    fn hvn_at_or_above_low() {
+        let mut h = HighLowVolumeNodes::new(10, 24).unwrap();
+        let candles: Vec<Candle> = (0..30)
+            .map(|i| {
+                c(
+                    110.0 + (f64::from(i) * 0.3).sin() * 5.0,
+                    90.0,
+                    1_000.0 + f64::from(i),
+                )
+            })
+            .collect();
+        for o in h.batch(&candles).into_iter().flatten() {
+            assert!(o.hvn.is_finite() && o.lvn.is_finite());
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut h = HighLowVolumeNodes::new(4, 8).unwrap();
+        h.batch(&[c(110.0, 90.0, 1_000.0); 6]);
+        assert!(h.is_ready());
+        h.reset();
+        assert!(!h.is_ready());
+        assert_eq!(h.value(), None);
+        assert_eq!(h.update(c(110.0, 90.0, 1_000.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..80)
+            .map(|i| {
+                c(
+                    110.0 + (f64::from(i) * 0.25).sin() * 9.0,
+                    90.0,
+                    1_000.0 + f64::from(i),
+                )
+            })
+            .collect();
+        let batch = HighLowVolumeNodes::new(20, 24).unwrap().batch(&candles);
+        let mut b = HighLowVolumeNodes::new(20, 24).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn flat_window_is_handled() {
+        // Zero high-low span dumps all volume into bin 0 and returns early.
+        let mut h = HighLowVolumeNodes::new(2, 4).unwrap();
+        h.update(c(50.0, 50.0, 10.0));
+        assert!(h.update(c(50.0, 50.0, 10.0)).is_some());
+    }
+
+    #[test]
+    fn zero_volume_window_falls_back() {
+        // All-zero volume leaves no traded bin; the LVN falls back to the HVN.
+        let mut h = HighLowVolumeNodes::new(2, 4).unwrap();
+        h.update(c(60.0, 40.0, 0.0));
+        let out = h.update(c(60.0, 40.0, 0.0)).unwrap();
+        assert_eq!(out.hvn, out.lvn);
+    }
+}

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

@@ -0,0 +1,239 @@
+//! K-Ratio (Kestner) — slope of the cumulative-return curve over the standard error of that slope.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// K-Ratio over a trailing window of `period` returns.
+///
+/// Lars Kestner's K-Ratio measures the *consistency* of an equity curve, not just
+/// its return. It builds the cumulative-return curve over the window, fits an
+/// ordinary-least-squares trend line through it against time, and divides the
+/// fitted slope by the standard error of that slope:
+///
+/// ```text
+/// equity_t = Σ_{i<=t} return_i           (cumulative curve, t = 1..period)
+/// slope, intercept = OLS(equity_t ~ t)
+/// SE(slope) = sqrt( (Σ residual² / (period − 2)) / Σ(t − t̄)² )
+/// K-Ratio   = slope / SE(slope)
+/// ```
+///
+/// A high K-Ratio means the equity curve climbs *steadily* — a steep slope with
+/// little scatter around the trend. A strategy that earns the same total return in
+/// a few lucky jumps scores lower because its residual scatter inflates the
+/// standard error. This is the original 1996 form; later Kestner revisions scale by
+/// the number of periods (`slope / (SE · period)` in 2003, `slope / (SE · √period)`
+/// in 2013) — apply that scaling downstream if you need to compare across window
+/// lengths.
+///
+/// A perfectly straight window (e.g. constant returns) has zero residual scatter,
+/// so the slope's standard error is zero and the K-Ratio is undefined; the
+/// indicator reports `0.0` in that degenerate case. The statistic therefore needs
+/// some dispersion in the returns to be meaningful.
+///
+/// The first value lands after `period` returns; each `update` re-fits the line
+/// over the window (O(period)), which is O(1) in the length of the overall series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, KRatio};
+///
+/// let mut indicator = KRatio::new(30).unwrap();
+/// let mut last = None;
+/// for i in 0..60 {
+///     last = indicator.update(0.001 + (f64::from(i) * 0.3).sin() * 0.01);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct KRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl KRatio {
+    /// Construct a K-Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 3` (the slope's standard error
+    /// divides by `period − 2`).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 3 {
+            return Err(Error::InvalidPeriod {
+                message: "k-ratio needs period >= 3",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        let count = self.window.len();
+        #[allow(clippy::cast_precision_loss)]
+        let length = count as f64;
+        // Build the cumulative-equity curve and its mean.
+        let mut equity = 0.0;
+        let mut curve: Vec<f64> = Vec::with_capacity(count);
+        let mut sum_equity = 0.0;
+        for ret in &self.window {
+            equity += *ret;
+            curve.push(equity);
+            sum_equity += equity;
+        }
+        // Times are 1..=count, so Σt = count(count+1)/2 in closed form.
+        let mean_time = f64::midpoint(length, 1.0);
+        let mean_equity = sum_equity / length;
+        let mut sxx = 0.0;
+        let mut sxy = 0.0;
+        for (index, value) in curve.iter().enumerate() {
+            #[allow(clippy::cast_precision_loss)]
+            let time = (index + 1) as f64;
+            let dt = time - mean_time;
+            sxx += dt * dt;
+            sxy += dt * (value - mean_equity);
+        }
+        // sxx > 0 for count >= 2 (distinct integer times), guaranteed by period >= 3.
+        let slope = sxy / sxx;
+        let intercept = mean_equity - slope * mean_time;
+        let mut sse = 0.0;
+        for (index, value) in curve.iter().enumerate() {
+            #[allow(clippy::cast_precision_loss)]
+            let time = (index + 1) as f64;
+            let residual = value - (intercept + slope * time);
+            sse += residual * residual;
+        }
+        if sse <= 0.0 {
+            return 0.0;
+        }
+        let se_slope = (sse / (length - 2.0) / sxx).sqrt();
+        slope / se_slope
+    }
+}
+
+impl Indicator for KRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "KRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_three() {
+        assert!(matches!(KRatio::new(2), Err(Error::InvalidPeriod { .. })));
+        assert!(matches!(KRatio::new(0), Err(Error::InvalidPeriod { .. })));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let kr = KRatio::new(30).unwrap();
+        assert_eq!(kr.period(), 30);
+        assert_eq!(kr.warmup_period(), 30);
+        assert_eq!(kr.name(), "KRatio");
+        assert!(!kr.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.01, 0.02, 0.03] -> equity curve [0.01, 0.03, 0.06].
+        // slope = 0.025, SE(slope) = sqrt((1/60000)/1/2) = 1/sqrt(120000).
+        // K-Ratio = 0.025 * sqrt(120000) = 5*sqrt(3) ≈ 8.660254.
+        let mut kr = KRatio::new(3).unwrap();
+        let out = kr.batch(&[0.01, 0.02, 0.03]);
+        let expected = 0.025_f64 / (1.0_f64 / 120_000.0).sqrt();
+        assert_relative_eq!(out[2].unwrap(), expected, epsilon = 1e-6);
+    }
+
+    #[test]
+    fn constant_returns_are_degenerate_zero() {
+        // A perfectly linear equity curve has zero residual scatter -> undefined.
+        let mut kr = KRatio::new(4).unwrap();
+        let last = kr.batch(&[0.01; 4]).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn rising_curve_is_positive() {
+        let mut kr = KRatio::new(5).unwrap();
+        let last = kr
+            .batch(&[0.01, 0.012, 0.009, 0.011, 0.013])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last > 0.0);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut kr = KRatio::new(3).unwrap();
+        assert_eq!(kr.update(0.01), None);
+        assert_eq!(kr.update(f64::NAN), None);
+        assert_eq!(kr.update(0.02), None);
+        assert!(kr.update(0.03).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut kr = KRatio::new(3).unwrap();
+        kr.batch(&[0.01, 0.02, 0.03]);
+        assert!(kr.is_ready());
+        kr.reset();
+        assert!(!kr.is_ready());
+        assert_eq!(kr.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| 0.001 + (f64::from(i) * 0.25).sin() * 0.01)
+            .collect();
+        let batch = KRatio::new(20).unwrap().batch(&rets);
+        let mut streamer = KRatio::new(20).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/indicators/m2_measure.rs

@@ -0,0 +1,232 @@
+//! M² / Modigliani–Modigliani measure — Sharpe expressed in benchmark return units.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// M² (Modigliani–Modigliani) measure over a trailing window of `period` returns.
+///
+/// ```text
+/// Sharpe = (mean(returns) − risk_free) / stddev(returns)
+/// M²     = risk_free + Sharpe · benchmark_stddev
+/// ```
+///
+/// The [`SharpeRatio`](crate::SharpeRatio) is dimensionless, which makes it hard to
+/// communicate: "0.8" means little to a client. M² rescales the Sharpe ratio back
+/// into *return units* by levering (or de-levering) the portfolio to the
+/// benchmark's volatility. The result answers a concrete question: "if this
+/// strategy had run at the market's risk level, what return would it have
+/// produced?" Two portfolios can then be ranked on the same risk-adjusted scale,
+/// and M² preserves the Sharpe ordering while being quoted as a percentage.
+///
+/// `stddev` is the sample standard deviation (Bessel's `n − 1`).
+/// `risk_free` is the per-period risk-free rate and `benchmark_stddev` the
+/// per-period volatility of the benchmark, both supplied by the caller at the
+/// return frequency. A flat window has zero volatility and the Sharpe ratio is
+/// undefined; the indicator returns `0.0` in that case rather than producing `NaN`.
+///
+/// Each `update` is O(1) — running sums maintain `Σr` and `Σr²` as the window slides.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, M2Measure};
+///
+/// let mut indicator = M2Measure::new(20, 0.0, 0.02).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update(0.001 + (f64::from(i) * 0.1).sin() * 0.01);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct M2Measure {
+    period: usize,
+    risk_free: f64,
+    benchmark_stddev: f64,
+    window: VecDeque<f64>,
+    sum: f64,
+    sum_sq: f64,
+}
+
+impl M2Measure {
+    /// Construct an M² measure over `period` returns with the given per-period
+    /// risk-free rate and benchmark standard deviation.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2`, or
+    /// [`Error::InvalidParameter`] if `risk_free` is not finite or
+    /// `benchmark_stddev` is negative or not finite.
+    pub fn new(period: usize, risk_free: f64, benchmark_stddev: f64) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "m2 measure needs period >= 2",
+            });
+        }
+        if !risk_free.is_finite() || !benchmark_stddev.is_finite() || benchmark_stddev < 0.0 {
+            return Err(Error::InvalidParameter {
+                message: "risk_free must be finite and benchmark_stddev finite and non-negative",
+            });
+        }
+        Ok(Self {
+            period,
+            risk_free,
+            benchmark_stddev,
+            window: VecDeque::with_capacity(period),
+            sum: 0.0,
+            sum_sq: 0.0,
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Configured per-period risk-free rate.
+    pub const fn risk_free(&self) -> f64 {
+        self.risk_free
+    }
+
+    /// Configured per-period benchmark standard deviation.
+    pub const fn benchmark_stddev(&self) -> f64 {
+        self.benchmark_stddev
+    }
+}
+
+impl Indicator for M2Measure {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("non-empty");
+            self.sum -= old;
+            self.sum_sq -= old * old;
+        }
+        self.window.push_back(ret);
+        self.sum += ret;
+        self.sum_sq += ret * ret;
+        if self.window.len() < self.period {
+            return None;
+        }
+        let n = self.period as f64;
+        let mean = self.sum / n;
+        let var = (self.sum_sq - n * mean * mean).max(0.0) / (n - 1.0);
+        let sd = var.sqrt();
+        if sd == 0.0 {
+            return Some(0.0);
+        }
+        let sharpe = (mean - self.risk_free) / sd;
+        Some(self.risk_free + sharpe * self.benchmark_stddev)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum = 0.0;
+        self.sum_sq = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "M2Measure"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            M2Measure::new(1, 0.0, 0.02),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn rejects_invalid_benchmark_stddev() {
+        assert!(matches!(
+            M2Measure::new(10, 0.0, -0.01),
+            Err(Error::InvalidParameter { .. })
+        ));
+        assert!(matches!(
+            M2Measure::new(10, f64::NAN, 0.02),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let m2 = M2Measure::new(20, 0.001, 0.02).unwrap();
+        assert_eq!(m2.period(), 20);
+        assert_relative_eq!(m2.risk_free(), 0.001, epsilon = 1e-12);
+        assert_relative_eq!(m2.benchmark_stddev(), 0.02, epsilon = 1e-12);
+        assert_eq!(m2.warmup_period(), 20);
+        assert_eq!(m2.name(), "M2Measure");
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.01, 0.02, 0.03, 0.04], rf = 0, benchmark_stddev = 0.02.
+        // mean = 0.025, sd = sqrt(0.000166666...), Sharpe = 0.025 / sd.
+        // M2 = 0 + Sharpe * 0.02.
+        let mut m2 = M2Measure::new(4, 0.0, 0.02).unwrap();
+        let out = m2.batch(&[0.01, 0.02, 0.03, 0.04]);
+        let sharpe = 0.025_f64 / (0.000_166_666_666_666_666_67_f64).sqrt();
+        assert_relative_eq!(out[3].unwrap(), sharpe * 0.02, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn constant_returns_yield_zero() {
+        let mut m2 = M2Measure::new(5, 0.0, 0.02).unwrap();
+        for v in m2.batch(&[0.01; 10]).into_iter().flatten() {
+            assert_relative_eq!(v, 0.0, epsilon = 1e-12);
+        }
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut m2 = M2Measure::new(3, 0.0, 0.02).unwrap();
+        assert_eq!(m2.update(0.01), None);
+        assert_eq!(m2.update(f64::NAN), None);
+        assert_eq!(m2.update(0.02), None);
+        assert!(m2.update(0.03).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut m2 = M2Measure::new(3, 0.0, 0.02).unwrap();
+        m2.batch(&[0.01, 0.02, 0.03]);
+        assert!(m2.is_ready());
+        m2.reset();
+        assert!(!m2.is_ready());
+        assert_eq!(m2.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..50)
+            .map(|i| 0.001 + (f64::from(i) * 0.2).sin() * 0.01)
+            .collect();
+        let batch = M2Measure::new(10, 0.0, 0.02).unwrap().batch(&rets);
+        let mut streamer = M2Measure::new(10, 0.0, 0.02).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,220 @@
+//! Martin Ratio (Ulcer Performance Index) — mean return over the Ulcer Index.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Martin Ratio — also called the Ulcer Performance Index (UPI) — over a trailing
+/// window of `period` returns.
+///
+/// ```text
+/// equity_t = Π_{i<=t} (1 + return_i)               (compounded curve)
+/// peak_t   = max_{s<=t} equity_s
+/// dd_t%    = 100 · (peak_t − equity_t) / peak_t      (percentage drawdown)
+/// UlcerIdx = sqrt( mean( dd_t%² ) )
+/// Martin   = mean(returns) / UlcerIdx
+/// ```
+///
+/// The Martin Ratio divides the average per-period return by the **Ulcer Index** —
+/// the root-mean-square of the *percentage* drawdowns. The Ulcer Index, by
+/// construction, measures the depth *and* duration of the time spent under water:
+/// a long shallow slump and a short deep one can score the same. Compared to
+/// Wickra's other drawdown ratios, Martin uses the RMS (not the average as in the
+/// [`SterlingRatio`](crate::SterlingRatio), nor the un-normalised sum-norm as in the
+/// [`BurkeRatio`](crate::BurkeRatio)) and expresses drawdowns in **percent**, so its
+/// denominator is on a `0..100` scale and its output is numerically smaller than
+/// the fractional-drawdown ratios. A window that never draws down has an Ulcer Index
+/// of zero and the indicator reports `0.0`.
+///
+/// The first value lands after `period` returns; each `update` rebuilds the equity
+/// curve over the window (O(period)), which is O(1) in the length of the overall
+/// series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, MartinRatio};
+///
+/// let mut indicator = MartinRatio::new(14).unwrap();
+/// let mut last = None;
+/// for i in 0..28 {
+///     last = indicator.update((f64::from(i) * 0.5).sin() * 0.05);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct MartinRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl MartinRatio {
+    /// Construct a Martin Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "martin ratio needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        #[allow(clippy::cast_precision_loss)]
+        let length = self.window.len() as f64;
+        let mut sum_return = 0.0;
+        let mut sum_drawdown_pct_sq = 0.0;
+        let mut equity = 1.0;
+        let mut peak: f64 = 1.0;
+        for ret in &self.window {
+            sum_return += *ret;
+            equity *= 1.0 + *ret;
+            peak = peak.max(equity);
+            let drawdown_pct = 100.0 * (peak - equity) / peak;
+            sum_drawdown_pct_sq += drawdown_pct * drawdown_pct;
+        }
+        let ulcer_index = (sum_drawdown_pct_sq / length).sqrt();
+        if ulcer_index > 0.0 {
+            (sum_return / length) / ulcer_index
+        } else {
+            0.0
+        }
+    }
+}
+
+impl Indicator for MartinRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "MartinRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            MartinRatio::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let mr = MartinRatio::new(14).unwrap();
+        assert_eq!(mr.period(), 14);
+        assert_eq!(mr.warmup_period(), 14);
+        assert_eq!(mr.name(), "MartinRatio");
+        assert!(!mr.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.1, -0.1, 0.1]: drawdowns% = [0, 10, 1].
+        // Ulcer Index = sqrt((0 + 100 + 1)/3) = sqrt(101/3).
+        // Martin = (0.1/3) / sqrt(101/3).
+        let mut mr = MartinRatio::new(3).unwrap();
+        let out = mr.batch(&[0.1, -0.1, 0.1]);
+        let expected = (0.1_f64 / 3.0) / (101.0_f64 / 3.0).sqrt();
+        assert_relative_eq!(out[2].unwrap(), expected, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn no_drawdown_is_zero() {
+        let mut mr = MartinRatio::new(3).unwrap();
+        let last = mr
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn losing_window_is_negative() {
+        let mut mr = MartinRatio::new(3).unwrap();
+        let last = mr
+            .batch(&[-0.05, -0.02, -0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last < 0.0);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut mr = MartinRatio::new(3).unwrap();
+        assert_eq!(mr.update(0.1), None);
+        assert_eq!(mr.update(f64::NAN), None);
+        assert_eq!(mr.update(-0.1), None);
+        assert!(mr.update(0.1).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut mr = MartinRatio::new(3).unwrap();
+        mr.batch(&[0.1, -0.1, 0.1]);
+        assert!(mr.is_ready());
+        mr.reset();
+        assert!(!mr.is_ready());
+        assert_eq!(mr.update(0.1), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.05)
+            .collect();
+        let batch = MartinRatio::new(14).unwrap().batch(&rets);
+        let mut streamer = MartinRatio::new(14).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -63,6 +63,7 @@ mod bomar_bands;
 mod breadth_thrust;
 mod breakaway;
 mod bullish_percent_index;
+mod burke_ratio;
 mod butterfly;
 mod calendar_spread;
 mod calmar_ratio;
@@ -84,6 +85,8 @@ mod cmf;
 mod cmo;
 mod coefficient_of_variation;
 mod cointegration;
+mod common_sense_ratio;
+mod composite_profile;
 mod concealing_baby_swallow;
 mod conditional_value_at_risk;
 mod connors_rsi;
@@ -117,6 +120,7 @@ mod downside_gap_three_methods;
 mod dpo;
 mod dragonfly_doji;
 mod drawdown_duration;
+mod dumpling_top;
 mod dx;
 mod dynamic_momentum_index;
 mod ease_of_movement;
@@ -130,6 +134,7 @@ mod ema;
 mod empirical_mode_decomposition;
 mod engulfing;
 mod equivolume;
+mod estimated_leverage_ratio;
 mod even_better_sinewave;
 mod evening_doji_star;
 mod evwma;
@@ -153,11 +158,14 @@ mod footprint;
 mod force_index;
 mod fractal_chaos_bands;
 mod frama;
+mod fry_pan_bottom;
 mod funding_basis;
+mod funding_implied_apr;
 mod funding_rate;
 mod funding_rate_mean;
 mod funding_rate_zscore;
 mod gain_loss_ratio;
+mod gain_to_pain_ratio;
 mod gap_side_by_side_white;
 mod garch11;
 mod garman_klass;
@@ -171,11 +179,14 @@ mod gravestone_doji;
 mod hammer;
 mod hanging_man;
 mod harami;
+mod harami_cross;
+mod hasbrouck_information_share;
 mod head_and_shoulders;
 mod heikin_ashi;
 mod heikin_ashi_oscillator;
 mod high_low_index;
 mod high_low_range;
+mod high_low_volume_nodes;
 mod high_wave;
 mod highpass_filter;
 mod hikkake;
@@ -206,6 +217,7 @@ mod inverted_hammer;
 mod jarque_bera;
 mod jma;
 mod jump_indicator;
+mod k_ratio;
 mod kagi_bars;
 mod kalman_hedge_ratio;
 mod kama;
@@ -233,6 +245,7 @@ mod log_return;
 mod long_legged_doji;
 mod long_line;
 mod long_short_ratio;
+mod m2_measure;
 mod ma_envelope;
 mod macd;
 mod macd_ext;
@@ -240,6 +253,7 @@ mod macd_fix;
 mod macd_histogram;
 mod mama;
 mod market_facilitation_index;
+mod martin_ratio;
 mod marubozu;
 mod mass_index;
 mod mat_hold;
@@ -263,8 +277,10 @@ mod mom;
 mod morning_doji_star;
 mod morning_evening_star;
 mod murrey_math_lines;
+mod naked_poc;
 mod natr;
 mod new_highs_new_lows;
+mod new_price_lines;
 mod nrtr;
 mod nvi;
 mod ob_imbalance_full;
@@ -273,9 +289,11 @@ mod ob_imbalance_topn;
 mod obv;
 mod oi_delta;
 mod oi_price_divergence;
+mod oi_to_volume_ratio;
 mod oi_weighted;
 mod omega_ratio;
 mod on_neck;
+mod open_interest_momentum;
 mod opening_marubozu;
 mod opening_range;
 mod order_flow_imbalance;
@@ -290,8 +308,10 @@ mod pearson_correlation;
 mod percent_above_ma;
 mod percent_b;
 mod percentage_trailing_stop;
+mod perpetual_premium_index;
 mod pgo;
 mod piercing_dark_cloud;
+mod pin;
 mod pivot_reversal;
 mod plus_di;
 mod plus_dm;
@@ -300,6 +320,7 @@ mod point_and_figure_bars;
 mod polarized_fractal_efficiency;
 mod ppo;
 mod ppo_histogram;
+mod profile_shape;
 mod profit_factor;
 mod projection_bands;
 mod projection_oscillator;
@@ -355,6 +376,7 @@ mod short_line;
 mod signed_volume;
 mod sine_wave;
 mod sine_weighted_ma;
+mod single_prints;
 mod skewness;
 mod sma;
 mod smi;
@@ -373,6 +395,7 @@ mod starc_bands;
 mod stc;
 mod std_dev;
 mod step_trailing_stop;
+mod sterling_ratio;
 mod stick_sandwich;
 mod stoch_rsi;
 mod stochastic;
@@ -380,6 +403,7 @@ mod stochastic_cci;
 mod super_smoother;
 mod super_trend;
 mod t3;
+mod tail_ratio;
 mod taker_buy_sell_ratio;
 mod takuri;
 mod tasuki_gap;
@@ -416,8 +440,10 @@ mod tick_index;
 mod tii;
 mod time_based_stop;
 mod time_of_day_return_profile;
+mod tower_top_bottom;
 mod tpo_profile;
 mod trade_imbalance;
+mod trade_sign_autocorrelation;
 mod trade_volume_index;
 mod trend_label;
 mod trend_strength_index;
@@ -427,6 +453,7 @@ mod triangle;
 mod trima;
 mod trin;
 mod triple_top_bottom;
+mod tristar;
 mod trix;
 mod true_range;
 mod tsf;
@@ -447,6 +474,7 @@ mod universal_oscillator;
 mod up_down_volume_ratio;
 mod upside_gap_three_methods;
 mod upside_gap_two_crows;
+mod upside_potential_ratio;
 mod value_area;
 mod value_at_risk;
 mod variance;
@@ -542,6 +570,7 @@ pub use bomar_bands::{BomarBands, BomarBandsOutput};
 pub use breadth_thrust::BreadthThrust;
 pub use breakaway::Breakaway;
 pub use bullish_percent_index::BullishPercentIndex;
+pub use burke_ratio::BurkeRatio;
 pub use butterfly::Butterfly;
 pub use calendar_spread::CalendarSpread;
 pub use calmar_ratio::CalmarRatio;
@@ -563,6 +592,8 @@ pub use cmf::ChaikinMoneyFlow;
 pub use cmo::Cmo;
 pub use coefficient_of_variation::CoefficientOfVariation;
 pub use cointegration::{Cointegration, CointegrationOutput};
+pub use common_sense_ratio::CommonSenseRatio;
+pub use composite_profile::{CompositeProfile, CompositeProfileOutput};
 pub use concealing_baby_swallow::ConcealingBabySwallow;
 pub use conditional_value_at_risk::ConditionalValueAtRisk;
 pub use connors_rsi::ConnorsRsi;
@@ -596,6 +627,7 @@ pub use downside_gap_three_methods::DownsideGapThreeMethods;
 pub use dpo::Dpo;
 pub use dragonfly_doji::DragonflyDoji;
 pub use drawdown_duration::DrawdownDuration;
+pub use dumpling_top::DumplingTop;
 pub use dx::Dx;
 pub use dynamic_momentum_index::DynamicMomentumIndex;
 pub use ease_of_movement::EaseOfMovement;
@@ -609,6 +641,7 @@ pub use ema::Ema;
 pub use empirical_mode_decomposition::EmpiricalModeDecomposition;
 pub use engulfing::Engulfing;
 pub use equivolume::{Equivolume, EquivolumeOutput};
+pub use estimated_leverage_ratio::EstimatedLeverageRatio;
 pub use even_better_sinewave::EvenBetterSinewave;
 pub use evening_doji_star::EveningDojiStar;
 pub use evwma::Evwma;
@@ -632,11 +665,14 @@ pub use footprint::{Footprint, FootprintLevel, FootprintOutput};
 pub use force_index::ForceIndex;
 pub use fractal_chaos_bands::{FractalChaosBands, FractalChaosBandsOutput};
 pub use frama::Frama;
+pub use fry_pan_bottom::FryPanBottom;
 pub use funding_basis::FundingBasis;
+pub use funding_implied_apr::FundingImpliedApr;
 pub use funding_rate::FundingRate;
 pub use funding_rate_mean::FundingRateMean;
 pub use funding_rate_zscore::FundingRateZScore;
 pub use gain_loss_ratio::GainLossRatio;
+pub use gain_to_pain_ratio::GainToPainRatio;
 pub use gap_side_by_side_white::GapSideBySideWhite;
 pub use garch11::Garch11;
 pub use garman_klass::GarmanKlassVolatility;
@@ -650,11 +686,14 @@ pub use gravestone_doji::GravestoneDoji;
 pub use hammer::Hammer;
 pub use hanging_man::HangingMan;
 pub use harami::Harami;
+pub use harami_cross::HaramiCross;
+pub use hasbrouck_information_share::HasbrouckInformationShare;
 pub use head_and_shoulders::HeadAndShoulders;
 pub use heikin_ashi::{HeikinAshi, HeikinAshiOutput};
 pub use heikin_ashi_oscillator::HeikinAshiOscillator;
 pub use high_low_index::HighLowIndex;
 pub use high_low_range::HighLowRange;
+pub use high_low_volume_nodes::{HighLowVolumeNodes, HighLowVolumeNodesOutput};
 pub use high_wave::HighWave;
 pub use highpass_filter::HighpassFilter;
 pub use hikkake::Hikkake;
@@ -685,6 +724,7 @@ pub use inverted_hammer::InvertedHammer;
 pub use jarque_bera::JarqueBera;
 pub use jma::Jma;
 pub use jump_indicator::JumpIndicator;
+pub use k_ratio::KRatio;
 pub use kagi_bars::{KagiBar, KagiBars};
 pub use kalman_hedge_ratio::{KalmanHedgeRatio, KalmanHedgeRatioOutput};
 pub use kama::Kama;
@@ -712,6 +752,7 @@ pub use log_return::LogReturn;
 pub use long_legged_doji::LongLeggedDoji;
 pub use long_line::LongLine;
 pub use long_short_ratio::LongShortRatio;
+pub use m2_measure::M2Measure;
 pub use ma_envelope::{MaEnvelope, MaEnvelopeOutput};
 pub use macd::{MacdIndicator, MacdOutput};
 pub use macd_ext::{MaType, MacdExt};
@@ -719,6 +760,7 @@ pub use macd_fix::MacdFix;
 pub use macd_histogram::MacdHistogram;
 pub use mama::{Mama, MamaOutput};
 pub use market_facilitation_index::MarketFacilitationIndex;
+pub use martin_ratio::MartinRatio;
 pub use marubozu::Marubozu;
 pub use mass_index::MassIndex;
 pub use mat_hold::MatHold;
@@ -742,8 +784,10 @@ pub use mom::Mom;
 pub use morning_doji_star::MorningDojiStar;
 pub use morning_evening_star::MorningEveningStar;
 pub use murrey_math_lines::{MurreyMathLines, MurreyMathLinesOutput};
+pub use naked_poc::NakedPoc;
 pub use natr::Natr;
 pub use new_highs_new_lows::NewHighsNewLows;
+pub use new_price_lines::NewPriceLines;
 pub use nrtr::{Nrtr, NrtrOutput};
 pub use nvi::Nvi;
 pub use ob_imbalance_full::OrderBookImbalanceFull;
@@ -752,9 +796,11 @@ pub use ob_imbalance_topn::OrderBookImbalanceTopN;
 pub use obv::Obv;
 pub use oi_delta::OpenInterestDelta;
 pub use oi_price_divergence::OIPriceDivergence;
+pub use oi_to_volume_ratio::OiToVolumeRatio;
 pub use oi_weighted::OIWeighted;
 pub use omega_ratio::OmegaRatio;
 pub use on_neck::OnNeck;
+pub use open_interest_momentum::OpenInterestMomentum;
 pub use opening_marubozu::OpeningMarubozu;
 pub use opening_range::{OpeningRange, OpeningRangeOutput};
 pub use order_flow_imbalance::OrderFlowImbalance;
@@ -769,8 +815,10 @@ pub use pearson_correlation::PearsonCorrelation;
 pub use percent_above_ma::PercentAboveMa;
 pub use percent_b::PercentB;
 pub use percentage_trailing_stop::PercentageTrailingStop;
+pub use perpetual_premium_index::PerpetualPremiumIndex;
 pub use pgo::Pgo;
 pub use piercing_dark_cloud::PiercingDarkCloud;
+pub use pin::Pin;
 pub use pivot_reversal::PivotReversal;
 pub use plus_di::PlusDi;
 pub use plus_dm::PlusDm;
@@ -779,6 +827,7 @@ pub use point_and_figure_bars::{PnfColumn, PointAndFigureBars};
 pub use polarized_fractal_efficiency::PolarizedFractalEfficiency;
 pub use ppo::Ppo;
 pub use ppo_histogram::PpoHistogram;
+pub use profile_shape::ProfileShape;
 pub use profit_factor::ProfitFactor;
 pub use projection_bands::{ProjectionBands, ProjectionBandsOutput};
 pub use projection_oscillator::ProjectionOscillator;
@@ -834,6 +883,7 @@ pub use short_line::ShortLine;
 pub use signed_volume::SignedVolume;
 pub use sine_wave::SineWave;
 pub use sine_weighted_ma::SineWeightedMa;
+pub use single_prints::SinglePrints;
 pub use skewness::Skewness;
 pub use sma::Sma;
 pub use smi::Smi;
@@ -852,6 +902,7 @@ pub use starc_bands::{StarcBands, StarcBandsOutput};
 pub use stc::Stc;
 pub use std_dev::StdDev;
 pub use step_trailing_stop::StepTrailingStop;
+pub use sterling_ratio::SterlingRatio;
 pub use stick_sandwich::StickSandwich;
 pub use stoch_rsi::StochRsi;
 pub use stochastic::{Stochastic, StochasticOutput};
@@ -859,6 +910,7 @@ pub use stochastic_cci::StochasticCci;
 pub use super_smoother::SuperSmoother;
 pub use super_trend::{SuperTrend, SuperTrendOutput};
 pub use t3::T3;
+pub use tail_ratio::TailRatio;
 pub use taker_buy_sell_ratio::TakerBuySellRatio;
 pub use takuri::Takuri;
 pub use tasuki_gap::TasukiGap;
@@ -895,8 +947,10 @@ pub use tick_index::TickIndex;
 pub use tii::Tii;
 pub use time_based_stop::TimeBasedStop;
 pub use time_of_day_return_profile::{TimeOfDayReturnProfile, TimeOfDayReturnProfileOutput};
+pub use tower_top_bottom::TowerTopBottom;
 pub use tpo_profile::{TpoProfile, TpoProfileOutput};
 pub use trade_imbalance::TradeImbalance;
+pub use trade_sign_autocorrelation::TradeSignAutocorrelation;
 pub use trade_volume_index::TradeVolumeIndex;
 pub use trend_label::TrendLabel;
 pub use trend_strength_index::TrendStrengthIndex;
@@ -906,6 +960,7 @@ pub use triangle::Triangle;
 pub use trima::Trima;
 pub use trin::Trin;
 pub use triple_top_bottom::TripleTopBottom;
+pub use tristar::Tristar;
 pub use trix::Trix;
 pub use true_range::TrueRange;
 pub use tsf::Tsf;
@@ -926,6 +981,7 @@ pub use universal_oscillator::UniversalOscillator;
 pub use up_down_volume_ratio::UpDownVolumeRatio;
 pub use upside_gap_three_methods::UpsideGapThreeMethods;
 pub use upside_gap_two_crows::UpsideGapTwoCrows;
+pub use upside_potential_ratio::UpsidePotentialRatio;
 pub use value_area::{ValueArea, ValueAreaOutput};
 pub use value_at_risk::ValueAtRisk;
 pub use variance::Variance;
@@ -1412,6 +1468,12 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "TasukiGap",
             "UniqueThreeRiver",
             "ConcealingBabySwallow",
+            "Tristar",
+            "HaramiCross",
+            "TowerTopBottom",
+            "FryPanBottom",
+            "DumplingTop",
+            "NewPriceLines",
         ],
     ),
     (
@@ -1434,6 +1496,9 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "Vpin",
             "AmihudIlliquidity",
             "RollMeasure",
+            "TradeSignAutocorrelation",
+            "Pin",
+            "HasbrouckInformationShare",
         ],
     ),
     (
@@ -1451,6 +1516,11 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "LiquidationFeatures",
             "TermStructureBasis",
             "CalendarSpread",
+            "EstimatedLeverageRatio",
+            "OiToVolumeRatio",
+            "PerpetualPremiumIndex",
+            "FundingImpliedApr",
+            "OpenInterestMomentum",
         ],
     ),
     (
@@ -1461,6 +1531,11 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "OpeningRange",
             "VolumeProfile",
             "TpoProfile",
+            "NakedPoc",
+            "SinglePrints",
+            "ProfileShape",
+            "HighLowVolumeNodes",
+            "CompositeProfile",
         ],
     ),
     (
@@ -1485,6 +1560,15 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
             "Alpha",
             "WinRate",
             "Expectancy",
+            "SterlingRatio",
+            "BurkeRatio",
+            "MartinRatio",
+            "TailRatio",
+            "KRatio",
+            "CommonSenseRatio",
+            "GainToPainRatio",
+            "UpsidePotentialRatio",
+            "M2Measure",
         ],
     ),
     (
@@ -1597,6 +1681,6 @@ mod family_tests {
         // the actual indicator count is the early-warning signal that an
         // indicator was added without being assigned a family.
         let total: usize = FAMILIES.iter().map(|(_, ns)| ns.len()).sum();
-        assert_eq!(total, 479, "FAMILIES total drifted from indicator count");
+        assert_eq!(total, 507, "FAMILIES total drifted from indicator count");
     }
 }

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

@@ -0,0 +1,318 @@
+//! Naked POC — the nearest prior-session point of control price has not yet revisited.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Naked (Virgin) POC — the nearest **untested** point of control from a prior
+/// session: a heavily-traded price the market has not traded back through since.
+///
+/// ```text
+/// every `session_len` candles forms a session; its POC (heaviest-volume price) is
+///   recorded as "naked"
+/// a naked POC becomes "tested" once a later candle's high-low range covers it
+/// output = the nearest still-naked POC to the current close (or the close itself
+///   if every prior POC has been revisited)
+/// ```
+///
+/// A point of control is a magnet — price tends to return to fair value. A *naked*
+/// (or virgin) POC is one that has not yet been revisited, so it carries an
+/// outstanding "pull": untested POCs are high-probability targets and
+/// support/resistance on the approach. This indicator records each completed
+/// session's POC, marks them tested as price trades through them, and reports the
+/// closest one still outstanding.
+///
+/// The first value lands after `session_len` candles (the first session's POC).
+/// Each `update` is O(`session_len · bins` + naked-count).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, NakedPoc};
+///
+/// let mut indicator = NakedPoc::new(20, 24).unwrap();
+/// let mut last = None;
+/// for i in 0..60 {
+///     let base = 100.0 + (f64::from(i) * 0.2).sin() * 5.0;
+///     let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct NakedPoc {
+    session_len: usize,
+    bins: usize,
+    session: VecDeque<Candle>,
+    naked: Vec<f64>,
+    last_close: f64,
+    ready: bool,
+    last: Option<f64>,
+}
+
+impl NakedPoc {
+    /// Construct a Naked POC tracker with the given `session_len` and profile
+    /// `bins`.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `session_len` or `bins` is zero.
+    pub fn new(session_len: usize, bins: usize) -> Result<Self> {
+        if session_len == 0 || bins == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            session_len,
+            bins,
+            session: VecDeque::with_capacity(session_len),
+            naked: Vec::new(),
+            last_close: 0.0,
+            ready: false,
+            last: None,
+        })
+    }
+
+    /// Configured `(session_len, bins)`.
+    pub const fn params(&self) -> (usize, usize) {
+        (self.session_len, self.bins)
+    }
+
+    /// Number of currently-naked POCs.
+    pub fn naked_count(&self) -> usize {
+        self.naked.len()
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn session_poc(&self) -> f64 {
+        let mut low = f64::INFINITY;
+        let mut high = f64::NEG_INFINITY;
+        for c in &self.session {
+            low = low.min(c.low);
+            high = high.max(c.high);
+        }
+        let span = high - low;
+        if span <= 0.0 {
+            return low;
+        }
+        let width = span / self.bins as f64;
+        let mut hist = vec![0.0; self.bins];
+        for c in &self.session {
+            if c.volume == 0.0 {
+                continue;
+            }
+            let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
+            let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
+            let share = c.volume / (hi_idx - lo_idx + 1) as f64;
+            for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
+                *bin += share;
+            }
+        }
+        let mut poc = 0;
+        let mut poc_vol = f64::NEG_INFINITY;
+        for (idx, &vol) in hist.iter().enumerate() {
+            if vol > poc_vol {
+                poc_vol = vol;
+                poc = idx;
+            }
+        }
+        low + (poc as f64 + 0.5) * width
+    }
+}
+
+impl Indicator for NakedPoc {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        // Test outstanding naked POCs against this candle's range.
+        self.naked
+            .retain(|&poc| !(candle.low <= poc && poc <= candle.high));
+        self.last_close = candle.close;
+
+        // Accumulate the session; finalize a POC at the boundary.
+        self.session.push_back(candle);
+        if self.session.len() == self.session_len {
+            let poc = self.session_poc();
+            self.naked.push(poc);
+            self.session.clear();
+            self.ready = true;
+        }
+
+        if !self.ready {
+            return None;
+        }
+        let nearest = self
+            .naked
+            .iter()
+            .copied()
+            .min_by(|a, b| {
+                (a - self.last_close)
+                    .abs()
+                    .total_cmp(&(b - self.last_close).abs())
+            })
+            .unwrap_or(self.last_close);
+        self.last = Some(nearest);
+        Some(nearest)
+    }
+
+    fn reset(&mut self) {
+        self.session.clear();
+        self.naked.clear();
+        self.last_close = 0.0;
+        self.ready = false;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.session_len
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "NakedPoc"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(high: f64, low: f64, close: f64, volume: f64) -> Candle {
+        Candle::new_unchecked(f64::midpoint(high, low), high, low, close, volume, 0)
+    }
+
+    #[test]
+    fn rejects_zero_params() {
+        assert!(matches!(NakedPoc::new(0, 24), Err(Error::PeriodZero)));
+        assert!(matches!(NakedPoc::new(20, 0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let n = NakedPoc::new(20, 24).unwrap();
+        assert_eq!(n.params(), (20, 24));
+        assert_eq!(n.naked_count(), 0);
+        assert_eq!(n.warmup_period(), 20);
+        assert_eq!(n.name(), "NakedPoc");
+        assert!(!n.is_ready());
+        assert_eq!(n.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_session_end() {
+        let mut n = NakedPoc::new(4, 8).unwrap();
+        let candles: Vec<Candle> = (0..6).map(|_| c(101.0, 99.0, 100.0, 1_000.0)).collect();
+        let out = n.batch(&candles);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn records_session_poc() {
+        let mut n = NakedPoc::new(4, 16).unwrap();
+        // A session clustered around 100 -> POC near 100.
+        n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
+        assert_eq!(n.naked_count(), 1);
+        let poc = n.value().unwrap();
+        assert!(
+            (poc - 100.0).abs() < 2.0,
+            "POC should be near 100, got {poc}"
+        );
+    }
+
+    #[test]
+    fn revisit_marks_poc_tested() {
+        let mut n = NakedPoc::new(4, 16).unwrap();
+        // Session 1 around 100 -> naked POC ~100.
+        n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
+        assert_eq!(n.naked_count(), 1);
+        // Trade away at 120 (does not cover 100) -> still naked.
+        n.update(c(121.0, 119.0, 120.0, 1_000.0));
+        assert_eq!(n.naked_count(), 1);
+        // A candle whose range covers 100 -> POC tested -> removed.
+        n.update(c(121.0, 95.0, 100.0, 1_000.0));
+        assert_eq!(n.naked_count(), 0);
+    }
+
+    #[test]
+    fn empty_naked_reports_close() {
+        let mut n = NakedPoc::new(4, 16).unwrap();
+        n.batch(&[c(101.0, 99.0, 100.0, 5_000.0); 4]);
+        // Wipe the naked POC with a covering candle.
+        let out = n.update(c(121.0, 95.0, 117.0, 1_000.0)).unwrap();
+        assert_eq!(n.naked_count(), 0);
+        assert!(
+            (out - 117.0).abs() < 1e-9,
+            "with no naked POC, output is the close"
+        );
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut n = NakedPoc::new(4, 8).unwrap();
+        n.batch(&[c(101.0, 99.0, 100.0, 1_000.0); 6]);
+        assert!(n.is_ready());
+        n.reset();
+        assert!(!n.is_ready());
+        assert_eq!(n.value(), None);
+        assert_eq!(n.naked_count(), 0);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..80)
+            .map(|i| {
+                let b = 100.0 + (f64::from(i) * 0.25).sin() * 9.0;
+                c(b + 1.0, b - 1.0, b, 1_000.0 + f64::from(i))
+            })
+            .collect();
+        let batch = NakedPoc::new(20, 24).unwrap().batch(&candles);
+        let mut b = NakedPoc::new(20, 24).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn flat_session_reports_price() {
+        // A session with zero high-low span returns the session price directly.
+        let mut n = NakedPoc::new(2, 4).unwrap();
+        n.update(c(50.0, 50.0, 50.0, 10.0));
+        assert_eq!(n.update(c(50.0, 50.0, 50.0, 10.0)), Some(50.0));
+    }
+
+    #[test]
+    fn zero_volume_session_is_handled() {
+        // Zero-volume candles are skipped in the histogram; a POC still emits.
+        let mut n = NakedPoc::new(2, 4).unwrap();
+        n.update(c(60.0, 40.0, 50.0, 0.0));
+        assert!(n.update(c(60.0, 40.0, 50.0, 0.0)).is_some());
+    }
+
+    #[test]
+    fn nearest_of_two_naked_pocs() {
+        // Two untouched POCs at distant prices accumulate; the one nearest the
+        // last close is reported (exercises the min-by comparison).
+        let mut n = NakedPoc::new(2, 4).unwrap();
+        n.update(c(11.0, 9.0, 10.0, 100.0));
+        n.update(c(11.0, 9.0, 10.0, 100.0)); // POC near 10
+        n.update(c(101.0, 99.0, 100.0, 100.0));
+        let v = n.update(c(101.0, 99.0, 100.0, 100.0)).unwrap(); // POC near 100
+        assert!(
+            v > 50.0,
+            "nearest to close 100 should be the upper POC, got {v}"
+        );
+    }
+}

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

@@ -0,0 +1,234 @@
+//! New Price Lines — the "eight/ten new price lines" exhaustion count.
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// New Price Lines — the Japanese "shinne" (new-price) exhaustion count: when the
+/// close has made `count` consecutive new highs (or lows), the trend is considered
+/// stretched and ripe for a pause or reversal.
+///
+/// ```text
+/// consecutive higher closes form "new price lines" up
+/// consecutive lower  closes form "new price lines" down
+/// signal = −1 once `count` consecutive higher closes (overbought / sell warning)
+/// signal = +1 once `count` consecutive lower  closes (oversold / buy warning)
+/// signal =  0 otherwise
+/// ```
+///
+/// Traditional Japanese practice flags **eight** new price lines (and a stronger
+/// **ten** or twelve) as the point where a directional run becomes exhausted —
+/// the market has gone up (or down) so many bars in a row that a corrective pause
+/// is statistically due. The signal stays active for every bar the streak remains
+/// at or above `count`, and clears the moment a close breaks the streak.
+///
+/// The first value lands on the second bar (one prior close is needed). The
+/// output is `+1` / `0` / `−1`. Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, NewPriceLines};
+///
+/// let mut indicator = NewPriceLines::new(8).unwrap();
+/// let mut last = None;
+/// for i in 0..12 {
+///     let close = 100.0 + f64::from(i); // 11 consecutive higher closes
+///     let c = Candle::new(close, close, close, close, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert_eq!(last, Some(-1.0));
+/// ```
+#[derive(Debug, Clone)]
+pub struct NewPriceLines {
+    count: usize,
+    prev_close: Option<f64>,
+    consec_up: usize,
+    consec_down: usize,
+    last: Option<f64>,
+}
+
+impl NewPriceLines {
+    /// Construct a New Price Lines counter that fires at `count` consecutive new
+    /// closes (classic `8`, stronger `10`/`12`).
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `count < 2`.
+    pub fn new(count: usize) -> Result<Self> {
+        if count < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "new price lines count must be >= 2",
+            });
+        }
+        Ok(Self {
+            count,
+            prev_close: None,
+            consec_up: 0,
+            consec_down: 0,
+            last: None,
+        })
+    }
+
+    /// Configured count threshold.
+    pub const fn count(&self) -> usize {
+        self.count
+    }
+
+    /// Current consecutive streak `(up, down)`.
+    pub const fn streak(&self) -> (usize, usize) {
+        (self.consec_up, self.consec_down)
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for NewPriceLines {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let close = candle.close;
+        let Some(prev) = self.prev_close else {
+            self.prev_close = Some(close);
+            return None;
+        };
+        if close > prev {
+            self.consec_up += 1;
+            self.consec_down = 0;
+        } else if close < prev {
+            self.consec_down += 1;
+            self.consec_up = 0;
+        } else {
+            self.consec_up = 0;
+            self.consec_down = 0;
+        }
+        self.prev_close = Some(close);
+
+        let v = if self.consec_up >= self.count {
+            -1.0
+        } else if self.consec_down >= self.count {
+            1.0
+        } else {
+            0.0
+        };
+        self.last = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.prev_close = None;
+        self.consec_up = 0;
+        self.consec_down = 0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "NewPriceLines"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(close: f64) -> Candle {
+        Candle::new_unchecked(close, close, close, close, 1_000.0, 0)
+    }
+
+    #[test]
+    fn rejects_small_count() {
+        assert!(matches!(
+            NewPriceLines::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(NewPriceLines::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let n = NewPriceLines::new(8).unwrap();
+        assert_eq!(n.count(), 8);
+        assert_eq!(n.streak(), (0, 0));
+        assert_eq!(n.warmup_period(), 2);
+        assert_eq!(n.name(), "NewPriceLines");
+        assert!(!n.is_ready());
+        assert_eq!(n.value(), None);
+    }
+
+    #[test]
+    fn first_bar_seeds_without_signal() {
+        let mut n = NewPriceLines::new(3).unwrap();
+        assert_eq!(n.update(c(100.0)), None);
+        assert!(n.update(c(101.0)).is_some());
+    }
+
+    #[test]
+    fn eight_higher_closes_signal_sell() {
+        let mut n = NewPriceLines::new(8).unwrap();
+        // 11 consecutive higher closes -> by the 9th the count reaches 8 -> -1.
+        let candles: Vec<Candle> = (0..12).map(|i| c(100.0 + f64::from(i))).collect();
+        let last = n.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, -1.0);
+    }
+
+    #[test]
+    fn eight_lower_closes_signal_buy() {
+        let mut n = NewPriceLines::new(8).unwrap();
+        let candles: Vec<Candle> = (0..12).map(|i| c(200.0 - f64::from(i))).collect();
+        let last = n.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 1.0);
+    }
+
+    #[test]
+    fn break_in_streak_clears_signal() {
+        let mut n = NewPriceLines::new(3).unwrap();
+        n.batch(&[c(100.0), c(101.0), c(102.0), c(103.0)]); // streak 3 -> -1
+        assert_eq!(n.value(), Some(-1.0));
+        // A lower close breaks the up streak.
+        assert_eq!(n.update(c(102.0)), Some(0.0));
+        assert_eq!(n.streak(), (0, 1));
+    }
+
+    #[test]
+    fn unchanged_close_resets_streak() {
+        let mut n = NewPriceLines::new(3).unwrap();
+        n.batch(&[c(100.0), c(101.0), c(102.0)]);
+        assert_eq!(n.update(c(102.0)), Some(0.0)); // equal -> reset
+        assert_eq!(n.streak(), (0, 0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut n = NewPriceLines::new(3).unwrap();
+        n.batch(&[c(100.0), c(101.0), c(102.0), c(103.0)]);
+        assert!(n.is_ready());
+        n.reset();
+        assert!(!n.is_ready());
+        assert_eq!(n.value(), None);
+        assert_eq!(n.streak(), (0, 0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..80)
+            .map(|i| c(100.0 + (f64::from(i) * 0.25).sin() * 9.0))
+            .collect();
+        let batch = NewPriceLines::new(8).unwrap().batch(&candles);
+        let mut b = NewPriceLines::new(8).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,154 @@
+//! OI-to-Volume Ratio — open interest relative to traded volume.
+
+use crate::derivatives::DerivativesTick;
+use crate::traits::Indicator;
+
+/// OI-to-Volume Ratio — open interest divided by the tick's total taker volume, a
+/// measure of how much position is *held* versus *turned over*.
+///
+/// ```text
+/// OIVR = open_interest / (taker_buy_volume + taker_sell_volume)
+/// ```
+///
+/// A high ratio means open interest dwarfs the volume trading it — positions are
+/// being held, not churned (low participation, potential complacency or a coiling
+/// market). A low ratio means heavy volume relative to outstanding interest —
+/// active churn, often around breakouts or capitulation. Watching the ratio change
+/// distinguishes new-money trends (OI and volume both rising) from short-covering
+/// or position rolls.
+///
+/// The ratio is non-negative; a tick with zero taker volume reports `0` rather than
+/// dividing by zero. It is stateless — each tick yields one value (no warmup). Each
+/// `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativesTick, Indicator, OiToVolumeRatio};
+///
+/// let mut indicator = OiToVolumeRatio::new();
+/// let tick = DerivativesTick::new(0.0, 100.0, 100.0, 100.0, 5_000.0, 0.0, 0.0, 400.0, 600.0, 0.0, 0.0, 0).unwrap();
+/// let oivr = indicator.update(tick).unwrap();
+/// assert!((oivr - 5.0).abs() < 1e-12); // 5000 / (400 + 600)
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct OiToVolumeRatio {
+    ready: bool,
+}
+
+impl OiToVolumeRatio {
+    /// Construct a new OI-to-Volume Ratio. The indicator is parameter-free.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { ready: false }
+    }
+}
+
+impl Indicator for OiToVolumeRatio {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        let volume = tick.taker_buy_volume + tick.taker_sell_volume;
+        let ratio = if volume > 0.0 {
+            tick.open_interest / volume
+        } else {
+            0.0
+        };
+        self.ready = true;
+        Some(ratio)
+    }
+
+    fn reset(&mut self) {
+        self.ready = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ready
+    }
+
+    fn name(&self) -> &'static str {
+        "OiToVolumeRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn tick(oi: f64, buy: f64, sell: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(
+            0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, buy, sell, 0.0, 0.0, 0,
+        )
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let o = OiToVolumeRatio::new();
+        assert_eq!(o.warmup_period(), 1);
+        assert_eq!(o.name(), "OiToVolumeRatio");
+        assert!(!o.is_ready());
+    }
+
+    #[test]
+    fn ratio_reference_value() {
+        let mut o = OiToVolumeRatio::new();
+        assert_relative_eq!(
+            o.update(tick(5_000.0, 400.0, 600.0)).unwrap(),
+            5.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn more_volume_lowers_ratio() {
+        let mut o = OiToVolumeRatio::new();
+        let held = o.update(tick(5_000.0, 100.0, 100.0)).unwrap();
+        let churned = o.update(tick(5_000.0, 1_000.0, 1_000.0)).unwrap();
+        assert!(churned < held);
+    }
+
+    #[test]
+    fn zero_volume_is_zero() {
+        let mut o = OiToVolumeRatio::new();
+        assert_relative_eq!(
+            o.update(tick(5_000.0, 0.0, 0.0)).unwrap(),
+            0.0,
+            epsilon = 1e-12
+        );
+    }
+
+    #[test]
+    fn ready_after_first_update() {
+        let mut o = OiToVolumeRatio::new();
+        assert!(!o.is_ready());
+        o.update(tick(5_000.0, 100.0, 100.0));
+        assert!(o.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut o = OiToVolumeRatio::new();
+        o.update(tick(5_000.0, 100.0, 100.0));
+        assert!(o.is_ready());
+        o.reset();
+        assert!(!o.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..40)
+            .map(|i| tick(5_000.0, 100.0 + f64::from(i), 100.0))
+            .collect();
+        let batch = OiToVolumeRatio::new().batch(&ticks);
+        let mut b = OiToVolumeRatio::new();
+        let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,221 @@
+//! Open-Interest Momentum — the rate of change of open interest over a lookback.
+
+use std::collections::VecDeque;
+
+use crate::derivatives::DerivativesTick;
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Open-Interest Momentum — the percentage rate of change of open interest over a
+/// `period`-tick lookback.
+///
+/// ```text
+/// OIM = 100 · (OI_t − OI_{t−period}) / OI_{t−period}
+/// ```
+///
+/// Where [`OIDelta`](crate::OIDelta) reports the single-tick change in open
+/// interest, OI Momentum measures the trend in positioning over a window: positive
+/// values mean open interest is expanding (new money entering — a position build
+/// that fuels the prevailing move), negative values mean it is contracting
+/// (positions being closed — deleveraging or short-covering). Read alongside price:
+/// rising OI with rising price is a strong new-long trend, while rising price with
+/// falling OI is a short-covering rally on borrowed time.
+///
+/// The output is a percentage and may be negative. A zero base open interest
+/// `period` ticks ago reports `0` rather than dividing by zero. The first value
+/// lands after `period + 1` inputs. Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativesTick, Indicator, OpenInterestMomentum};
+///
+/// let mut indicator = OpenInterestMomentum::new(5).unwrap();
+/// let mut last = None;
+/// for i in 0..20 {
+///     let oi = 1_000.0 + f64::from(i) * 100.0;
+///     let tick = DerivativesTick::new(0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
+///     last = indicator.update(tick);
+/// }
+/// assert!(last.unwrap() > 0.0); // expanding OI
+/// ```
+#[derive(Debug, Clone)]
+pub struct OpenInterestMomentum {
+    period: usize,
+    window: VecDeque<f64>,
+    last: Option<f64>,
+}
+
+impl OpenInterestMomentum {
+    /// Construct an OI Momentum over a `period`-tick lookback.
+    ///
+    /// # 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 + 1),
+            last: None,
+        })
+    }
+
+    /// Configured lookback period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for OpenInterestMomentum {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        if self.window.len() == self.period + 1 {
+            self.window.pop_front();
+        }
+        self.window.push_back(tick.open_interest);
+        if self.window.len() < self.period + 1 {
+            return None;
+        }
+        let base = *self.window.front().expect("non-empty");
+        let current = tick.open_interest;
+        let oim = if base > 0.0 {
+            100.0 * (current - base) / base
+        } else {
+            0.0
+        };
+        self.last = Some(oim);
+        Some(oim)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        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 {
+        "OpenInterestMomentum"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn tick(oi: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(
+            0.0, 100.0, 100.0, 100.0, oi, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0,
+        )
+    }
+
+    #[test]
+    fn rejects_zero_period() {
+        assert!(matches!(
+            OpenInterestMomentum::new(0),
+            Err(Error::PeriodZero)
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let o = OpenInterestMomentum::new(5).unwrap();
+        assert_eq!(o.period(), 5);
+        assert_eq!(o.warmup_period(), 6);
+        assert_eq!(o.name(), "OpenInterestMomentum");
+        assert!(!o.is_ready());
+        assert_eq!(o.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut o = OpenInterestMomentum::new(3).unwrap();
+        let ticks: Vec<DerivativesTick> = (0..6)
+            .map(|i| tick(1_000.0 + f64::from(i) * 100.0))
+            .collect();
+        let out = o.batch(&ticks);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn reference_value() {
+        // period 2: OI 1000 -> 1200 over the window -> +20%.
+        let mut o = OpenInterestMomentum::new(2).unwrap();
+        let out = o.batch(&[tick(1_000.0), tick(1_100.0), tick(1_200.0)]);
+        assert_relative_eq!(out[2].unwrap(), 20.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn expanding_oi_is_positive() {
+        let mut o = OpenInterestMomentum::new(5).unwrap();
+        let ticks: Vec<DerivativesTick> = (0..20)
+            .map(|i| tick(1_000.0 + f64::from(i) * 100.0))
+            .collect();
+        let last = o.batch(&ticks).into_iter().flatten().last().unwrap();
+        assert!(last > 0.0);
+    }
+
+    #[test]
+    fn contracting_oi_is_negative() {
+        let mut o = OpenInterestMomentum::new(5).unwrap();
+        let ticks: Vec<DerivativesTick> = (0..20)
+            .map(|i| tick(3_000.0 - f64::from(i) * 100.0))
+            .collect();
+        let last = o.batch(&ticks).into_iter().flatten().last().unwrap();
+        assert!(last < 0.0);
+    }
+
+    #[test]
+    fn zero_base_is_zero() {
+        let mut o = OpenInterestMomentum::new(2).unwrap();
+        let out = o.batch(&[tick(0.0), tick(100.0), tick(200.0)]);
+        assert_relative_eq!(out[2].unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut o = OpenInterestMomentum::new(3).unwrap();
+        o.batch(
+            &(0..10)
+                .map(|i| tick(1_000.0 + f64::from(i) * 50.0))
+                .collect::<Vec<_>>(),
+        );
+        assert!(o.is_ready());
+        o.reset();
+        assert!(!o.is_ready());
+        assert_eq!(o.value(), None);
+        assert_eq!(o.update(tick(1_000.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..80)
+            .map(|i| tick(1_000.0 + (f64::from(i) * 0.25).sin() * 300.0))
+            .collect();
+        let batch = OpenInterestMomentum::new(10).unwrap().batch(&ticks);
+        let mut b = OpenInterestMomentum::new(10).unwrap();
+        let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,139 @@
+//! Perpetual Premium Index — the perp mark price relative to spot.
+
+use crate::derivatives::DerivativesTick;
+use crate::traits::Indicator;
+
+/// Perpetual Premium Index — the perpetual's mark price relative to the spot index
+/// it tracks, as a fraction.
+///
+/// ```text
+/// premium = (mark_price − index_price) / index_price
+/// ```
+///
+/// A perpetual swap is pegged to spot by the funding mechanism, but it can still
+/// trade at a premium (above spot) or discount (below). A positive premium signals
+/// net long demand willing to pay up to hold the perp — bullish positioning, and
+/// the proximate driver of positive funding; a negative premium signals the
+/// reverse. Sustained extremes flag crowded positioning ripe for a funding-driven
+/// mean reversion.
+///
+/// The output is centred on zero and dimensionless (a fraction; multiply by `100`
+/// for percent). `index_price` is validated strictly positive on the tick, so the
+/// division is always defined. It is stateless — each tick yields one value (no
+/// warmup). Each `update` is O(1).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{DerivativesTick, Indicator, PerpetualPremiumIndex};
+///
+/// let mut indicator = PerpetualPremiumIndex::new();
+/// // Mark 101 vs index 100 -> +1% premium.
+/// let tick = DerivativesTick::new(0.0, 101.0, 100.0, 101.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0).unwrap();
+/// let premium = indicator.update(tick).unwrap();
+/// assert!((premium - 0.01).abs() < 1e-12);
+/// ```
+#[derive(Debug, Clone, Default)]
+pub struct PerpetualPremiumIndex {
+    ready: bool,
+}
+
+impl PerpetualPremiumIndex {
+    /// Construct a new Perpetual Premium Index. The indicator is parameter-free.
+    #[must_use]
+    pub const fn new() -> Self {
+        Self { ready: false }
+    }
+}
+
+impl Indicator for PerpetualPremiumIndex {
+    type Input = DerivativesTick;
+    type Output = f64;
+
+    fn update(&mut self, tick: DerivativesTick) -> Option<f64> {
+        let premium = (tick.mark_price - tick.index_price) / tick.index_price;
+        self.ready = true;
+        Some(premium)
+    }
+
+    fn reset(&mut self) {
+        self.ready = false;
+    }
+
+    fn warmup_period(&self) -> usize {
+        1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.ready
+    }
+
+    fn name(&self) -> &'static str {
+        "PerpetualPremiumIndex"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn tick(mark: f64, index: f64) -> DerivativesTick {
+        DerivativesTick::new_unchecked(0.0, mark, index, mark, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0)
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let p = PerpetualPremiumIndex::new();
+        assert_eq!(p.warmup_period(), 1);
+        assert_eq!(p.name(), "PerpetualPremiumIndex");
+        assert!(!p.is_ready());
+    }
+
+    #[test]
+    fn premium_reference_value() {
+        let mut p = PerpetualPremiumIndex::new();
+        assert_relative_eq!(p.update(tick(101.0, 100.0)).unwrap(), 0.01, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn discount_is_negative() {
+        let mut p = PerpetualPremiumIndex::new();
+        assert!(p.update(tick(99.0, 100.0)).unwrap() < 0.0);
+    }
+
+    #[test]
+    fn at_par_is_zero() {
+        let mut p = PerpetualPremiumIndex::new();
+        assert_relative_eq!(p.update(tick(100.0, 100.0)).unwrap(), 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ready_after_first_update() {
+        let mut p = PerpetualPremiumIndex::new();
+        assert!(!p.is_ready());
+        p.update(tick(100.0, 100.0));
+        assert!(p.is_ready());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut p = PerpetualPremiumIndex::new();
+        p.update(tick(101.0, 100.0));
+        assert!(p.is_ready());
+        p.reset();
+        assert!(!p.is_ready());
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let ticks: Vec<DerivativesTick> = (0..40)
+            .map(|i| tick(100.0 + (f64::from(i) * 0.3).sin(), 100.0))
+            .collect();
+        let batch = PerpetualPremiumIndex::new().batch(&ticks);
+        let mut b = PerpetualPremiumIndex::new();
+        let streamed: Vec<_> = ticks.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,223 @@
+//! PIN — Probability of Informed Trading (single-window EKOP estimate).
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// PIN — the **Probability of Informed Trading**, estimated from the buy/sell order
+/// imbalance over a rolling window of trades.
+///
+/// ```text
+/// over the last `window` trades: B = buys, S = sells   (B + S = window)
+/// PIN ≈ |B − S| / (B + S)        ∈ [0, 1]
+/// ```
+///
+/// The Easley-Kiefer-O'Hara-Paperman (EKOP) model splits order flow into an
+/// uninformed component (balanced buys and sells, rate `ε` per side) and an
+/// informed component that trades one-directionally when private information
+/// arrives (rate `μ`, probability `α`). The probability that any given trade is
+/// information-motivated is `PIN = αμ / (αμ + 2ε)`. Estimated over a single window,
+/// the informed flow shows up as the **net imbalance** `|B − S|` and the uninformed
+/// flow as the balanced remainder, giving the moment estimator above. A high PIN
+/// flags a one-sided, likely-informed market; a low PIN flags balanced, uninformed
+/// flow.
+///
+/// This is distinct from [`Vpin`](crate::Vpin), the volume-synchronised variant
+/// that buckets by volume and uses bulk-volume classification; here trades are
+/// counted in event time and classified by their tagged aggressor side. The full
+/// PIN is fit by maximum likelihood over many periods — this single-window
+/// estimator is the streaming moment approximation. The output is in `[0, 1]`; the
+/// first value lands after `window` trades.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Pin, Side, Trade};
+///
+/// let mut indicator = Pin::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     // All buys -> maximally one-sided -> PIN 1.
+///     last = indicator.update(Trade::new(100.0, 1.0, Side::Buy, i).unwrap());
+/// }
+/// assert!((last.unwrap() - 1.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct Pin {
+    window: usize,
+    sides: VecDeque<f64>,
+    buy_count: usize,
+    last: Option<f64>,
+}
+
+impl Pin {
+    /// Construct a PIN estimator over `window` trades.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `window == 0`.
+    pub fn new(window: usize) -> Result<Self> {
+        if window == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            window,
+            sides: VecDeque::with_capacity(window),
+            buy_count: 0,
+            last: None,
+        })
+    }
+
+    /// Configured window of trades.
+    pub const fn window(&self) -> usize {
+        self.window
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for Pin {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        let is_buy = trade.side.sign() > 0.0;
+        if self.sides.len() == self.window {
+            let old = self.sides.pop_front().expect("non-empty");
+            if old > 0.0 {
+                self.buy_count -= 1;
+            }
+        }
+        self.sides.push_back(if is_buy { 1.0 } else { 0.0 });
+        if is_buy {
+            self.buy_count += 1;
+        }
+        if self.sides.len() < self.window {
+            return None;
+        }
+        // The window is full and `window >= 1` (zero is rejected at
+        // construction), so the trade count is always positive — `|B - S| / N`
+        // needs no zero guard.
+        let buys = self.buy_count as f64;
+        let sells = self.window as f64 - buys;
+        let total = self.window as f64;
+        let pin = (buys - sells).abs() / total;
+        self.last = Some(pin);
+        Some(pin)
+    }
+
+    fn reset(&mut self) {
+        self.sides.clear();
+        self.buy_count = 0;
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.window
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "PIN"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn buy() -> Trade {
+        Trade::new_unchecked(100.0, 1.0, Side::Buy, 0)
+    }
+
+    fn sell() -> Trade {
+        Trade::new_unchecked(100.0, 1.0, Side::Sell, 0)
+    }
+
+    #[test]
+    fn rejects_zero_window() {
+        assert!(matches!(Pin::new(0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let p = Pin::new(20).unwrap();
+        assert_eq!(p.window(), 20);
+        assert_eq!(p.warmup_period(), 20);
+        assert_eq!(p.name(), "PIN");
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut p = Pin::new(4).unwrap();
+        let out = p.batch(&[buy(), buy(), buy(), buy(), buy()]);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn one_sided_flow_is_one() {
+        let mut p = Pin::new(10).unwrap();
+        let trades: Vec<Trade> = (0..20).map(|_| buy()).collect();
+        let last = p.batch(&trades).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 1.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn balanced_flow_is_zero() {
+        let mut p = Pin::new(10).unwrap();
+        let trades: Vec<Trade> = (0..20)
+            .map(|i| if i % 2 == 0 { buy() } else { sell() })
+            .collect();
+        let last = p.batch(&trades).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn output_in_range() {
+        let mut p = Pin::new(16).unwrap();
+        let trades: Vec<Trade> = (0..200)
+            .map(|i| if (i * 5 % 13) < 8 { buy() } else { sell() })
+            .collect();
+        for v in p.batch(&trades).into_iter().flatten() {
+            assert!((0.0..=1.0).contains(&v));
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut p = Pin::new(4).unwrap();
+        p.batch(&[buy(), buy(), sell(), buy()]);
+        assert!(p.is_ready());
+        p.reset();
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+        assert_eq!(p.update(buy()), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..120)
+            .map(|i| if i % 3 == 0 { sell() } else { buy() })
+            .collect();
+        let batch = Pin::new(16).unwrap().batch(&trades);
+        let mut b = Pin::new(16).unwrap();
+        let streamed: Vec<_> = trades.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,285 @@
+//! Profile Shape — classifies the volume profile as b-shape, P-shape, or D/normal.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Profile Shape — classifies a rolling volume profile by where its point of
+/// control (POC) sits within the range: `b`, `P`, or `D` (normal).
+///
+/// ```text
+/// build a `bins`-bucket volume profile over the last `period` candles
+/// poc_idx = bin with the most volume
+/// +1  P-shape : POC in the upper third  (heavy top, thin tail down) — short-covering / accumulation
+/// −1  b-shape : POC in the lower third  (heavy bottom, thin tail up) — long-liquidation / distribution
+///  0  D/normal: POC in the middle third (balanced bell)
+/// ```
+///
+/// Market Profile readers classify the day's shape by the location of the heaviest
+/// trading. A **P-shape** (control high, a thin tail beneath) typically marks
+/// short-covering or the start of accumulation; a **b-shape** (control low, thin
+/// tail above) marks long liquidation or distribution; a **D-shape** is a balanced,
+/// two-sided day. Reducing the profile to this three-way code gives a compact,
+/// streaming read of market posture.
+///
+/// The output is `+1` / `0` / `−1`. The first value lands after `period` candles;
+/// each `update` rebuilds the profile in O(`period · bins`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, ProfileShape};
+///
+/// let mut indicator = ProfileShape::new(20, 24).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let base = 100.0 + (f64::from(i) * 0.3).sin() * 5.0;
+///     let c = Candle::new(base, base + 1.0, base - 1.0, base, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct ProfileShape {
+    period: usize,
+    bins: usize,
+    window: VecDeque<Candle>,
+    last: Option<f64>,
+}
+
+impl ProfileShape {
+    /// Construct a Profile Shape classifier.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period` is zero, or
+    /// [`Error::InvalidPeriod`] if `bins < 3` (the three-way split needs three
+    /// zones).
+    pub fn new(period: usize, bins: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        if bins < 3 {
+            return Err(Error::InvalidPeriod {
+                message: "profile shape needs bins >= 3",
+            });
+        }
+        Ok(Self {
+            period,
+            bins,
+            window: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured `(period, bins)`.
+    pub const fn params(&self) -> (usize, usize) {
+        (self.period, self.bins)
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn poc_index(&self) -> usize {
+        let mut low = f64::INFINITY;
+        let mut high = f64::NEG_INFINITY;
+        for c in &self.window {
+            low = low.min(c.low);
+            high = high.max(c.high);
+        }
+        let mut hist = vec![0.0; self.bins];
+        let span = high - low;
+        if span > 0.0 {
+            let width = span / self.bins as f64;
+            for c in &self.window {
+                if c.volume == 0.0 {
+                    continue;
+                }
+                let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
+                let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
+                let share = c.volume / (hi_idx - lo_idx + 1) as f64;
+                for bin in hist.iter_mut().take(hi_idx + 1).skip(lo_idx) {
+                    *bin += share;
+                }
+            }
+        }
+        let mut poc_idx = 0;
+        let mut poc_vol = f64::NEG_INFINITY;
+        for (idx, &vol) in hist.iter().enumerate() {
+            if vol > poc_vol {
+                poc_vol = vol;
+                poc_idx = idx;
+            }
+        }
+        poc_idx
+    }
+}
+
+impl Indicator for ProfileShape {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(candle);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let poc = self.poc_index();
+        let lower = self.bins / 3;
+        let upper = self.bins - self.bins / 3;
+        let shape = if poc >= upper {
+            1.0
+        } else if poc < lower {
+            -1.0
+        } else {
+            0.0
+        };
+        self.last = Some(shape);
+        Some(shape)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "ProfileShape"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(high: f64, low: f64, volume: f64) -> Candle {
+        Candle::new_unchecked(
+            f64::midpoint(high, low),
+            high,
+            low,
+            f64::midpoint(high, low),
+            volume,
+            0,
+        )
+    }
+
+    #[test]
+    fn rejects_invalid_params() {
+        assert!(matches!(ProfileShape::new(0, 24), Err(Error::PeriodZero)));
+        assert!(matches!(
+            ProfileShape::new(20, 2),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let p = ProfileShape::new(20, 24).unwrap();
+        assert_eq!(p.params(), (20, 24));
+        assert_eq!(p.warmup_period(), 20);
+        assert_eq!(p.name(), "ProfileShape");
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut p = ProfileShape::new(4, 9).unwrap();
+        let candles: Vec<Candle> = (0..6).map(|_| c(110.0, 90.0, 1_000.0)).collect();
+        let out = p.batch(&candles);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn heavy_top_is_p_shape() {
+        // Volume concentrated near the top of the range -> P-shape -> +1.
+        let mut p = ProfileShape::new(6, 9).unwrap();
+        let mut candles: Vec<Candle> = (0..5).map(|_| c(119.0, 117.0, 5_000.0)).collect();
+        candles.push(c(119.0, 80.0, 50.0)); // a thin tail down to 80
+        let last = p.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 1.0);
+    }
+
+    #[test]
+    fn heavy_bottom_is_b_shape() {
+        let mut p = ProfileShape::new(6, 9).unwrap();
+        let mut candles: Vec<Candle> = (0..5).map(|_| c(83.0, 81.0, 5_000.0)).collect();
+        candles.push(c(120.0, 81.0, 50.0)); // a thin tail up to 120
+        let last = p.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, -1.0);
+    }
+
+    #[test]
+    fn balanced_is_d_shape() {
+        // Volume concentrated in the middle -> D/normal -> 0.
+        let mut p = ProfileShape::new(6, 9).unwrap();
+        let mut candles: Vec<Candle> = (0..5).map(|_| c(101.0, 99.0, 5_000.0)).collect();
+        candles.push(c(120.0, 80.0, 50.0)); // thin tails both ways, POC in the middle
+        let last = p.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut p = ProfileShape::new(4, 9).unwrap();
+        p.batch(&[c(110.0, 90.0, 1_000.0); 6]);
+        assert!(p.is_ready());
+        p.reset();
+        assert!(!p.is_ready());
+        assert_eq!(p.value(), None);
+        assert_eq!(p.update(c(110.0, 90.0, 1_000.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..80)
+            .map(|i| {
+                c(
+                    110.0 + (f64::from(i) * 0.25).sin() * 9.0,
+                    90.0,
+                    1_000.0 + f64::from(i),
+                )
+            })
+            .collect();
+        let batch = ProfileShape::new(20, 24).unwrap().batch(&candles);
+        let mut b = ProfileShape::new(20, 24).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn flat_window_is_handled() {
+        // Zero high-low span skips the histogram pass entirely.
+        let mut p = ProfileShape::new(2, 4).unwrap();
+        p.update(c(50.0, 50.0, 10.0));
+        assert!(p.update(c(50.0, 50.0, 10.0)).is_some());
+    }
+
+    #[test]
+    fn zero_volume_window_is_handled() {
+        // Non-flat window of zero-volume candles hits the skip path.
+        let mut p = ProfileShape::new(2, 4).unwrap();
+        p.update(c(60.0, 40.0, 0.0));
+        assert!(p.update(c(60.0, 40.0, 0.0)).is_some());
+    }
+}

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

@@ -0,0 +1,253 @@
+//! Single Prints — count of price levels touched by exactly one bar (low acceptance).
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Single Prints — the number of price levels (bins) in the rolling profile that
+/// were touched by **exactly one** bar, marking zones of low acceptance / fast
+/// movement.
+///
+/// ```text
+/// for each of `bins` price levels over the last `period` candles:
+///   touches = number of bars whose high-low range covers that level
+/// SinglePrints = count of levels with touches == 1
+/// ```
+///
+/// In Market Profile a "single print" is a price the market traded through so
+/// quickly that only one time-period printed there — a footprint of an aggressive,
+/// one-sided move with little two-way trade. Single prints often act as support or
+/// resistance on a retest (the imbalance gets "repaired") and mark the edges of
+/// rapid moves. Counting them per profile gives a streaming gauge of how much of
+/// the recent range was traversed without acceptance: a high count means a fast,
+/// trending, low-rotation market; a low count means a balanced, well-traded range.
+///
+/// The output is a non-negative count. The first value lands after `period`
+/// candles; each `update` rebuilds the touch histogram in O(`period · bins`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Candle, Indicator, SinglePrints};
+///
+/// let mut indicator = SinglePrints::new(20, 24).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let base = 100.0 + f64::from(i); // a one-directional ramp -> many single prints
+///     let c = Candle::new(base, base + 0.5, base - 0.5, base, 1_000.0, 0).unwrap();
+///     last = indicator.update(c);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct SinglePrints {
+    period: usize,
+    bins: usize,
+    window: VecDeque<Candle>,
+    last: Option<f64>,
+}
+
+impl SinglePrints {
+    /// Construct a Single Prints counter.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::PeriodZero`] if `period` or `bins` is zero.
+    pub fn new(period: usize, bins: usize) -> Result<Self> {
+        if period == 0 || bins == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            bins,
+            window: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured `(period, bins)`.
+    pub const fn params(&self) -> (usize, usize) {
+        (self.period, self.bins)
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    fn count_single_prints(&self) -> usize {
+        let mut low = f64::INFINITY;
+        let mut high = f64::NEG_INFINITY;
+        for c in &self.window {
+            low = low.min(c.low);
+            high = high.max(c.high);
+        }
+        let span = high - low;
+        if span <= 0.0 {
+            return 0;
+        }
+        let width = span / self.bins as f64;
+        let mut touches = vec![0u32; self.bins];
+        for c in &self.window {
+            let lo_idx = (((c.low - low) / width).floor() as usize).min(self.bins - 1);
+            let hi_idx = (((c.high - low) / width).floor() as usize).min(self.bins - 1);
+            for t in touches.iter_mut().take(hi_idx + 1).skip(lo_idx) {
+                *t += 1;
+            }
+        }
+        touches.iter().filter(|&&t| t == 1).count()
+    }
+}
+
+impl Indicator for SinglePrints {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(candle);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let count = self.count_single_prints() as f64;
+        self.last = Some(count);
+        Some(count)
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "SinglePrints"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(high: f64, low: f64) -> Candle {
+        Candle::new_unchecked(
+            f64::midpoint(high, low),
+            high,
+            low,
+            f64::midpoint(high, low),
+            1_000.0,
+            0,
+        )
+    }
+
+    #[test]
+    fn rejects_zero_params() {
+        assert!(matches!(SinglePrints::new(0, 24), Err(Error::PeriodZero)));
+        assert!(matches!(SinglePrints::new(20, 0), Err(Error::PeriodZero)));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let s = SinglePrints::new(20, 24).unwrap();
+        assert_eq!(s.params(), (20, 24));
+        assert_eq!(s.warmup_period(), 20);
+        assert_eq!(s.name(), "SinglePrints");
+        assert!(!s.is_ready());
+        assert_eq!(s.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut s = SinglePrints::new(4, 8).unwrap();
+        let candles: Vec<Candle> = (0..6)
+            .map(|i| c(101.0 + f64::from(i), 99.0 + f64::from(i)))
+            .collect();
+        let out = s.batch(&candles);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn flat_range_has_no_single_prints() {
+        // Every bar covers the same single price -> zero span -> 0.
+        let mut s = SinglePrints::new(4, 8).unwrap();
+        let last = s
+            .batch(&[c(100.0, 100.0); 6])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_eq!(last, 0.0);
+    }
+
+    #[test]
+    fn ramp_has_many_single_prints() {
+        // A one-directional ramp visits most levels exactly once.
+        let mut s = SinglePrints::new(10, 24).unwrap();
+        let candles: Vec<Candle> = (0..10)
+            .map(|i| c(100.5 + f64::from(i), 99.5 + f64::from(i)))
+            .collect();
+        let last = s.batch(&candles).into_iter().flatten().last().unwrap();
+        assert!(
+            last > 0.0,
+            "a ramp should produce single prints, got {last}"
+        );
+    }
+
+    #[test]
+    fn output_non_negative() {
+        let mut s = SinglePrints::new(14, 24).unwrap();
+        for v in s
+            .batch(
+                &(0..60)
+                    .map(|i| c(110.0 + (f64::from(i) * 0.3).sin() * 8.0, 90.0))
+                    .collect::<Vec<_>>(),
+            )
+            .into_iter()
+            .flatten()
+        {
+            assert!(v >= 0.0);
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut s = SinglePrints::new(4, 8).unwrap();
+        s.batch(
+            &(0..6)
+                .map(|i| c(101.0 + f64::from(i), 99.0 + f64::from(i)))
+                .collect::<Vec<_>>(),
+        );
+        assert!(s.is_ready());
+        s.reset();
+        assert!(!s.is_ready());
+        assert_eq!(s.value(), None);
+        assert_eq!(s.update(c(101.0, 99.0)), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..80)
+            .map(|i| c(110.0 + (f64::from(i) * 0.25).sin() * 9.0, 90.0))
+            .collect();
+        let batch = SinglePrints::new(20, 24).unwrap().batch(&candles);
+        let mut b = SinglePrints::new(20, 24).unwrap();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,216 @@
+//! Sterling Ratio — mean return over the average drawdown of the equity curve.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Sterling Ratio over a trailing window of `period` returns.
+///
+/// ```text
+/// equity_t  = Π_{i<=t} (1 + return_i)          (compounded curve)
+/// peak_t    = max_{s<=t} equity_s
+/// dd_t      = (peak_t − equity_t) / peak_t      (fractional drawdown, >= 0)
+/// Sterling  = mean(returns) / mean(dd_t)
+/// ```
+///
+/// The Sterling Ratio rewards return per unit of *typical* pain: it divides the
+/// average per-period return by the **average drawdown** experienced along the
+/// compounded equity curve. Of the three drawdown-based ratios Wickra ships it is
+/// the gentlest on outliers — averaging the drawdowns means one deep crater does
+/// not dominate the way it does in the [`BurkeRatio`](crate::BurkeRatio) (which
+/// sums squared drawdowns) or the [`MartinRatio`](crate::MartinRatio) (which uses
+/// the root-mean-square percentage drawdown). A window that never draws down has
+/// zero average drawdown and the indicator reports `0.0`.
+///
+/// The first value lands after `period` returns; each `update` rebuilds the equity
+/// curve over the window (O(period)), which is O(1) in the length of the overall
+/// series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, SterlingRatio};
+///
+/// let mut indicator = SterlingRatio::new(12).unwrap();
+/// let mut last = None;
+/// for i in 0..24 {
+///     last = indicator.update((f64::from(i) * 0.5).sin() * 0.05);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct SterlingRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl SterlingRatio {
+    /// Construct a Sterling Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "sterling ratio needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        #[allow(clippy::cast_precision_loss)]
+        let length = self.window.len() as f64;
+        let mut sum_return = 0.0;
+        let mut sum_drawdown = 0.0;
+        let mut equity = 1.0;
+        let mut peak: f64 = 1.0;
+        for ret in &self.window {
+            sum_return += *ret;
+            equity *= 1.0 + *ret;
+            peak = peak.max(equity);
+            sum_drawdown += (peak - equity) / peak;
+        }
+        let avg_drawdown = sum_drawdown / length;
+        if avg_drawdown > 0.0 {
+            (sum_return / length) / avg_drawdown
+        } else {
+            0.0
+        }
+    }
+}
+
+impl Indicator for SterlingRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "SterlingRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            SterlingRatio::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let sr = SterlingRatio::new(12).unwrap();
+        assert_eq!(sr.period(), 12);
+        assert_eq!(sr.warmup_period(), 12);
+        assert_eq!(sr.name(), "SterlingRatio");
+        assert!(!sr.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.1, -0.1, 0.1]:
+        //   equity 1.1, 0.99, 1.089; peak stays 1.1.
+        //   dd = [0, 0.1, 0.01]; avg_dd = 0.11/3; mean_return = 0.1/3.
+        //   Sterling = (0.1/3) / (0.11/3) = 0.1/0.11.
+        let mut sr = SterlingRatio::new(3).unwrap();
+        let out = sr.batch(&[0.1, -0.1, 0.1]);
+        assert_relative_eq!(out[2].unwrap(), 0.1_f64 / 0.11, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn no_drawdown_is_zero() {
+        // Monotonically rising equity never draws down.
+        let mut sr = SterlingRatio::new(3).unwrap();
+        let last = sr
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn losing_window_is_negative() {
+        let mut sr = SterlingRatio::new(3).unwrap();
+        let last = sr
+            .batch(&[-0.05, -0.02, -0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert!(last < 0.0);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut sr = SterlingRatio::new(3).unwrap();
+        assert_eq!(sr.update(0.1), None);
+        assert_eq!(sr.update(f64::NAN), None);
+        assert_eq!(sr.update(-0.1), None);
+        assert!(sr.update(0.1).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut sr = SterlingRatio::new(3).unwrap();
+        sr.batch(&[0.1, -0.1, 0.1]);
+        assert!(sr.is_ready());
+        sr.reset();
+        assert!(!sr.is_ready());
+        assert_eq!(sr.update(0.1), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.05)
+            .collect();
+        let batch = SterlingRatio::new(12).unwrap().batch(&rets);
+        let mut streamer = SterlingRatio::new(12).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,224 @@
+//! Tail Ratio — the right tail (95th percentile) over the absolute left tail (5th percentile).
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Tail Ratio over a trailing window of `period` returns.
+///
+/// ```text
+/// TailRatio = P95(returns) / |P5(returns)|
+/// ```
+///
+/// The Tail Ratio contrasts the magnitude of the best outcomes against the worst:
+/// the 95th percentile of the return distribution divided by the absolute value of
+/// the 5th percentile. A value above `1.0` means the right tail (upside surprises)
+/// is fatter than the left tail (downside surprises); below `1.0` means crashes are
+/// larger than rallies. It is a distribution-shape statistic, distinct from the
+/// average-based [`SharpeRatio`](crate::SharpeRatio): two series with the same mean
+/// and variance can have very different tail ratios.
+///
+/// Percentiles are computed by linear interpolation over the sorted window
+/// (the same rule `NumPy` uses by default). A window whose 5th percentile is exactly
+/// zero has no measurable left tail and the indicator reports `0.0` rather than
+/// dividing by zero.
+///
+/// The first value lands after `period` returns; each `update` re-sorts the window
+/// (O(period log period)), which is O(1) in the length of the overall series.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, TailRatio};
+///
+/// let mut indicator = TailRatio::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update((f64::from(i) * 0.3).sin() * 0.02);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct TailRatio {
+    period: usize,
+    window: VecDeque<f64>,
+}
+
+impl TailRatio {
+    /// Construct a Tail Ratio over `period` returns.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` (percentiles need at least
+    /// two observations to interpolate).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "tail ratio needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            window: VecDeque::with_capacity(period),
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    fn compute(&self) -> f64 {
+        let mut sorted: Vec<f64> = self.window.iter().copied().collect();
+        sorted.sort_unstable_by(f64::total_cmp);
+        let upper = percentile(&sorted, 95.0);
+        let lower = percentile(&sorted, 5.0).abs();
+        if lower > 0.0 {
+            upper / lower
+        } else {
+            0.0
+        }
+    }
+}
+
+/// Linear-interpolation percentile of an ascending, non-empty slice.
+fn percentile(sorted: &[f64], pct: f64) -> f64 {
+    let last_index = sorted.len() - 1;
+    #[allow(clippy::cast_precision_loss)]
+    let rank = pct / 100.0 * last_index as f64;
+    let floor = rank.floor();
+    // `rank` lies in `[0, last_index]`, so its floor is a valid in-bounds index.
+    #[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
+    let lower = floor as usize;
+    if lower >= last_index {
+        return sorted[last_index];
+    }
+    let frac = rank - floor;
+    sorted[lower] + frac * (sorted[lower + 1] - sorted[lower])
+}
+
+impl Indicator for TailRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            self.window.pop_front();
+        }
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        Some(self.compute())
+    }
+
+    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 {
+        "TailRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            TailRatio::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(matches!(
+            TailRatio::new(0),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let tr = TailRatio::new(20).unwrap();
+        assert_eq!(tr.period(), 20);
+        assert_eq!(tr.warmup_period(), 20);
+        assert_eq!(tr.name(), "TailRatio");
+        assert!(!tr.is_ready());
+    }
+
+    #[test]
+    fn reference_value() {
+        // sorted window [-0.04, -0.02, 0.0, 0.02, 0.04], last_index = 4.
+        // P95: rank 3.8 -> 0.02 + 0.8*(0.04-0.02) = 0.036.
+        // P5:  rank 0.2 -> -0.04 + 0.2*(0.02)     = -0.036, abs 0.036.
+        // ratio = 0.036 / 0.036 = 1.0.
+        let mut tr = TailRatio::new(5).unwrap();
+        let out = tr.batch(&[-0.04, -0.02, 0.0, 0.02, 0.04]);
+        assert_relative_eq!(out[4].unwrap(), 1.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn fatter_right_tail_exceeds_one() {
+        let mut tr = TailRatio::new(5).unwrap();
+        let out = tr.batch(&[-0.01, 0.0, 0.01, 0.02, 0.10]);
+        assert!(out[4].unwrap() > 1.0);
+    }
+
+    #[test]
+    fn flat_window_is_zero() {
+        let mut tr = TailRatio::new(4).unwrap();
+        let last = tr.batch(&[0.0; 4]).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut tr = TailRatio::new(3).unwrap();
+        assert_eq!(tr.update(0.01), None);
+        assert_eq!(tr.update(f64::NAN), None);
+        assert_eq!(tr.update(0.02), None);
+        assert!(tr.update(0.03).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut tr = TailRatio::new(3).unwrap();
+        tr.batch(&[-0.01, 0.0, 0.02]);
+        assert!(tr.is_ready());
+        tr.reset();
+        assert!(!tr.is_ready());
+        assert_eq!(tr.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.02)
+            .collect();
+        let batch = TailRatio::new(15).unwrap().batch(&rets);
+        let mut streamer = TailRatio::new(15).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+
+    #[test]
+    fn percentile_at_top_returns_last() {
+        // When the rank floor reaches the final index (the 100th percentile), the
+        // helper returns the largest element without interpolating past the end.
+        assert_relative_eq!(percentile(&[1.0, 2.0, 3.0], 100.0), 3.0, epsilon = 1e-12);
+    }
+}

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

@@ -0,0 +1,224 @@
+#![allow(clippy::doc_markdown)]
+
+//! Tower Top / Tower Bottom — a tall bar, a pause, then a tall opposite bar.
+//!
+//! A Tower is a reversal where a strong directional bar is followed by a small
+//! "pause" bar and then a strong bar in the *opposite* direction, like two towers
+//! flanking a low wall. This is the compact three-bar form of the classic
+//! multi-bar Tower pattern.
+//!
+//! - **Tower Bottom** (`+1.0`): a tall **bearish** bar, a small-bodied bar, then a
+//!   tall **bullish** bar.
+//! - **Tower Top** (`-1.0`): a tall **bullish** bar, a small-bodied bar, then a
+//!   tall **bearish** bar.
+//! - Otherwise the output is `0.0`.
+//!
+//! "Tall" = body `>= 0.5 * range`; "small" = body `<= 0.3 * range`. The three-bar
+//! lookback means the first value lands on the third candle.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+fn body_fraction(candle: Candle) -> f64 {
+    let range = candle.high - candle.low;
+    if range > 0.0 {
+        (candle.close - candle.open).abs() / range
+    } else {
+        0.0
+    }
+}
+
+fn is_tall(candle: Candle) -> bool {
+    body_fraction(candle) >= 0.5
+}
+
+fn is_small(candle: Candle) -> bool {
+    body_fraction(candle) <= 0.3
+}
+
+/// Tower Top / Bottom — three-bar reversal detector.
+#[derive(Debug, Clone, Default)]
+pub struct TowerTopBottom {
+    c1: Option<Candle>,
+    c2: Option<Candle>,
+    last_value: Option<f64>,
+}
+
+impl TowerTopBottom {
+    /// Construct a new `TowerTopBottom`.
+    #[must_use]
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// Latest emitted signal if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last_value
+    }
+}
+
+impl Indicator for TowerTopBottom {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let (Some(first), Some(middle)) = (self.c1, self.c2) else {
+            self.c1 = self.c2;
+            self.c2 = Some(candle);
+            self.last_value = Some(0.0);
+            return Some(0.0);
+        };
+        let pause = is_small(middle);
+        let first_tall = is_tall(first);
+        let last_tall = is_tall(candle);
+        let v = if pause && first_tall && last_tall {
+            let first_up = first.close > first.open;
+            let last_up = candle.close > candle.open;
+            if !first_up && last_up {
+                1.0
+            } else if first_up && !last_up {
+                -1.0
+            } else {
+                0.0
+            }
+        } else {
+            0.0
+        };
+        self.c1 = self.c2;
+        self.c2 = Some(candle);
+        self.last_value = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.c1 = None;
+        self.c2 = None;
+        self.last_value = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last_value.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "TowerTopBottom"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    /// A tall candle from `open` to `close` (body fills most of the range).
+    fn tall(open: f64, close: f64) -> Candle {
+        Candle::new_unchecked(
+            open,
+            open.max(close) + 0.1,
+            open.min(close) - 0.1,
+            close,
+            0.0,
+            0,
+        )
+    }
+
+    /// A small-bodied candle (long shadows, tiny body).
+    fn small(mid: f64) -> Candle {
+        Candle::new_unchecked(mid, mid + 2.0, mid - 2.0, mid + 0.1, 0.0, 0)
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = TowerTopBottom::new();
+        assert_eq!(t.warmup_period(), 3);
+        assert_eq!(t.name(), "TowerTopBottom");
+        assert!(!t.is_ready());
+        assert_eq!(t.value(), None);
+    }
+
+    #[test]
+    fn first_two_bars_seed_without_signal() {
+        let mut t = TowerTopBottom::new();
+        assert_eq!(t.update(tall(100.0, 110.0)), Some(0.0));
+        assert_eq!(t.update(small(105.0)), Some(0.0));
+        assert!(t.update(tall(110.0, 100.0)).is_some());
+    }
+
+    #[test]
+    fn tower_top() {
+        // tall bullish, small pause, tall bearish -> top -> -1.
+        let mut t = TowerTopBottom::new();
+        t.update(tall(100.0, 110.0));
+        t.update(small(110.0));
+        assert_eq!(t.update(tall(110.0, 100.0)), Some(-1.0));
+    }
+
+    #[test]
+    fn tower_bottom() {
+        let mut t = TowerTopBottom::new();
+        t.update(tall(110.0, 100.0));
+        t.update(small(100.0));
+        assert_eq!(t.update(tall(100.0, 110.0)), Some(1.0));
+    }
+
+    #[test]
+    fn same_direction_is_zero() {
+        let mut t = TowerTopBottom::new();
+        t.update(tall(100.0, 110.0));
+        t.update(small(110.0));
+        // last bar also bullish -> not a tower -> 0.
+        assert_eq!(t.update(tall(110.0, 120.0)), Some(0.0));
+    }
+
+    #[test]
+    fn no_pause_is_zero() {
+        let mut t = TowerTopBottom::new();
+        t.update(tall(100.0, 110.0));
+        t.update(tall(110.0, 120.0)); // middle is tall, not a pause
+        assert_eq!(t.update(tall(120.0, 110.0)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = TowerTopBottom::new();
+        t.update(tall(100.0, 110.0));
+        t.update(small(110.0));
+        t.update(tall(110.0, 100.0));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.update(tall(100.0, 110.0)), Some(0.0));
+    }
+
+    #[test]
+    fn zero_range_bar_has_zero_body_fraction() {
+        // A flat bar (high == low) exercises the zero-range body-fraction branch;
+        // it counts as a small "pause" bar, so tall-flat-tall still reverses.
+        fn flat(mid: f64) -> Candle {
+            Candle::new_unchecked(mid, mid, mid, mid, 0.0, 0)
+        }
+        let mut t = TowerTopBottom::new();
+        t.update(tall(100.0, 110.0));
+        t.update(flat(110.0));
+        assert_eq!(t.update(tall(110.0, 100.0)), Some(-1.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..30)
+            .map(|i| match i % 3 {
+                0 => tall(100.0, 110.0),
+                1 => small(110.0),
+                _ => tall(110.0, 100.0),
+            })
+            .collect();
+        let batch = TowerTopBottom::new().batch(&candles);
+        let mut b = TowerTopBottom::new();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,217 @@
+//! Trade-Sign Autocorrelation — lag-1 persistence of the trade-aggressor side.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::microstructure::Trade;
+use crate::traits::Indicator;
+
+/// Trade-Sign Autocorrelation — the lag-1 autocorrelation of the **trade sign**
+/// (`+1` buy, `−1` sell), measuring how strongly signed order flow persists.
+///
+/// ```text
+/// s_t  = +1 if the trade is a buy, −1 if a sell
+/// ρ1   = mean over the window of ( s_t · s_{t−1} )      ∈ [−1, +1]
+/// ```
+///
+/// In real markets trade signs are strongly **positively** autocorrelated: a buy
+/// tends to be followed by another buy (and a sell by a sell), because large
+/// parent orders are split into many child trades and because of order-splitting
+/// and herding. A high reading therefore indicates persistent directional pressure
+/// — a footprint of informed or algorithmic execution — while a reading near zero
+/// signals balanced, uninformed flow and a negative reading signals alternating
+/// (bid-ask bounce) flow.
+///
+/// The output is the mean product of consecutive signs, bounded in `[−1, +1]`. The
+/// first value lands after `period` trades. Each `update` is O(`period`).
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, Side, Trade, TradeSignAutocorrelation};
+///
+/// let mut indicator = TradeSignAutocorrelation::new(20).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     let side = if i % 2 == 0 { Side::Buy } else { Side::Sell };
+///     last = indicator.update(Trade::new(100.0, 1.0, side, i).unwrap());
+/// }
+/// // Perfectly alternating signs -> autocorrelation -1.
+/// assert!((last.unwrap() + 1.0).abs() < 1e-9);
+/// ```
+#[derive(Debug, Clone)]
+pub struct TradeSignAutocorrelation {
+    period: usize,
+    signs: VecDeque<f64>,
+    last: Option<f64>,
+}
+
+impl TradeSignAutocorrelation {
+    /// Construct a trade-sign autocorrelation over `period` trades.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2` (a lag-1 product needs two
+    /// trades).
+    pub fn new(period: usize) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "trade-sign autocorrelation needs period >= 2",
+            });
+        }
+        Ok(Self {
+            period,
+            signs: VecDeque::with_capacity(period),
+            last: None,
+        })
+    }
+
+    /// Configured window of trades.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Current value if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last
+    }
+}
+
+impl Indicator for TradeSignAutocorrelation {
+    type Input = Trade;
+    type Output = f64;
+
+    fn update(&mut self, trade: Trade) -> Option<f64> {
+        if self.signs.len() == self.period {
+            self.signs.pop_front();
+        }
+        self.signs.push_back(trade.side.sign());
+        if self.signs.len() < self.period {
+            return None;
+        }
+        let mut product_sum = 0.0;
+        let mut prev: Option<f64> = None;
+        for &s in &self.signs {
+            if let Some(p) = prev {
+                product_sum += s * p;
+            }
+            prev = Some(s);
+        }
+        let rho = product_sum / (self.period as f64 - 1.0);
+        self.last = Some(rho);
+        Some(rho)
+    }
+
+    fn reset(&mut self) {
+        self.signs.clear();
+        self.last = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "TradeSignAutocorrelation"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::microstructure::Side;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn buy() -> Trade {
+        Trade::new_unchecked(100.0, 1.0, Side::Buy, 0)
+    }
+
+    fn sell() -> Trade {
+        Trade::new_unchecked(100.0, 1.0, Side::Sell, 0)
+    }
+
+    #[test]
+    fn rejects_period_below_two() {
+        assert!(matches!(
+            TradeSignAutocorrelation::new(1),
+            Err(Error::InvalidPeriod { .. })
+        ));
+        assert!(TradeSignAutocorrelation::new(2).is_ok());
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = TradeSignAutocorrelation::new(20).unwrap();
+        assert_eq!(t.period(), 20);
+        assert_eq!(t.warmup_period(), 20);
+        assert_eq!(t.name(), "TradeSignAutocorrelation");
+        assert!(!t.is_ready());
+        assert_eq!(t.value(), None);
+    }
+
+    #[test]
+    fn first_emission_at_warmup_period() {
+        let mut t = TradeSignAutocorrelation::new(4).unwrap();
+        let out = t.batch(&[buy(), buy(), buy(), buy(), buy()]);
+        for v in out.iter().take(3) {
+            assert!(v.is_none());
+        }
+        assert!(out[3].is_some());
+    }
+
+    #[test]
+    fn persistent_flow_is_one() {
+        let mut t = TradeSignAutocorrelation::new(10).unwrap();
+        let trades: Vec<Trade> = (0..20).map(|_| buy()).collect();
+        let last = t.batch(&trades).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, 1.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn alternating_flow_is_minus_one() {
+        let mut t = TradeSignAutocorrelation::new(10).unwrap();
+        let trades: Vec<Trade> = (0..20)
+            .map(|i| if i % 2 == 0 { buy() } else { sell() })
+            .collect();
+        let last = t.batch(&trades).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last, -1.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn output_in_range() {
+        let mut t = TradeSignAutocorrelation::new(16).unwrap();
+        let trades: Vec<Trade> = (0..200)
+            .map(|i| if (i * 7 % 13) < 6 { buy() } else { sell() })
+            .collect();
+        for v in t.batch(&trades).into_iter().flatten() {
+            assert!((-1.0..=1.0).contains(&v));
+        }
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = TradeSignAutocorrelation::new(4).unwrap();
+        t.batch(&[buy(), buy(), buy(), buy()]);
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.value(), None);
+        assert_eq!(t.update(buy()), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let trades: Vec<Trade> = (0..120)
+            .map(|i| if i % 3 == 0 { sell() } else { buy() })
+            .collect();
+        let batch = TradeSignAutocorrelation::new(16).unwrap().batch(&trades);
+        let mut b = TradeSignAutocorrelation::new(16).unwrap();
+        let streamed: Vec<_> = trades.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,189 @@
+#![allow(clippy::doc_markdown)]
+
+//! Tristar — a three-doji reversal pattern.
+//!
+//! A Tristar is three consecutive Doji candles where the middle one gaps away
+//! from its neighbours, forming a star. A bearish Tristar (top) has the middle
+//! doji sitting above the other two; a bullish Tristar (bottom) has it below.
+//!
+//! - **Bullish** (`+1.0`): three dojis, the middle doji's body centre below both
+//!   neighbours' body centres.
+//! - **Bearish** (`-1.0`): three dojis, the middle above both neighbours.
+//! - Otherwise the output is `0.0`.
+//!
+//! A doji is a candle whose body is `<= 0.1 * range`. The three-bar lookback means
+//! the first value lands on the third candle.
+
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Body-centre of a candle.
+fn body_mid(candle: Candle) -> f64 {
+    f64::midpoint(candle.open, candle.close)
+}
+
+/// Whether a candle is a doji (body small relative to range).
+fn is_doji(candle: Candle) -> bool {
+    let body = (candle.close - candle.open).abs();
+    let range = candle.high - candle.low;
+    range > 0.0 && body <= 0.1 * range
+}
+
+/// Tristar — three-doji star reversal detector.
+#[derive(Debug, Clone, Default)]
+pub struct Tristar {
+    c1: Option<Candle>,
+    c2: Option<Candle>,
+    last_value: Option<f64>,
+}
+
+impl Tristar {
+    /// Construct a new `Tristar`.
+    #[must_use]
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// Latest emitted signal if available.
+    pub const fn value(&self) -> Option<f64> {
+        self.last_value
+    }
+}
+
+impl Indicator for Tristar {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        let (Some(first), Some(middle)) = (self.c1, self.c2) else {
+            self.c1 = self.c2;
+            self.c2 = Some(candle);
+            self.last_value = Some(0.0);
+            return Some(0.0);
+        };
+        let v = if is_doji(first) && is_doji(middle) && is_doji(candle) {
+            let mid = body_mid(middle);
+            let n1 = body_mid(first);
+            let n3 = body_mid(candle);
+            if mid > n1 && mid > n3 {
+                -1.0
+            } else if mid < n1 && mid < n3 {
+                1.0
+            } else {
+                0.0
+            }
+        } else {
+            0.0
+        };
+        self.c1 = self.c2;
+        self.c2 = Some(candle);
+        self.last_value = Some(v);
+        Some(v)
+    }
+
+    fn reset(&mut self) {
+        self.c1 = None;
+        self.c2 = None;
+        self.last_value = None;
+    }
+
+    fn warmup_period(&self) -> usize {
+        3
+    }
+
+    fn is_ready(&self) -> bool {
+        self.last_value.is_some()
+    }
+
+    fn name(&self) -> &'static str {
+        "Tristar"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    /// A doji centred at `mid` (tiny body, symmetric shadows).
+    fn doji(mid: f64) -> Candle {
+        Candle::new_unchecked(mid, mid + 1.0, mid - 1.0, mid + 0.02, 0.0, 0)
+    }
+
+    /// A non-doji (big body).
+    fn solid(open: f64, close: f64) -> Candle {
+        Candle::new_unchecked(
+            open,
+            open.max(close) + 0.1,
+            open.min(close) - 0.1,
+            close,
+            0.0,
+            0,
+        )
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let t = Tristar::new();
+        assert_eq!(t.warmup_period(), 3);
+        assert_eq!(t.name(), "Tristar");
+        assert!(!t.is_ready());
+        assert_eq!(t.value(), None);
+    }
+
+    #[test]
+    fn first_two_bars_seed_without_signal() {
+        let mut t = Tristar::new();
+        assert_eq!(t.update(doji(100.0)), Some(0.0));
+        assert_eq!(t.update(doji(100.0)), Some(0.0));
+        assert!(t.update(doji(100.0)).is_some());
+    }
+
+    #[test]
+    fn bearish_tristar_top() {
+        // middle doji centred above the two neighbours -> top -> -1.
+        let mut t = Tristar::new();
+        t.update(doji(100.0));
+        t.update(doji(105.0)); // middle, highest
+        assert_eq!(t.update(doji(100.0)), Some(-1.0));
+    }
+
+    #[test]
+    fn bullish_tristar_bottom() {
+        let mut t = Tristar::new();
+        t.update(doji(100.0));
+        t.update(doji(95.0)); // middle, lowest
+        assert_eq!(t.update(doji(100.0)), Some(1.0));
+    }
+
+    #[test]
+    fn non_doji_is_zero() {
+        let mut t = Tristar::new();
+        t.update(doji(100.0));
+        t.update(solid(100.0, 110.0)); // not a doji
+        assert_eq!(t.update(doji(100.0)), Some(0.0));
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut t = Tristar::new();
+        t.update(doji(100.0));
+        t.update(doji(105.0));
+        t.update(doji(100.0));
+        assert!(t.is_ready());
+        t.reset();
+        assert!(!t.is_ready());
+        assert_eq!(t.update(doji(100.0)), Some(0.0));
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| doji(100.0 + (f64::from(i) * 0.4).sin() * 5.0))
+            .collect();
+        let batch = Tristar::new().batch(&candles);
+        let mut b = Tristar::new();
+        let streamed: Vec<_> = candles.iter().map(|x| b.update(*x)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

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

@@ -0,0 +1,226 @@
+//! Upside Potential Ratio (Sortino, van der Meer & Plantinga) — upside mean over downside deviation.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::traits::Indicator;
+
+/// Upside Potential Ratio over a trailing window of `period` returns, measured
+/// relative to a minimal acceptable return (`mar`).
+///
+/// ```text
+/// upside     = mean( max(r − mar, 0) )            over the window
+/// downside   = sqrt( mean( min(r − mar, 0)² ) )   over the window
+/// UPR        = upside / downside
+/// ```
+///
+/// Where the [`SharpeRatio`](crate::SharpeRatio) divides excess return by *total*
+/// volatility (penalising upside and downside symmetrically), the Upside Potential
+/// Ratio rewards only the average outperformance above the threshold while
+/// penalising solely the downside deviation below it. It is the purest expression
+/// of the Sortino philosophy: investors do not dislike upside variance, only
+/// shortfall risk.
+///
+/// `mar` (minimal acceptable return) is the per-period hurdle the caller supplies
+/// (e.g. `0.0` for break-even, or a target rate matching the return frequency). A
+/// window that never breaches the threshold has zero downside deviation; the
+/// indicator then reports `0.0` rather than dividing by zero.
+///
+/// Each `update` is O(1) — running sums maintain the upside total and the
+/// downside sum-of-squares as the window slides.
+///
+/// # Example
+///
+/// ```
+/// use wickra_core::{Indicator, UpsidePotentialRatio};
+///
+/// let mut indicator = UpsidePotentialRatio::new(20, 0.0).unwrap();
+/// let mut last = None;
+/// for i in 0..40 {
+///     last = indicator.update((f64::from(i) * 0.3).sin() * 0.02);
+/// }
+/// assert!(last.is_some());
+/// ```
+#[derive(Debug, Clone)]
+pub struct UpsidePotentialRatio {
+    period: usize,
+    mar: f64,
+    window: VecDeque<f64>,
+    sum_upside: f64,
+    sum_downside_sq: f64,
+}
+
+impl UpsidePotentialRatio {
+    /// Construct an Upside Potential Ratio over `period` returns with minimal
+    /// acceptable return `mar`.
+    ///
+    /// # Errors
+    ///
+    /// Returns [`Error::InvalidPeriod`] if `period < 2`, or
+    /// [`Error::InvalidParameter`] if `mar` is not finite.
+    pub fn new(period: usize, mar: f64) -> Result<Self> {
+        if period < 2 {
+            return Err(Error::InvalidPeriod {
+                message: "upside potential ratio needs period >= 2",
+            });
+        }
+        if !mar.is_finite() {
+            return Err(Error::InvalidParameter {
+                message: "mar must be finite",
+            });
+        }
+        Ok(Self {
+            period,
+            mar,
+            window: VecDeque::with_capacity(period),
+            sum_upside: 0.0,
+            sum_downside_sq: 0.0,
+        })
+    }
+
+    /// Configured window of returns.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+
+    /// Configured minimal acceptable return.
+    pub const fn mar(&self) -> f64 {
+        self.mar
+    }
+}
+
+impl Indicator for UpsidePotentialRatio {
+    type Input = f64;
+    type Output = f64;
+
+    fn update(&mut self, ret: f64) -> Option<f64> {
+        if !ret.is_finite() {
+            return None;
+        }
+        if self.window.len() == self.period {
+            let old = self.window.pop_front().expect("non-empty");
+            let excess = old - self.mar;
+            self.sum_upside -= excess.max(0.0);
+            self.sum_downside_sq -= excess.min(0.0).powi(2);
+        }
+        let excess = ret - self.mar;
+        self.sum_upside += excess.max(0.0);
+        self.sum_downside_sq += excess.min(0.0).powi(2);
+        self.window.push_back(ret);
+        if self.window.len() < self.period {
+            return None;
+        }
+        let n = self.period as f64;
+        let upside_mean = self.sum_upside / n;
+        let downside_dev = (self.sum_downside_sq / n).sqrt();
+        if downside_dev > 0.0 {
+            Some(upside_mean / downside_dev)
+        } else {
+            Some(0.0)
+        }
+    }
+
+    fn reset(&mut self) {
+        self.window.clear();
+        self.sum_upside = 0.0;
+        self.sum_downside_sq = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period
+    }
+
+    fn is_ready(&self) -> bool {
+        self.window.len() == self.period
+    }
+
+    fn name(&self) -> &'static str {
+        "UpsidePotentialRatio"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    #[test]
+    fn rejects_period_less_than_two() {
+        assert!(matches!(
+            UpsidePotentialRatio::new(1, 0.0),
+            Err(Error::InvalidPeriod { .. })
+        ));
+    }
+
+    #[test]
+    fn rejects_non_finite_mar() {
+        assert!(matches!(
+            UpsidePotentialRatio::new(10, f64::NAN),
+            Err(Error::InvalidParameter { .. })
+        ));
+    }
+
+    #[test]
+    fn accessors_and_metadata() {
+        let upr = UpsidePotentialRatio::new(20, 0.001).unwrap();
+        assert_eq!(upr.period(), 20);
+        assert_relative_eq!(upr.mar(), 0.001, epsilon = 1e-12);
+        assert_eq!(upr.warmup_period(), 20);
+        assert_eq!(upr.name(), "UpsidePotentialRatio");
+    }
+
+    #[test]
+    fn reference_value() {
+        // returns [0.02, -0.01, 0.03, -0.02], mar = 0.
+        // upside = (0.02 + 0 + 0.03 + 0)/4 = 0.0125.
+        // downside = sqrt((0 + 0.0001 + 0 + 0.0004)/4) = sqrt(0.000125).
+        // UPR = 0.0125 / sqrt(0.000125).
+        let mut upr = UpsidePotentialRatio::new(4, 0.0).unwrap();
+        let out = upr.batch(&[0.02, -0.01, 0.03, -0.02]);
+        let expected = 0.0125_f64 / (0.000_125_f64).sqrt();
+        assert_relative_eq!(out[3].unwrap(), expected, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn no_downside_is_zero() {
+        let mut upr = UpsidePotentialRatio::new(3, 0.0).unwrap();
+        let last = upr
+            .batch(&[0.01, 0.02, 0.03])
+            .into_iter()
+            .flatten()
+            .last()
+            .unwrap();
+        assert_relative_eq!(last, 0.0, epsilon = 1e-12);
+    }
+
+    #[test]
+    fn ignores_non_finite_input() {
+        let mut upr = UpsidePotentialRatio::new(3, 0.0).unwrap();
+        assert_eq!(upr.update(0.01), None);
+        assert_eq!(upr.update(f64::INFINITY), None);
+        assert_eq!(upr.update(-0.02), None);
+        assert!(upr.update(0.03).is_some());
+    }
+
+    #[test]
+    fn reset_clears_state() {
+        let mut upr = UpsidePotentialRatio::new(2, 0.0).unwrap();
+        upr.batch(&[0.02, -0.01]);
+        assert!(upr.is_ready());
+        upr.reset();
+        assert!(!upr.is_ready());
+        assert_eq!(upr.update(0.01), None);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let rets: Vec<f64> = (0..60)
+            .map(|i| (f64::from(i) * 0.25).sin() * 0.02)
+            .collect();
+        let batch = UpsidePotentialRatio::new(12, 0.0).unwrap().batch(&rets);
+        let mut streamer = UpsidePotentialRatio::new(12, 0.0).unwrap();
+        let streamed: Vec<_> = rets.iter().map(|r| streamer.update(*r)).collect();
+        assert_eq!(batch, streamed);
+    }
+}

crates/wickra-core/src/lib.rs

@@ -66,93 +66,99 @@ pub use indicators::{
     AverageDrawdown, AvgPrice, AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower,
     BandpassFilter, Bat, BeltHold, Beta, BetaNeutralSpread, BetterVolume, BipowerVariation,
     BodySizePct, BollingerBands, BollingerBandwidth, BollingerOutput, BomarBands, BomarBandsOutput,
-    BreadthThrust, Breakaway, BullishPercentIndex, Butterfly, CalendarSpread, CalmarRatio,
-    Camarilla, CamarillaPivotsOutput, CandleVolume, CandleVolumeOutput, Cci, CenterOfGravity,
-    CentralPivotRange, CentralPivotRangeOutput, Cfo, ChaikinMoneyFlow, ChaikinOscillator,
-    ChaikinVolatility, ChandeKrollStop, ChandeKrollStopOutput, ChandelierExit,
+    BreadthThrust, Breakaway, BullishPercentIndex, BurkeRatio, Butterfly, CalendarSpread,
+    CalmarRatio, Camarilla, CamarillaPivotsOutput, CandleVolume, CandleVolumeOutput, Cci,
+    CenterOfGravity, CentralPivotRange, CentralPivotRangeOutput, Cfo, ChaikinMoneyFlow,
+    ChaikinOscillator, ChaikinVolatility, ChandeKrollStop, ChandeKrollStopOutput, ChandelierExit,
     ChandelierExitOutput, ChoppinessIndex, ClassicPivots, ClassicPivotsOutput, CloseVsOpen,
     ClosingMarubozu, Cmo, CoefficientOfVariation, Cointegration, CointegrationOutput,
-    ConcealingBabySwallow, ConditionalValueAtRisk, ConnorsRsi, Coppock, CorrelationTrendIndicator,
-    Counterattack, Crab, CumulativeVolumeDelta, CumulativeVolumeIndex, CupAndHandle,
-    CyberneticCycle, Cypher, DayOfWeekProfile, DayOfWeekProfileOutput, Decycler,
-    DecyclerOscillator, Dema, DemandIndex, DemarkPivots, DemarkPivotsOutput, DepthSlope,
-    DerivativeOscillator, DetrendedStdDev, DisparityIndex, DistanceSsd, Doji, DojiStar, Donchian,
-    DonchianOutput, DonchianStop, DonchianStopOutput, DoubleBollinger, DoubleBollingerOutput,
-    DoubleTopBottom, DownsideGapThreeMethods, Dpo, DragonflyDoji, DrawdownDuration, Dx,
+    CommonSenseRatio, CompositeProfile, CompositeProfileOutput, ConcealingBabySwallow,
+    ConditionalValueAtRisk, ConnorsRsi, Coppock, CorrelationTrendIndicator, Counterattack, Crab,
+    CumulativeVolumeDelta, CumulativeVolumeIndex, CupAndHandle, CyberneticCycle, Cypher,
+    DayOfWeekProfile, DayOfWeekProfileOutput, Decycler, DecyclerOscillator, Dema, DemandIndex,
+    DemarkPivots, DemarkPivotsOutput, DepthSlope, DerivativeOscillator, DetrendedStdDev,
+    DisparityIndex, DistanceSsd, Doji, DojiStar, Donchian, DonchianOutput, DonchianStop,
+    DonchianStopOutput, DoubleBollinger, DoubleBollingerOutput, DoubleTopBottom,
+    DownsideGapThreeMethods, Dpo, DragonflyDoji, DrawdownDuration, DumplingTop, Dx,
     DynamicMomentumIndex, EaseOfMovement, EffectiveSpread, EhlersStochastic, Ehma, ElderImpulse,
     ElderRay, ElderRayOutput, ElderSafeZone, ElderSafeZoneOutput, Ema, EmpiricalModeDecomposition,
-    Engulfing, Equivolume, EquivolumeOutput, EvenBetterSinewave, EveningDojiStar, Evwma,
-    EwmaVolatility, Expectancy, FallingThreeMethods, Fama, FibArcs, FibArcsOutput, FibChannel,
-    FibChannelOutput, FibConfluence, FibConfluenceOutput, FibExtension, FibExtensionOutput, FibFan,
-    FibFanOutput, FibProjection, FibProjectionOutput, FibRetracement, FibRetracementOutput,
-    FibTimeZones, FibTimeZonesOutput, FibonacciPivots, FibonacciPivotsOutput, FisherRsi,
-    FisherTransform, FlagPennant, Footprint, FootprintOutput, ForceIndex, FractalChaosBands,
-    FractalChaosBandsOutput, Frama, FundingBasis, FundingRate, FundingRateMean, FundingRateZScore,
-    GainLossRatio, GapSideBySideWhite, Garch11, GarmanKlassVolatility, Gartley, GatorOscillator,
+    Engulfing, Equivolume, EquivolumeOutput, EstimatedLeverageRatio, EvenBetterSinewave,
+    EveningDojiStar, Evwma, EwmaVolatility, Expectancy, FallingThreeMethods, Fama, FibArcs,
+    FibArcsOutput, FibChannel, FibChannelOutput, FibConfluence, FibConfluenceOutput, FibExtension,
+    FibExtensionOutput, FibFan, FibFanOutput, FibProjection, FibProjectionOutput, FibRetracement,
+    FibRetracementOutput, FibTimeZones, FibTimeZonesOutput, FibonacciPivots, FibonacciPivotsOutput,
+    FisherRsi, FisherTransform, FlagPennant, Footprint, FootprintOutput, ForceIndex,
+    FractalChaosBands, FractalChaosBandsOutput, Frama, FryPanBottom, FundingBasis,
+    FundingImpliedApr, FundingRate, FundingRateMean, FundingRateZScore, GainLossRatio,
+    GainToPainRatio, GapSideBySideWhite, Garch11, GarmanKlassVolatility, Gartley, GatorOscillator,
     GatorOscillatorOutput, GeneralizedDema, GeometricMa, GoldenPocket, GoldenPocketOutput,
-    GrangerCausality, GravestoneDoji, Hammer, HangingMan, Harami, HeadAndShoulders, HeikinAshi,
-    HeikinAshiOscillator, HeikinAshiOutput, HiLoActivator, HighLowIndex, HighLowRange, HighWave,
-    HighpassFilter, Hikkake, HikkakeModified, HilbertDominantCycle, HistoricalVolatility, Hma,
-    HoltWinters, HomingPigeon, HtDcPhase, HtPhasor, HtPhasorOutput, HtTrendMode, HurstChannel,
-    HurstChannelOutput, HurstExponent, Ichimoku, IchimokuOutput, IdenticalThreeCrows, InNeck,
-    Inertia, InformationRatio, InitialBalance, InitialBalanceOutput, InstantaneousTrendline,
-    IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile,
-    IntradayVolatilityProfileOutput, InverseFisherTransform, InvertedHammer, JarqueBera, Jma,
-    JumpIndicator, KagiBars, KalmanHedgeRatio, KalmanHedgeRatioOutput, Kama, KaseDevStop,
-    KaseDevStopOutput, KasePermissionStochastic, KasePermissionStochasticOutput, KellyCriterion,
-    Keltner, KeltnerOutput, KendallTau, Kicking, KickingByLength, Kst, KstOutput, Kurtosis, Kvo,
+    GrangerCausality, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross,
+    HasbrouckInformationShare, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator,
+    HeikinAshiOutput, HiLoActivator, HighLowIndex, HighLowRange, HighLowVolumeNodes,
+    HighLowVolumeNodesOutput, HighWave, HighpassFilter, Hikkake, HikkakeModified,
+    HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HomingPigeon, HtDcPhase,
+    HtPhasor, HtPhasorOutput, HtTrendMode, HurstChannel, HurstChannelOutput, HurstExponent,
+    Ichimoku, IchimokuOutput, IdenticalThreeCrows, InNeck, Inertia, InformationRatio,
+    InitialBalance, InitialBalanceOutput, InstantaneousTrendline, IntradayIntensity,
+    IntradayMomentumIndex, IntradayVolatilityProfile, IntradayVolatilityProfileOutput,
+    InverseFisherTransform, InvertedHammer, JarqueBera, Jma, JumpIndicator, KRatio, KagiBars,
+    KalmanHedgeRatio, KalmanHedgeRatioOutput, Kama, KaseDevStop, KaseDevStopOutput,
+    KasePermissionStochastic, KasePermissionStochasticOutput, KellyCriterion, Keltner,
+    KeltnerOutput, KendallTau, Kicking, KickingByLength, Kst, KstOutput, Kurtosis, Kvo,
     KylesLambda, LadderBottom, LaguerreRsi, LeadLagCrossCorrelation, LeadLagCrossCorrelationOutput,
     LinRegAngle, LinRegChannel, LinRegChannelOutput, LinRegIntercept, LinRegSlope,
     LinearRegression, LiquidationFeatures, LiquidationFeaturesOutput, LogReturn, LongLeggedDoji,
-    LongLine, LongShortRatio, MaEnvelope, MaEnvelopeOutput, MacdExt, MacdFix, MacdHistogram,
-    MacdIndicator, MacdOutput, Mama, MamaOutput, MarketFacilitationIndex, Marubozu, MassIndex,
-    MatHold, MatchingLow, MaxDrawdown, McClellanOscillator, McClellanSummationIndex,
-    McGinleyDynamic, MedianAbsoluteDeviation, MedianChannel, MedianChannelOutput, MedianMa,
-    MedianPrice, Mfi, Microprice, MidPoint, MidPrice, MinusDi, MinusDm, ModifiedMaStop,
-    ModifiedMaStopOutput, Mom, MorningDojiStar, MorningEveningStar, MurreyMathLines,
-    MurreyMathLinesOutput, Natr, NewHighsNewLows, Nrtr, NrtrOutput, Nvi, OIPriceDivergence,
-    OIWeighted, Obv, OmegaRatio, OnNeck, OpenInterestDelta, OpeningMarubozu, OpeningRange,
-    OpeningRangeOutput, OrderBookImbalanceFull, OrderBookImbalanceTop1, OrderBookImbalanceTopN,
-    OrderFlowImbalance, OuHalfLife, OvernightGap, OvernightIntradayReturn,
-    OvernightIntradayReturnOutput, PainIndex, PairSpreadZScore, PairwiseBeta, ParkinsonVolatility,
-    PearsonCorrelation, PercentAboveMa, PercentB, PercentageTrailingStop, Pgo, PiercingDarkCloud,
+    LongLine, LongShortRatio, M2Measure, MaEnvelope, MaEnvelopeOutput, MacdExt, MacdFix,
+    MacdHistogram, MacdIndicator, MacdOutput, Mama, MamaOutput, MarketFacilitationIndex,
+    MartinRatio, Marubozu, MassIndex, MatHold, MatchingLow, MaxDrawdown, McClellanOscillator,
+    McClellanSummationIndex, McGinleyDynamic, MedianAbsoluteDeviation, MedianChannel,
+    MedianChannelOutput, MedianMa, MedianPrice, Mfi, Microprice, MidPoint, MidPrice, MinusDi,
+    MinusDm, ModifiedMaStop, ModifiedMaStopOutput, Mom, MorningDojiStar, MorningEveningStar,
+    MurreyMathLines, MurreyMathLinesOutput, NakedPoc, Natr, NewHighsNewLows, NewPriceLines, Nrtr,
+    NrtrOutput, Nvi, OIPriceDivergence, OIWeighted, Obv, OiToVolumeRatio, OmegaRatio, OnNeck,
+    OpenInterestDelta, OpenInterestMomentum, OpeningMarubozu, OpeningRange, OpeningRangeOutput,
+    OrderBookImbalanceFull, OrderBookImbalanceTop1, OrderBookImbalanceTopN, OrderFlowImbalance,
+    OuHalfLife, OvernightGap, OvernightIntradayReturn, OvernightIntradayReturnOutput, PainIndex,
+    PairSpreadZScore, PairwiseBeta, ParkinsonVolatility, PearsonCorrelation, PercentAboveMa,
+    PercentB, PercentageTrailingStop, PerpetualPremiumIndex, Pgo, PiercingDarkCloud, Pin,
     PivotReversal, PlusDi, PlusDm, Pmo, PointAndFigureBars, PolarizedFractalEfficiency, Ppo,
-    PpoHistogram, ProfitFactor, ProjectionBands, ProjectionBandsOutput, ProjectionOscillator, Psar,
-    Pvi, Qqe, QqeOutput, Qstick, QuartileBands, QuartileBandsOutput, QuotedSpread, RSquared,
-    RealizedSpread, RealizedVolatility, RecoveryFactor, RectangleRange, Reflex, RegimeLabel,
-    RelativeStrengthAB, RelativeStrengthOutput, RenkoBars, RenkoTrailingStop, RickshawMan,
-    RisingThreeMethods, Rmi, Roc, Rocp, Rocr, Rocr100, RogersSatchellVolatility, RollMeasure,
-    RollingCorrelation, RollingCovariance, RollingIqr, RollingMinMaxScaler, RollingPercentileRank,
-    RollingQuantile, RollingVwap, RoofingFilter, Rsi, Rsx, Rvi, RviVolatility, Rwi, RwiOutput,
-    SampleEntropy, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionHighLowOutput,
-    SessionRange, SessionRangeOutput, SessionVwap, ShannonEntropy, Shark, SharpeRatio,
-    ShootingStar, ShortLine, SignedVolume, SineWave, SineWeightedMa, Skewness, Sma, Smi, Smma,
-    SmoothedHeikinAshi, SmoothedHeikinAshiOutput, SortinoRatio, SpearmanCorrelation, SpinningTop,
-    SpreadAr1Coefficient, SpreadBollingerBands, SpreadBollingerBandsOutput, SpreadHurst,
-    StalledPattern, StandardError, StandardErrorBands, StandardErrorBandsOutput, StarcBands,
-    StarcBandsOutput, Stc, StdDev, StepTrailingStop, StickSandwich, StochRsi, Stochastic,
-    StochasticCci, StochasticOutput, SuperSmoother, SuperTrend, SuperTrendOutput,
-    TakerBuySellRatio, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown,
-    TdDWave, TdDeMarker, TdDifferential, TdLines, TdLinesOutput, TdMovingAverage,
-    TdMovingAverageOutput, TdOpen, TdPressure, TdPropulsion, TdRangeProjection,
-    TdRangeProjectionOutput, TdRei, TdRiskLevel, TdRiskLevelOutput, TdSequential,
-    TdSequentialOutput, TdSetup, TdTrap, Tema, TermStructureBasis, ThreeDrives, ThreeInside,
-    ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth,
-    Thrusting, TickIndex, Tii, TimeBasedStop, TimeOfDayReturnProfile, TimeOfDayReturnProfileOutput,
-    TpoProfile, TpoProfileOutput, TradeImbalance, TradeVolumeIndex, TrendLabel, TrendStrengthIndex,
-    Trendflex, TreynorRatio, Triangle, Trima, Trin, TripleTopBottom, Trix, TrueRange, Tsf,
+    PpoHistogram, ProfileShape, ProfitFactor, ProjectionBands, ProjectionBandsOutput,
+    ProjectionOscillator, Psar, Pvi, Qqe, QqeOutput, Qstick, QuartileBands, QuartileBandsOutput,
+    QuotedSpread, RSquared, RealizedSpread, RealizedVolatility, RecoveryFactor, RectangleRange,
+    Reflex, RegimeLabel, RelativeStrengthAB, RelativeStrengthOutput, RenkoBars, RenkoTrailingStop,
+    RickshawMan, RisingThreeMethods, Rmi, Roc, Rocp, Rocr, Rocr100, RogersSatchellVolatility,
+    RollMeasure, RollingCorrelation, RollingCovariance, RollingIqr, RollingMinMaxScaler,
+    RollingPercentileRank, RollingQuantile, RollingVwap, RoofingFilter, Rsi, Rsx, Rvi,
+    RviVolatility, Rwi, RwiOutput, SampleEntropy, SarExt, SeasonalZScore, SeparatingLines,
+    SessionHighLow, SessionHighLowOutput, SessionRange, SessionRangeOutput, SessionVwap,
+    ShannonEntropy, Shark, SharpeRatio, ShootingStar, ShortLine, SignedVolume, SineWave,
+    SineWeightedMa, SinglePrints, Skewness, Sma, Smi, Smma, SmoothedHeikinAshi,
+    SmoothedHeikinAshiOutput, SortinoRatio, SpearmanCorrelation, SpinningTop, SpreadAr1Coefficient,
+    SpreadBollingerBands, SpreadBollingerBandsOutput, SpreadHurst, StalledPattern, StandardError,
+    StandardErrorBands, StandardErrorBandsOutput, StarcBands, StarcBandsOutput, Stc, StdDev,
+    StepTrailingStop, SterlingRatio, StickSandwich, StochRsi, Stochastic, StochasticCci,
+    StochasticOutput, SuperSmoother, SuperTrend, SuperTrendOutput, TailRatio, TakerBuySellRatio,
+    Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker,
+    TdDifferential, TdLines, TdLinesOutput, TdMovingAverage, TdMovingAverageOutput, TdOpen,
+    TdPressure, TdPropulsion, TdRangeProjection, TdRangeProjectionOutput, TdRei, TdRiskLevel,
+    TdRiskLevelOutput, TdSequential, TdSequentialOutput, TdSetup, TdTrap, Tema, TermStructureBasis,
+    ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows,
+    ThreeStarsInSouth, Thrusting, TickIndex, Tii, TimeBasedStop, TimeOfDayReturnProfile,
+    TimeOfDayReturnProfileOutput, TowerTopBottom, TpoProfile, TpoProfileOutput, TradeImbalance,
+    TradeSignAutocorrelation, TradeVolumeIndex, TrendLabel, TrendStrengthIndex, Trendflex,
+    TreynorRatio, Triangle, Trima, Trin, TripleTopBottom, Tristar, Trix, TrueRange, Tsf,
     TsfOscillator, Tsi, Tsv, TtmSqueeze, TtmSqueezeOutput, TtmTrend, TurnOfMonth, Tweezer,
     TwiggsMoneyFlow, TwoCrows, TypicalPrice, UlcerIndex, UltimateOscillator, UniqueThreeRiver,
-    UniversalOscillator, UpDownVolumeRatio, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea,
-    ValueAreaOutput, ValueAtRisk, Variance, VarianceRatio, VerticalHorizontalFilter, Vidya,
-    VolatilityCone, VolatilityConeOutput, VolatilityOfVolatility, VolatilityRatio, VoltyStop,
-    VolumeByTimeProfile, VolumeByTimeProfileOutput, VolumeOscillator, VolumePriceTrend,
-    VolumeProfile, VolumeProfileOutput, VolumeRsi, VolumeWeightedMacd, VolumeWeightedMacdOutput,
-    VolumeWeightedSr, VolumeWeightedSrOutput, Vortex, VortexOutput, Vpin, Vwap, VwapStdDevBands,
-    VwapStdDevBandsOutput, Vwma, Vzo, Wad, WavePm, WaveTrend, WaveTrendOutput, Wedge,
-    WeightedClose, WickRatio, WilliamsFractals, WilliamsFractalsOutput, WilliamsR, WinRate, Wma,
-    WoodiePivots, WoodiePivotsOutput, YangZhangVolatility, YoyoExit, ZScore, ZeroLagMacd,
-    ZeroLagMacdOutput, ZigZag, ZigZagOutput, Zlema, FAMILIES, T3,
+    UniversalOscillator, UpDownVolumeRatio, UpsideGapThreeMethods, UpsideGapTwoCrows,
+    UpsidePotentialRatio, ValueArea, ValueAreaOutput, ValueAtRisk, Variance, VarianceRatio,
+    VerticalHorizontalFilter, Vidya, VolatilityCone, VolatilityConeOutput, VolatilityOfVolatility,
+    VolatilityRatio, VoltyStop, VolumeByTimeProfile, VolumeByTimeProfileOutput, VolumeOscillator,
+    VolumePriceTrend, VolumeProfile, VolumeProfileOutput, VolumeRsi, VolumeWeightedMacd,
+    VolumeWeightedMacdOutput, VolumeWeightedSr, VolumeWeightedSrOutput, Vortex, VortexOutput, Vpin,
+    Vwap, VwapStdDevBands, VwapStdDevBandsOutput, Vwma, Vzo, Wad, WavePm, WaveTrend,
+    WaveTrendOutput, Wedge, WeightedClose, WickRatio, WilliamsFractals, WilliamsFractalsOutput,
+    WilliamsR, WinRate, Wma, WoodiePivots, WoodiePivotsOutput, YangZhangVolatility, YoyoExit,
+    ZScore, ZeroLagMacd, ZeroLagMacdOutput, ZigZag, ZigZagOutput, Zlema, FAMILIES, T3,
 };
 // `FootprintLevel` is a row element of `FootprintOutput`, re-exported on its own
 // line so the indicator-count tooling (which scans the braced block above and

docs/README.md

@@ -8,7 +8,7 @@ That includes:
   [Python](https://docs.wickra.org/Quickstart-Python),
   [Node](https://docs.wickra.org/Quickstart-Node), and
   [WASM](https://docs.wickra.org/Quickstart-WASM).
-- A per-indicator deep dive for every one of the **479 indicators** across
+- A per-indicator deep dive for every one of the **507 indicators** across
   the sixteen families (Moving Averages, Momentum Oscillators, Trend &
   Directional, Price Oscillators, Volatility & Bands, Bands & Channels,
   Trailing Stops, Volume, Price Statistics, Ehlers / Cycle DSP, Pivots &

examples/node/package-lock.json

@@ -17,7 +17,7 @@
     },
     "../../bindings/node": {
       "name": "wickra",
-      "version": "0.6.8",
+      "version": "0.7.3",
       "license": "MIT OR Apache-2.0",
       "devDependencies": {
         "@napi-rs/cli": "^2.18.0"
@@ -26,12 +26,12 @@
         "node": ">= 18"
       },
       "optionalDependencies": {
-        "wickra-darwin-arm64": "0.6.8",
-        "wickra-darwin-x64": "0.6.8",
-        "wickra-linux-arm64-gnu": "0.6.8",
-        "wickra-linux-x64-gnu": "0.6.8",
-        "wickra-win32-arm64-msvc": "0.6.8",
-        "wickra-win32-x64-msvc": "0.6.8"
+        "wickra-darwin-arm64": "0.7.3",
+        "wickra-darwin-x64": "0.7.3",
+        "wickra-linux-arm64-gnu": "0.7.3",
+        "wickra-linux-x64-gnu": "0.7.3",
+        "wickra-win32-arm64-msvc": "0.7.3",
+        "wickra-win32-x64-msvc": "0.7.3"
       }
     },
     "node_modules/wickra": {

fuzz/fuzz_targets/indicator_update.rs

@@ -14,7 +14,7 @@
 //! `Ema(20)`. This target now covers every scalar indicator in the catalogue.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{AdaptiveCycle, AdaptiveLaguerreFilter, AdaptiveRsi, Alma, AnchoredRsi, Apo, Autocorrelation, AutocorrelationPeriodogram, AverageDrawdown, BandpassFilter, BatchExt, Beta, BipowerVariation, BollingerBands, BomarBands, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CorrelationTrendIndicator, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DerivativeOscillator, DetrendedStdDev, DisparityIndex, DoubleBollinger, Dpo, DrawdownDuration, DynamicMomentumIndex, EhlersStochastic, Ehma, ElderImpulse, Ema, EmpiricalModeDecomposition, EvenBetterSinewave, EwmaVolatility, Expectancy, Fama, FisherRsi, FisherTransform, Frama, GainLossRatio, Garch11, GeneralizedDema, GeometricMa, HighpassFilter, HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, JarqueBera, Jma, JumpIndicator, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, LogReturn, MaEnvelope, MaType, MacdExt, MacdFix, MacdHistogram, MacdIndicator, Mama, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MedianChannel, MedianMa, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, PolarizedFractalEfficiency, Ppo, PpoHistogram, ProfitFactor, Qqe, QuartileBands, RSquared, RealizedVolatility, RecoveryFactor, Reflex, RegimeLabel, RenkoTrailingStop, Rmi, Roc, Rocp, Rocr, Rocr100, RollingIqr, RollingMinMaxScaler, RollingPercentileRank, RollingQuantile, RoofingFilter, Rsi, Rsx, RviVolatility, SampleEntropy, ShannonEntropy, SharpeRatio, SineWave, SineWeightedMa, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, StochRsi, SuperSmoother, Tema, Tii, TrendLabel, TrendStrengthIndex, Trendflex, Trima, Trix, Tsf, TsfOscillator, Tsi, UlcerIndex, UniversalOscillator, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, VolatilityOfVolatility, WavePm, WinRate, Wma, ZScore, ZeroLagMacd, Zlema, T3};
+use wickra_core::{AdaptiveCycle, AdaptiveLaguerreFilter, AdaptiveRsi, Alma, AnchoredRsi, Apo, Autocorrelation, AutocorrelationPeriodogram, AverageDrawdown, BandpassFilter, BatchExt, Beta, BipowerVariation, BollingerBands, BomarBands, BurkeRatio, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, CommonSenseRatio, ConditionalValueAtRisk, ConnorsRsi, Coppock, CorrelationTrendIndicator, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DerivativeOscillator, DetrendedStdDev, DisparityIndex, DoubleBollinger, Dpo, DrawdownDuration, DynamicMomentumIndex, EhlersStochastic, Ehma, ElderImpulse, Ema, EmpiricalModeDecomposition, EvenBetterSinewave, EwmaVolatility, Expectancy, Fama, FisherRsi, FisherTransform, Frama, GainLossRatio, GainToPainRatio, Garch11, GeneralizedDema, GeometricMa, HighpassFilter, HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, JarqueBera, Jma, JumpIndicator, KRatio, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, LogReturn, M2Measure, MaEnvelope, MaType, MacdExt, MacdFix, MacdHistogram, MacdIndicator, Mama, MartinRatio, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MedianChannel, MedianMa, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, PolarizedFractalEfficiency, Ppo, PpoHistogram, ProfitFactor, Qqe, QuartileBands, RSquared, RealizedVolatility, RecoveryFactor, Reflex, RegimeLabel, RenkoTrailingStop, Rmi, Roc, Rocp, Rocr, Rocr100, RollingIqr, RollingMinMaxScaler, RollingPercentileRank, RollingQuantile, RoofingFilter, Rsi, Rsx, RviVolatility, SampleEntropy, ShannonEntropy, SharpeRatio, SineWave, SineWeightedMa, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, SterlingRatio, StochRsi, SuperSmoother, TailRatio, Tema, Tii, TrendLabel, TrendStrengthIndex, Trendflex, Trima, Trix, Tsf, TsfOscillator, Tsi, UlcerIndex, UniversalOscillator, UpsidePotentialRatio, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, VolatilityOfVolatility, WavePm, WinRate, Wma, ZScore, ZeroLagMacd, Zlema, T3};
 
 /// Drive a single streaming + batch run through one scalar indicator. Marked
 /// `#[inline(never)]` so a panic backtrace pin-points the specific indicator.
@@ -211,6 +211,15 @@ fuzz_target!(|data: Vec<f64>| {
     drive(|| KellyCriterion::new(20).unwrap(), &data);
     drive(|| WinRate::new(20).unwrap(), &data);
     drive(|| Expectancy::new(20).unwrap(), &data);
+    drive(|| SterlingRatio::new(12).unwrap(), &data);
+    drive(|| BurkeRatio::new(12).unwrap(), &data);
+    drive(|| MartinRatio::new(14).unwrap(), &data);
+    drive(|| TailRatio::new(20).unwrap(), &data);
+    drive(|| KRatio::new(30).unwrap(), &data);
+    drive(|| CommonSenseRatio::new(20).unwrap(), &data);
+    drive(|| GainToPainRatio::new(12).unwrap(), &data);
+    drive(|| UpsidePotentialRatio::new(20, 0.0).unwrap(), &data);
+    drive(|| M2Measure::new(20, 0.0, 0.02).unwrap(), &data);
 
     // RecoveryFactor and DrawdownDuration produce non-`f64` outputs / have
     // no `period` knob, so they cannot use the `drive` helper directly.

fuzz/fuzz_targets/indicator_update_candle.rs

@@ -22,7 +22,7 @@
 //! WeightedClose.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{AbandonedBaby, Abcd, AccelerationBands, AcceleratorOscillator, AdOscillator, AdaptiveCci, Adl, AdvanceBlock, Adx, Adxr, Alligator, AnchoredVwap, AndrewsPitchfork, Aroon, AroonOscillator, Atr, AtrBands, AtrRatchet, AtrTrailingStop, AutoFib, AverageDailyRange, AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower, Bat, BatchExt, BeltHold, BetterVolume, BodySizePct, Breakaway, Butterfly, Camarilla, Candle, CandleVolume, Cci, CentralPivotRange, ChaikinMoneyFlow, ChaikinOscillator, ChaikinVolatility, ChandeKrollStop, ChandelierExit, ChoppinessIndex, ClassicPivots, CloseVsOpen, ClosingMarubozu, ConcealingBabySwallow, Counterattack, Crab, CupAndHandle, Cypher, DayOfWeekProfile, DemandIndex, DemarkPivots, Doji, DojiStar, Donchian, DonchianStop, DoubleTopBottom, DownsideGapThreeMethods, DragonflyDoji, Dx, EaseOfMovement, ElderRay, ElderSafeZone, Engulfing, Equivolume, EveningDojiStar, Evwma, FallingThreeMethods, FibArcs, FibChannel, FibConfluence, FibExtension, FibFan, FibProjection, FibRetracement, FibTimeZones, FibonacciPivots, FlagPennant, ForceIndex, FractalChaosBands, GapSideBySideWhite, GarmanKlassVolatility, Gartley, GatorOscillator, GoldenPocket, GravestoneDoji, Hammer, HangingMan, Harami, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator, HiLoActivator, HighLowRange, HighWave, Hikkake, HikkakeModified, HomingPigeon, HurstChannel, Ichimoku, IdenticalThreeCrows, InNeck, Indicator, Inertia, InitialBalance, IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile, InvertedHammer, KaseDevStop, KasePermissionStochastic, Keltner, Kicking, KickingByLength, Kvo, LadderBottom, LongLeggedDoji, LongLine, MarketFacilitationIndex, Marubozu, MassIndex, MatHold, MatchingLow, AvgPrice, MedianPrice, Mfi, MidPrice, MinusDi, MinusDm, ModifiedMaStop, MorningDojiStar, MorningEveningStar, MurreyMathLines, Natr, Nrtr, Nvi, Obv, OnNeck, OpeningMarubozu, OpeningRange, OvernightGap, OvernightIntradayReturn, ParkinsonVolatility, Pgo, PiercingDarkCloud, PivotReversal, PlusDi, PlusDm, ProjectionBands, ProjectionOscillator, Psar, Pvi, Qstick, RectangleRange, RickshawMan, RisingThreeMethods, RogersSatchellVolatility, RollingVwap, Rvi, Rwi, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionRange, SessionVwap, Shark, ShootingStar, ShortLine, Smi, SmoothedHeikinAshi, SpinningTop, StalledPattern, StarcBands, StickSandwich, Stochastic, StochasticCci, SuperTrend, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker, TdDifferential, TdLines, TdMovingAverage, TdOpen, TdPressure, TdPropulsion, TdRangeProjection, TdRei, TdRiskLevel, TdSequential, TdSetup, TdTrap, ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth, Thrusting, TimeBasedStop, TimeOfDayReturnProfile, TpoProfile, TradeVolumeIndex, Triangle, TripleTopBottom, TrueRange, Tsv, TtmSqueeze, TtmTrend, TurnOfMonth, Tweezer, TwiggsMoneyFlow, TwoCrows, TypicalPrice, UltimateOscillator, UniqueThreeRiver, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea, VolatilityCone, VolatilityRatio, VoltyStop, VolumeByTimeProfile, VolumeOscillator, VolumePriceTrend, VolumeProfile, VolumeRsi, VolumeWeightedMacd, VolumeWeightedSr, Vortex, Vwap, VwapStdDevBands, Vwma, Vzo, WaveTrend, Wedge, WeightedClose, WickRatio, Wad, WilliamsFractals, WilliamsR, WoodiePivots, YangZhangVolatility, YoyoExit, ZigZag};
+use wickra_core::{AbandonedBaby, Abcd, AccelerationBands, AcceleratorOscillator, AdOscillator, AdaptiveCci, Adl, AdvanceBlock, Adx, Adxr, Alligator, AnchoredVwap, AndrewsPitchfork, Aroon, AroonOscillator, Atr, AtrBands, AtrRatchet, AtrTrailingStop, AutoFib, AverageDailyRange, AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower, Bat, BatchExt, BeltHold, BetterVolume, BodySizePct, Breakaway, Butterfly, Camarilla, Candle, CandleVolume, Cci, CentralPivotRange, ChaikinMoneyFlow, ChaikinOscillator, ChaikinVolatility, ChandeKrollStop, ChandelierExit, ChoppinessIndex, ClassicPivots, CloseVsOpen, ClosingMarubozu, CompositeProfile, ConcealingBabySwallow, Counterattack, Crab, CupAndHandle, Cypher, DayOfWeekProfile, DemandIndex, DemarkPivots, Doji, DojiStar, Donchian, DonchianStop, DoubleTopBottom, DownsideGapThreeMethods, DragonflyDoji, DumplingTop, Dx, EaseOfMovement, ElderRay, ElderSafeZone, Engulfing, Equivolume, EveningDojiStar, Evwma, FallingThreeMethods, FibArcs, FibChannel, FibConfluence, FibExtension, FibFan, FibProjection, FibRetracement, FibTimeZones, FibonacciPivots, FlagPennant, ForceIndex, FractalChaosBands, FryPanBottom, GapSideBySideWhite, GarmanKlassVolatility, Gartley, GatorOscillator, GoldenPocket, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator, HiLoActivator, HighLowRange, HighLowVolumeNodes, HighWave, Hikkake, HikkakeModified, HomingPigeon, HurstChannel, Ichimoku, IdenticalThreeCrows, InNeck, Indicator, Inertia, InitialBalance, IntradayIntensity, IntradayMomentumIndex, IntradayVolatilityProfile, InvertedHammer, KaseDevStop, KasePermissionStochastic, Keltner, Kicking, KickingByLength, Kvo, LadderBottom, LongLeggedDoji, LongLine, MarketFacilitationIndex, Marubozu, MassIndex, MatHold, MatchingLow, AvgPrice, MedianPrice, Mfi, MidPrice, MinusDi, MinusDm, ModifiedMaStop, MorningDojiStar, MorningEveningStar, MurreyMathLines, NakedPoc, Natr, NewPriceLines, Nrtr, Nvi, Obv, OnNeck, OpeningMarubozu, OpeningRange, OvernightGap, OvernightIntradayReturn, ParkinsonVolatility, Pgo, PiercingDarkCloud, PivotReversal, PlusDi, PlusDm, ProfileShape, ProjectionBands, ProjectionOscillator, Psar, Pvi, Qstick, RectangleRange, RickshawMan, RisingThreeMethods, RogersSatchellVolatility, RollingVwap, Rvi, Rwi, SarExt, SeasonalZScore, SeparatingLines, SessionHighLow, SessionRange, SessionVwap, Shark, ShootingStar, ShortLine, SinglePrints, Smi, SmoothedHeikinAshi, SpinningTop, StalledPattern, StarcBands, StickSandwich, Stochastic, StochasticCci, SuperTrend, Takuri, TasukiGap, TdCamouflage, TdClop, TdClopwin, TdCombo, TdCountdown, TdDWave, TdDeMarker, TdDifferential, TdLines, TdMovingAverage, TdOpen, TdPressure, TdPropulsion, TdRangeProjection, TdRei, TdRiskLevel, TdSequential, TdSetup, TdTrap, ThreeDrives, ThreeInside, ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth, Thrusting, TimeBasedStop, TimeOfDayReturnProfile, TowerTopBottom, TpoProfile, TradeVolumeIndex, Triangle, TripleTopBottom, Tristar, TrueRange, Tsv, TtmSqueeze, TtmTrend, TurnOfMonth, Tweezer, TwiggsMoneyFlow, TwoCrows, TypicalPrice, UltimateOscillator, UniqueThreeRiver, UpsideGapThreeMethods, UpsideGapTwoCrows, ValueArea, VolatilityCone, VolatilityRatio, VoltyStop, VolumeByTimeProfile, VolumeOscillator, VolumePriceTrend, VolumeProfile, VolumeRsi, VolumeWeightedMacd, VolumeWeightedSr, Vortex, Vwap, VwapStdDevBands, Vwma, Vzo, WaveTrend, Wedge, WeightedClose, WickRatio, Wad, WilliamsFractals, WilliamsR, WoodiePivots, YangZhangVolatility, YoyoExit, ZigZag};
 
 /// Convert a flat `f64` stream into a `Vec<Candle>` by chunking it into
 /// `[open, high, low, close, volume]` groups. Tuples that fail OHLCV
@@ -188,6 +188,11 @@ fuzz_target!(|data: Vec<f64>| {
     }
 
     // --- Market Profile (multi-output) ---
+    drive(|| CompositeProfile::new(20, 24, 0.7).unwrap(), &candles);
+    drive(|| HighLowVolumeNodes::new(20, 24).unwrap(), &candles);
+    drive(|| NakedPoc::new(20, 24).unwrap(), &candles);
+    drive(|| SinglePrints::new(20, 24).unwrap(), &candles);
+    drive(|| ProfileShape::new(20, 24).unwrap(), &candles);
     drive(|| ValueArea::new(20, 50, 0.70).unwrap(), &candles);
     drive(|| VolumeProfile::new(20, 50).unwrap(), &candles);
     drive(|| TpoProfile::new(20, 50).unwrap(), &candles);
@@ -315,6 +320,12 @@ fuzz_target!(|data: Vec<f64>| {
     }
 
     // --- Candlestick Patterns (family 14) ---
+    drive(TowerTopBottom::new, &candles);
+    drive(HaramiCross::new, &candles);
+    drive(Tristar::new, &candles);
+    drive(|| FryPanBottom::new(9).unwrap(), &candles);
+    drive(|| DumplingTop::new(9).unwrap(), &candles);
+    drive(|| NewPriceLines::new(5).unwrap(), &candles);
     drive(TdTrap::new, &candles);
     drive(TdPropulsion::new, &candles);
     drive(TdClopwin::new, &candles);

fuzz/fuzz_targets/indicator_update_derivatives.rs

@@ -10,11 +10,7 @@
 //! never panic, streaming or batched.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{
-    BatchExt, CalendarSpread, DerivativesTick, FundingBasis, FundingRate, FundingRateMean,
-    FundingRateZScore, Indicator, LiquidationFeatures, LongShortRatio, OIPriceDivergence,
-    OIWeighted, OpenInterestDelta, TakerBuySellRatio, TermStructureBasis,
-};
+use wickra_core::{BatchExt, CalendarSpread, DerivativesTick, EstimatedLeverageRatio, FundingBasis, FundingImpliedApr, FundingRate, FundingRateMean, FundingRateZScore, Indicator, LiquidationFeatures, LongShortRatio, OIPriceDivergence, OIWeighted, OiToVolumeRatio, OpenInterestDelta, OpenInterestMomentum, PerpetualPremiumIndex, TakerBuySellRatio, TermStructureBasis};
 
 #[inline(never)]
 fn drive<I>(make: impl Fn() -> I, ticks: &[DerivativesTick])
@@ -53,6 +49,11 @@ fuzz_target!(|data: &[u8]| {
     drive(TakerBuySellRatio::new, &ticks);
     drive(TermStructureBasis::new, &ticks);
     drive(CalendarSpread::new, &ticks);
+    drive(EstimatedLeverageRatio::new, &ticks);
+    drive(OiToVolumeRatio::new, &ticks);
+    drive(PerpetualPremiumIndex::new, &ticks);
+    drive(|| FundingImpliedApr::new(1095.0).unwrap(), &ticks);
+    drive(|| OpenInterestMomentum::new(14).unwrap(), &ticks);
 
     // LiquidationFeatures emits a struct, not an f64, so drive it directly.
     let mut liq = LiquidationFeatures::new();

fuzz/fuzz_targets/indicator_update_pair.rs

@@ -8,7 +8,7 @@
 //! panic.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{Alpha, BatchExt, BetaNeutralSpread, Cointegration, DistanceSsd, GrangerCausality, Indicator, InformationRatio, KalmanHedgeRatio, KendallTau, LeadLagCrossCorrelation, OuHalfLife, PairSpreadZScore, PairwiseBeta, RelativeStrengthAB, RollingCorrelation, RollingCovariance, SpreadAr1Coefficient, SpreadBollingerBands, SpreadHurst, TreynorRatio, VarianceRatio};
+use wickra_core::{Alpha, BatchExt, BetaNeutralSpread, Cointegration, DistanceSsd, GrangerCausality, HasbrouckInformationShare, Indicator, InformationRatio, KalmanHedgeRatio, KendallTau, LeadLagCrossCorrelation, OuHalfLife, PairSpreadZScore, PairwiseBeta, RelativeStrengthAB, RollingCorrelation, RollingCovariance, SpreadAr1Coefficient, SpreadBollingerBands, SpreadHurst, TreynorRatio, VarianceRatio};
 
 #[inline(never)]
 fn drive<I>(make: impl Fn() -> I, data: &[(f64, f64)])
@@ -48,6 +48,7 @@ fuzz_target!(|data: &[u8]| {
     drive(|| GrangerCausality::new(60, 1).unwrap(), &pairs);
     drive(|| SpreadAr1Coefficient::new(40).unwrap(), &pairs);
     drive(|| KendallTau::new(20).unwrap(), &pairs);
+    drive(|| HasbrouckInformationShare::new(2).unwrap(), &pairs);
 
     // Struct-output pair indicator: drive update + batch directly (the generic
     // `drive` above only covers `Output = f64`).

fuzz/fuzz_targets/indicator_update_trade.rs

@@ -10,7 +10,7 @@
 //! would reject — the indicators must never panic, streaming or batched.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{AmihudIlliquidity, BatchExt, CumulativeVolumeDelta, Footprint, Indicator, RollMeasure, Side, SignedVolume, Trade, TradeImbalance, Vpin};
+use wickra_core::{AmihudIlliquidity, BatchExt, CumulativeVolumeDelta, Footprint, Indicator, Pin, RollMeasure, Side, SignedVolume, Trade, TradeImbalance, TradeSignAutocorrelation, Vpin};
 
 #[inline(never)]
 fn drive<I>(make: impl Fn() -> I, trades: &[Trade])
@@ -43,6 +43,8 @@ fuzz_target!(|data: &[u8]| {
     drive(|| Vpin::new(8.0, 5).unwrap(), &trades);
     drive(|| AmihudIlliquidity::new(20).unwrap(), &trades);
     drive(|| RollMeasure::new(20).unwrap(), &trades);
+    drive(|| TradeSignAutocorrelation::new(20).unwrap(), &trades);
+    drive(|| Pin::new(20).unwrap(), &trades);
 
     // Footprint emits a variable-length `FootprintOutput` rather than an `f64`,
     // so it is driven directly rather than through the scalar-output helper.