release: bump 0.7.0 -> 0.7.1 (#215 )

Version bump 0.7.0 -> 0.7.1 for the B16 Derivatives batch (493 indicators).
feat(derivatives): leverage, OI/volume, perpetual premium, funding APR, OI momentum (B16) (#214 )
2026-06-08 03:35:31 +02:00 · 2026-06-08 03:33:59 +02:00 · 2026-06-08 03:10:16 +02:00 · 2026-06-08 03:07:50 +02:00
36 changed files with 3184 additions and 102 deletions
@@ -7,6 +7,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+## [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`).
@@ -1377,7 +1389,9 @@ 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/v0.6.9...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.7.1...HEAD
+[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
@@ -1944,7 +1944,7 @@ dependencies = [

 [[package]]
 name = "wickra"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "approx",
 "criterion",
@@ -1955,7 +1955,7 @@ dependencies = [

 [[package]]
 name = "wickra-bench"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "criterion",
 "kand",
@@ -1967,7 +1967,7 @@ dependencies = [

 [[package]]
 name = "wickra-core"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "approx",
 "proptest",
@@ -1977,7 +1977,7 @@ dependencies = [

 [[package]]
 name = "wickra-data"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "approx",
 "csv",
@@ -1994,7 +1994,7 @@ dependencies = [

 [[package]]
 name = "wickra-examples"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "serde_json",
 "tokio",
@@ -2004,7 +2004,7 @@ dependencies = [

 [[package]]
 name = "wickra-node"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "napi",
 "napi-build",
@@ -2014,7 +2014,7 @@ dependencies = [

 [[package]]
 name = "wickra-python"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "numpy",
 "pyo3",
@@ -2023,7 +2023,7 @@ dependencies = [

 [[package]]
 name = "wickra-wasm"
-version = "0.6.9"
+version = "0.7.1"
 dependencies = [
 "console_error_panic_hook",
 "js-sys",
@@ -13,7 +13,7 @@ members = [
 exclude = ["fuzz"]

 [workspace.package]
-version = "0.6.9"
+version = "0.7.1"
 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 = "0.6.9" }
+wickra-core = { path = "crates/wickra-core", version = "0.7.1" }

 thiserror = "2"
 rayon = "1.10"
@@ -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=485" 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=493" 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 485 indicators; start at the
+  every one of the 493 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.** 485 indicators across 24
+- **The biggest streaming-native catalogue, period.** 493 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
@@ -77,7 +77,7 @@ 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 485 indicators**.
+  for all 493 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
@@ -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** | **485** | **yes** |
+| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Python · Node · WASM · Rust** | **493** | **yes** |
 | kand             | clean       | yes         | Python · WASM · Rust        |       ~60  | yes    |
 | ta-rs            | clean       | yes         | Rust only                   |       ~30  | stale  |
 | yata             | clean       | partial     | Rust only                   |       ~35  | yes    |
@@ -128,7 +128,7 @@ Full tables (Rust + Python, streaming + batch) and how to reproduce them live in

 ## Indicators

-485 streaming-first indicators across twenty-four families. Every one passes the
+493 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).
@@ -153,8 +153,8 @@ warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
 | 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 |
+| 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 |
 | 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) |
@@ -237,7 +237,7 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 485 indicators
+│   ├── wickra-core/         core engine + all 493 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)
@@ -667,6 +667,7 @@ 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)) {
@@ -1270,7 +1271,7 @@ 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);
@@ -1279,6 +1280,16 @@ 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', () => {
@@ -1432,6 +1443,56 @@ 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.
@@ -1449,6 +1449,19 @@ 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)`
@@ -4333,6 +4346,24 @@ 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)
@@ -4513,6 +4544,51 @@ 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()
@@ -1,6 +1,6 @@
 {
  "name": "wickra-darwin-arm64",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.darwin-arm64.node",
  "files": [
@@ -1,6 +1,6 @@
 {
  "name": "wickra-darwin-x64",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.darwin-x64.node",
  "files": [
@@ -1,6 +1,6 @@
 {
  "name": "wickra-linux-arm64-gnu",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.linux-arm64-gnu.node",
  "files": [
@@ -1,6 +1,6 @@
 {
  "name": "wickra-linux-x64-gnu",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.linux-x64-gnu.node",
  "files": [
@@ -1,6 +1,6 @@
 {
  "name": "wickra-win32-arm64-msvc",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.win32-arm64-msvc.node",
  "files": [
@@ -1,6 +1,6 @@
 {
  "name": "wickra-win32-x64-msvc",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
  "main": "wickra.win32-x64-msvc.node",
  "files": [
@@ -1,12 +1,12 @@
 {
  "name": "wickra",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "wickra",
-      "version": "0.6.9",
+      "version": "0.7.1",
      "license": "MIT OR Apache-2.0",
      "devDependencies": {
        "@napi-rs/cli": "^2.18.0"
@@ -15,12 +15,12 @@
        "node": ">= 18"
      },
      "optionalDependencies": {
-        "wickra-darwin-arm64": "0.6.9",
-        "wickra-darwin-x64": "0.6.9",
-        "wickra-linux-arm64-gnu": "0.6.9",
-        "wickra-linux-x64-gnu": "0.6.9",
-        "wickra-win32-arm64-msvc": "0.6.9",
-        "wickra-win32-x64-msvc": "0.6.9"
+        "wickra-darwin-arm64": "0.7.1",
+        "wickra-darwin-x64": "0.7.1",
+        "wickra-linux-arm64-gnu": "0.7.1",
+        "wickra-linux-x64-gnu": "0.7.1",
+        "wickra-win32-arm64-msvc": "0.7.1",
+        "wickra-win32-x64-msvc": "0.7.1"
      }
    },
    "node_modules/@napi-rs/cli": {
@@ -41,8 +41,8 @@
      }
    },
    "node_modules/wickra-darwin-arm64": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.7.1.tgz",
      "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
      "cpu": [
        "arm64"
@@ -57,8 +57,8 @@
      }
    },
    "node_modules/wickra-darwin-x64": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.7.1.tgz",
      "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
      "cpu": [
        "x64"
@@ -73,8 +73,8 @@
      }
    },
    "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.7.1.tgz",
      "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
      "cpu": [
        "arm64"
@@ -89,8 +89,8 @@
      }
    },
    "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.7.1.tgz",
      "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
      "cpu": [
        "x64"
@@ -105,8 +105,8 @@
      }
    },
    "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.7.1.tgz",
      "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
      "cpu": [
        "arm64"
@@ -121,8 +121,8 @@
      }
    },
    "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.6.9",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.6.9.tgz",
+      "version": "0.7.1",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.7.1.tgz",
      "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
      "cpu": [
        "x64"
@@ -1,6 +1,6 @@
 {
  "name": "wickra",
-  "version": "0.6.9",
+  "version": "0.7.1",
  "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": "0.6.9",
-    "wickra-linux-arm64-gnu": "0.6.9",
-    "wickra-darwin-x64": "0.6.9",
-    "wickra-darwin-arm64": "0.6.9",
-    "wickra-win32-x64-msvc": "0.6.9",
-    "wickra-win32-arm64-msvc": "0.6.9"
+    "wickra-linux-x64-gnu": "0.7.1",
+    "wickra-linux-arm64-gnu": "0.7.1",
+    "wickra-darwin-x64": "0.7.1",
+    "wickra-darwin-arm64": "0.7.1",
+    "wickra-win32-x64-msvc": "0.7.1",
+    "wickra-win32-arm64-msvc": "0.7.1"
  },
  "scripts": {
    "build": "napi build --platform --release",
@@ -884,6 +884,11 @@ node_pair_indicator!(
    "BetaNeutralSpread",
    wc::BetaNeutralSpread
 );
+node_pair_indicator!(
+    HasbrouckInformationShareNode,
+    "HasbrouckInformationShare",
+    wc::HasbrouckInformationShare
+);

 // ============================== PairSpreadZScore ==============================

@@ -13739,6 +13744,108 @@ impl TradeImbalanceNode {
    }
 }

+// Trade-sign autocorrelation carries a `period` parameter, so it is hand-written.
+#[napi(js_name = "TradeSignAutocorrelation")]
+pub struct TradeSignAutocorrelationNode {
+    inner: wc::TradeSignAutocorrelation,
+}
+
+#[napi]
+impl TradeSignAutocorrelationNode {
+    #[napi(constructor)]
+    pub fn new(period: u32) -> napi::Result<Self> {
+        Ok(Self {
+            inner: wc::TradeSignAutocorrelation::new(period as usize).map_err(map_err)?,
+        })
+    }
+    #[napi]
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    #[napi]
+    pub fn batch(
+        &mut self,
+        price: Vec<f64>,
+        size: Vec<f64>,
+        is_buy: Vec<bool>,
+    ) -> napi::Result<Vec<f64>> {
+        if price.len() != size.len() || size.len() != is_buy.len() {
+            return Err(NapiError::from_reason(
+                "price, size, is_buy must be equal length".to_string(),
+            ));
+        }
+        let mut out = Vec::with_capacity(price.len());
+        for i in 0..price.len() {
+            let trade = build_trade(price[i], size[i], is_buy[i])?;
+            out.push(self.inner.update(trade).unwrap_or(f64::NAN));
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
+// PIN carries a `window` parameter, so it is hand-written.
+#[napi(js_name = "Pin")]
+pub struct PinNode {
+    inner: wc::Pin,
+}
+
+#[napi]
+impl PinNode {
+    #[napi(constructor)]
+    pub fn new(window: u32) -> napi::Result<Self> {
+        Ok(Self {
+            inner: wc::Pin::new(window as usize).map_err(map_err)?,
+        })
+    }
+    #[napi]
+    pub fn update(&mut self, price: f64, size: f64, is_buy: bool) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    #[napi]
+    pub fn batch(
+        &mut self,
+        price: Vec<f64>,
+        size: Vec<f64>,
+        is_buy: Vec<bool>,
+    ) -> napi::Result<Vec<f64>> {
+        if price.len() != size.len() || size.len() != is_buy.len() {
+            return Err(NapiError::from_reason(
+                "price, size, is_buy must be equal length".to_string(),
+            ));
+        }
+        let mut out = Vec::with_capacity(price.len());
+        for i in 0..price.len() {
+            let trade = build_trade(price[i], size[i], is_buy[i])?;
+            out.push(self.inner.update(trade).unwrap_or(f64::NAN));
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
 // Order Flow Imbalance: order-book input with a `period` parameter.
 #[napi(js_name = "OrderFlowImbalance")]
 pub struct OrderFlowImbalanceNode {
@@ -14343,6 +14450,50 @@ fn deriv_taker(taker_buy_volume: f64, taker_sell_volume: f64) -> napi::Result<wc
    .map_err(map_err)
 }

+fn deriv_oi_long_short(
+    open_interest: f64,
+    long_size: f64,
+    short_size: f64,
+) -> napi::Result<wc::DerivativesTick> {
+    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,
+) -> napi::Result<wc::DerivativesTick> {
+    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,
@@ -15058,6 +15209,288 @@ impl CalendarSpreadNode {
    }
 }

+// Estimated leverage ratio: open interest over aggregate long+short size.
+#[napi(js_name = "EstimatedLeverageRatio")]
+pub struct EstimatedLeverageRatioNode {
+    inner: wc::EstimatedLeverageRatio,
+}
+
+impl Default for EstimatedLeverageRatioNode {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[napi]
+impl EstimatedLeverageRatioNode {
+    #[napi(constructor)]
+    pub fn new() -> Self {
+        Self {
+            inner: wc::EstimatedLeverageRatio::new(),
+        }
+    }
+    #[napi]
+    pub fn update(
+        &mut self,
+        open_interest: f64,
+        long_size: f64,
+        short_size: f64,
+    ) -> napi::Result<Option<f64>> {
+        Ok(self
+            .inner
+            .update(deriv_oi_long_short(open_interest, long_size, short_size)?))
+    }
+    #[napi]
+    pub fn batch(
+        &mut self,
+        open_interest: Vec<f64>,
+        long_size: Vec<f64>,
+        short_size: Vec<f64>,
+    ) -> napi::Result<Vec<f64>> {
+        if open_interest.len() != long_size.len() || long_size.len() != short_size.len() {
+            return Err(NapiError::from_reason(
+                "open_interest, long_size, short_size must be equal length".to_string(),
+            ));
+        }
+        let mut out = Vec::with_capacity(open_interest.len());
+        for i in 0..open_interest.len() {
+            out.push(
+                self.inner
+                    .update(deriv_oi_long_short(
+                        open_interest[i],
+                        long_size[i],
+                        short_size[i],
+                    )?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
+// OI-to-volume ratio: open interest over taker buy+sell volume.
+#[napi(js_name = "OiToVolumeRatio")]
+pub struct OiToVolumeRatioNode {
+    inner: wc::OiToVolumeRatio,
+}
+
+impl Default for OiToVolumeRatioNode {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[napi]
+impl OiToVolumeRatioNode {
+    #[napi(constructor)]
+    pub fn new() -> Self {
+        Self {
+            inner: wc::OiToVolumeRatio::new(),
+        }
+    }
+    #[napi]
+    pub fn update(
+        &mut self,
+        open_interest: f64,
+        taker_buy_volume: f64,
+        taker_sell_volume: f64,
+    ) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(deriv_oi_taker(
+            open_interest,
+            taker_buy_volume,
+            taker_sell_volume,
+        )?))
+    }
+    #[napi]
+    pub fn batch(
+        &mut self,
+        open_interest: Vec<f64>,
+        taker_buy_volume: Vec<f64>,
+        taker_sell_volume: Vec<f64>,
+    ) -> napi::Result<Vec<f64>> {
+        if open_interest.len() != taker_buy_volume.len()
+            || taker_buy_volume.len() != taker_sell_volume.len()
+        {
+            return Err(NapiError::from_reason(
+                "open_interest, taker_buy_volume, taker_sell_volume must be equal length"
+                    .to_string(),
+            ));
+        }
+        let mut out = Vec::with_capacity(open_interest.len());
+        for i in 0..open_interest.len() {
+            out.push(
+                self.inner
+                    .update(deriv_oi_taker(
+                        open_interest[i],
+                        taker_buy_volume[i],
+                        taker_sell_volume[i],
+                    )?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
+// Perpetual premium index: relative premium of mark over index price.
+#[napi(js_name = "PerpetualPremiumIndex")]
+pub struct PerpetualPremiumIndexNode {
+    inner: wc::PerpetualPremiumIndex,
+}
+
+impl Default for PerpetualPremiumIndexNode {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+#[napi]
+impl PerpetualPremiumIndexNode {
+    #[napi(constructor)]
+    pub fn new() -> Self {
+        Self {
+            inner: wc::PerpetualPremiumIndex::new(),
+        }
+    }
+    #[napi]
+    pub fn update(&mut self, mark_price: f64, index_price: f64) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
+    }
+    #[napi]
+    pub fn batch(&mut self, mark_price: Vec<f64>, index_price: Vec<f64>) -> napi::Result<Vec<f64>> {
+        if mark_price.len() != index_price.len() {
+            return Err(NapiError::from_reason(
+                "mark_price and index_price must be equal length".to_string(),
+            ));
+        }
+        let mut out = Vec::with_capacity(mark_price.len());
+        for i in 0..mark_price.len() {
+            out.push(
+                self.inner
+                    .update(deriv_basis(mark_price[i], index_price[i])?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
+// Funding-implied APR: per-interval funding annualised.
+#[napi(js_name = "FundingImpliedApr")]
+pub struct FundingImpliedAprNode {
+    inner: wc::FundingImpliedApr,
+}
+
+#[napi]
+impl FundingImpliedAprNode {
+    #[napi(constructor)]
+    pub fn new(intervals_per_year: f64) -> napi::Result<Self> {
+        Ok(Self {
+            inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
+        })
+    }
+    #[napi]
+    pub fn update(&mut self, funding_rate: f64) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(deriv_funding(funding_rate)?))
+    }
+    #[napi]
+    pub fn batch(&mut self, funding_rate: Vec<f64>) -> napi::Result<Vec<f64>> {
+        let mut out = Vec::with_capacity(funding_rate.len());
+        for r in funding_rate {
+            out.push(self.inner.update(deriv_funding(r)?).unwrap_or(f64::NAN));
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
+// Open-interest momentum: rate-of-change of open interest over a window.
+#[napi(js_name = "OpenInterestMomentum")]
+pub struct OpenInterestMomentumNode {
+    inner: wc::OpenInterestMomentum,
+}
+
+#[napi]
+impl OpenInterestMomentumNode {
+    #[napi(constructor)]
+    pub fn new(period: u32) -> napi::Result<Self> {
+        Ok(Self {
+            inner: wc::OpenInterestMomentum::new(period as usize).map_err(map_err)?,
+        })
+    }
+    #[napi]
+    pub fn update(&mut self, open_interest: f64) -> napi::Result<Option<f64>> {
+        Ok(self.inner.update(deriv_oi(open_interest)?))
+    }
+    #[napi]
+    pub fn batch(&mut self, open_interest: Vec<f64>) -> napi::Result<Vec<f64>> {
+        let mut out = Vec::with_capacity(open_interest.len());
+        for oi in open_interest {
+            out.push(self.inner.update(deriv_oi(oi)?).unwrap_or(f64::NAN));
+        }
+        Ok(out)
+    }
+    #[napi]
+    pub fn reset(&mut self) {
+        self.inner.reset();
+    }
+    #[napi(js_name = "isReady")]
+    pub fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    #[napi(js_name = "warmupPeriod")]
+    pub fn warmup_period(&self) -> u32 {
+        self.inner.warmup_period() as u32
+    }
+}
+
 // ---------- Market Breadth (CrossSection input) ----------
 //
 // A breadth tick is the per-symbol state of the whole universe, passed as four
@@ -4,7 +4,7 @@ build-backend = "maturin"

 [project]
 name = "wickra"
-version = "0.6.9"
+version = "0.7.1"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
 license = "MIT OR Apache-2.0"
@@ -464,6 +464,8 @@ from ._wickra import (
    QuotedSpread,
    DepthSlope,
    # Microstructure: trade flow
+    Pin,
+    TradeSignAutocorrelation,
    RollMeasure,
    AmihudIlliquidity,
    Vpin,
@@ -471,12 +473,18 @@ from ._wickra import (
    CumulativeVolumeDelta,
    TradeImbalance,
    # Microstructure: price impact
+    HasbrouckInformationShare,
    EffectiveSpread,
    RealizedSpread,
    KylesLambda,
    # Microstructure: footprint
    Footprint,
    # Derivatives
+    OpenInterestMomentum,
+    FundingImpliedApr,
+    PerpetualPremiumIndex,
+    OiToVolumeRatio,
+    EstimatedLeverageRatio,
    FundingRate,
    FundingRateMean,
    FundingRateZScore,
@@ -979,6 +987,8 @@ __all__ = [
    "QuotedSpread",
    "DepthSlope",
    # Microstructure: trade flow
+    "Pin",
+    "TradeSignAutocorrelation",
    "RollMeasure",
    "AmihudIlliquidity",
    "Vpin",
@@ -986,12 +996,18 @@ __all__ = [
    "CumulativeVolumeDelta",
    "TradeImbalance",
    # Microstructure: price impact
+    "HasbrouckInformationShare",
    "EffectiveSpread",
    "RealizedSpread",
    "KylesLambda",
    # Microstructure: footprint
    "Footprint",
    # Derivatives
+    "OpenInterestMomentum",
+    "FundingImpliedApr",
+    "PerpetualPremiumIndex",
+    "OiToVolumeRatio",
+    "EstimatedLeverageRatio",
    "FundingRate",
    "FundingRateMean",
    "FundingRateZScore",
@@ -16980,6 +16980,70 @@ impl PyRollingCorrelation {
    }
 }

+// ========================= HasbrouckInformationShare =========================
+
+#[pyclass(
+    name = "HasbrouckInformationShare",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyHasbrouckInformationShare {
+    inner: wc::HasbrouckInformationShare,
+}
+
+#[pymethods]
+impl PyHasbrouckInformationShare {
+    #[new]
+    #[pyo3(signature = (period=20))]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::HasbrouckInformationShare::new(period).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, a: f64, b: f64) -> Option<f64> {
+        self.inner.update((a, b))
+    }
+    /// Batch over two equally-sized numpy arrays: `a` and `b`.
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        a: PyReadonlyArray1<'py, f64>,
+        b: PyReadonlyArray1<'py, f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        let xs = a
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        let ys = b
+            .as_slice()
+            .map_err(|_| PyValueError::new_err(NON_CONTIGUOUS))?;
+        if xs.len() != ys.len() {
+            return Err(PyValueError::new_err("a and b must be equal length"));
+        }
+        let mut out = Vec::with_capacity(xs.len());
+        for i in 0..xs.len() {
+            out.push(self.inner.update((xs[i], ys[i])).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    #[getter]
+    fn period(&self) -> usize {
+        self.inner.period()
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        format!("HasbrouckInformationShare(period={})", self.inner.period())
+    }
+}
+
 // ============================== RollingCovariance ==============================

 #[pyclass(
@@ -18652,6 +18716,112 @@ impl PyTradeImbalance {
    }
 }

+// Trade-sign autocorrelation carries a `period` parameter, so it is hand-written.
+#[pyclass(
+    name = "TradeSignAutocorrelation",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyTradeSignAutocorrelation {
+    inner: wc::TradeSignAutocorrelation,
+}
+
+#[pymethods]
+impl PyTradeSignAutocorrelation {
+    #[new]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::TradeSignAutocorrelation::new(period).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, price: f64, size: f64, is_buy: bool) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        price: Vec<f64>,
+        size: Vec<f64>,
+        is_buy: Vec<bool>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        if price.len() != size.len() || size.len() != is_buy.len() {
+            return Err(PyValueError::new_err(
+                "price, size, is_buy must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(price.len());
+        for i in 0..price.len() {
+            let trade = build_trade(price[i], size[i], is_buy[i])?;
+            out.push(self.inner.update(trade).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        format!("TradeSignAutocorrelation(period={})", self.inner.period())
+    }
+}
+
+// PIN carries a `window` parameter, so it is hand-written.
+#[pyclass(name = "Pin", module = "wickra._wickra", skip_from_py_object)]
+#[derive(Clone)]
+struct PyPin {
+    inner: wc::Pin,
+}
+
+#[pymethods]
+impl PyPin {
+    #[new]
+    fn new(window: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::Pin::new(window).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, price: f64, size: f64, is_buy: bool) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(build_trade(price, size, is_buy)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        price: Vec<f64>,
+        size: Vec<f64>,
+        is_buy: Vec<bool>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        if price.len() != size.len() || size.len() != is_buy.len() {
+            return Err(PyValueError::new_err(
+                "price, size, is_buy must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(price.len());
+        for i in 0..price.len() {
+            let trade = build_trade(price[i], size[i], is_buy[i])?;
+            out.push(self.inner.update(trade).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        format!("Pin(window={})", self.inner.window())
+    }
+}
+
 // Order Flow Imbalance carries a `period` parameter and an order-book input,
 // so it is hand-written.
 #[pyclass(
@@ -19250,6 +19420,50 @@ fn deriv_taker(taker_buy_volume: f64, taker_sell_volume: f64) -> PyResult<wc::De
    .map_err(map_err)
 }

+fn deriv_oi_long_short(
+    open_interest: f64,
+    long_size: f64,
+    short_size: f64,
+) -> PyResult<wc::DerivativesTick> {
+    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,
+) -> PyResult<wc::DerivativesTick> {
+    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,
@@ -19970,6 +20184,302 @@ impl PyCalendarSpread {
    }
 }

+// Estimated leverage ratio: open interest over aggregate long+short size.
+#[pyclass(
+    name = "EstimatedLeverageRatio",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyEstimatedLeverageRatio {
+    inner: wc::EstimatedLeverageRatio,
+}
+
+#[pymethods]
+impl PyEstimatedLeverageRatio {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::EstimatedLeverageRatio::new(),
+        }
+    }
+    fn update(
+        &mut self,
+        open_interest: f64,
+        long_size: f64,
+        short_size: f64,
+    ) -> PyResult<Option<f64>> {
+        Ok(self
+            .inner
+            .update(deriv_oi_long_short(open_interest, long_size, short_size)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open_interest: Vec<f64>,
+        long_size: Vec<f64>,
+        short_size: Vec<f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        if open_interest.len() != long_size.len() || long_size.len() != short_size.len() {
+            return Err(PyValueError::new_err(
+                "open_interest, long_size, short_size must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(open_interest.len());
+        for i in 0..open_interest.len() {
+            out.push(
+                self.inner
+                    .update(deriv_oi_long_short(
+                        open_interest[i],
+                        long_size[i],
+                        short_size[i],
+                    )?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        "EstimatedLeverageRatio()".to_string()
+    }
+}
+
+// OI-to-volume ratio: open interest over taker buy+sell volume.
+#[pyclass(
+    name = "OiToVolumeRatio",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyOiToVolumeRatio {
+    inner: wc::OiToVolumeRatio,
+}
+
+#[pymethods]
+impl PyOiToVolumeRatio {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::OiToVolumeRatio::new(),
+        }
+    }
+    fn update(
+        &mut self,
+        open_interest: f64,
+        taker_buy_volume: f64,
+        taker_sell_volume: f64,
+    ) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(deriv_oi_taker(
+            open_interest,
+            taker_buy_volume,
+            taker_sell_volume,
+        )?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open_interest: Vec<f64>,
+        taker_buy_volume: Vec<f64>,
+        taker_sell_volume: Vec<f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        if open_interest.len() != taker_buy_volume.len()
+            || taker_buy_volume.len() != taker_sell_volume.len()
+        {
+            return Err(PyValueError::new_err(
+                "open_interest, taker_buy_volume, taker_sell_volume must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(open_interest.len());
+        for i in 0..open_interest.len() {
+            out.push(
+                self.inner
+                    .update(deriv_oi_taker(
+                        open_interest[i],
+                        taker_buy_volume[i],
+                        taker_sell_volume[i],
+                    )?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        "OiToVolumeRatio()".to_string()
+    }
+}
+
+// Perpetual premium index: relative premium of mark over index price.
+#[pyclass(
+    name = "PerpetualPremiumIndex",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyPerpetualPremiumIndex {
+    inner: wc::PerpetualPremiumIndex,
+}
+
+#[pymethods]
+impl PyPerpetualPremiumIndex {
+    #[new]
+    fn new() -> Self {
+        Self {
+            inner: wc::PerpetualPremiumIndex::new(),
+        }
+    }
+    fn update(&mut self, mark_price: f64, index_price: f64) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(deriv_basis(mark_price, index_price)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        mark_price: Vec<f64>,
+        index_price: Vec<f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        if mark_price.len() != index_price.len() {
+            return Err(PyValueError::new_err(
+                "mark_price and index_price must be equal length",
+            ));
+        }
+        let mut out = Vec::with_capacity(mark_price.len());
+        for i in 0..mark_price.len() {
+            out.push(
+                self.inner
+                    .update(deriv_basis(mark_price[i], index_price[i])?)
+                    .unwrap_or(f64::NAN),
+            );
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        "PerpetualPremiumIndex()".to_string()
+    }
+}
+
+// Funding-implied APR: per-interval funding annualised.
+#[pyclass(
+    name = "FundingImpliedApr",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyFundingImpliedApr {
+    inner: wc::FundingImpliedApr,
+}
+
+#[pymethods]
+impl PyFundingImpliedApr {
+    #[new]
+    fn new(intervals_per_year: f64) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::FundingImpliedApr::new(intervals_per_year).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, funding_rate: f64) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(deriv_funding(funding_rate)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        funding_rate: Vec<f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        let mut out = Vec::with_capacity(funding_rate.len());
+        for r in funding_rate {
+            out.push(self.inner.update(deriv_funding(r)?).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        format!(
+            "FundingImpliedApr(intervals_per_year={})",
+            self.inner.intervals_per_year()
+        )
+    }
+}
+
+// Open-interest momentum: rate-of-change of open interest over a window.
+#[pyclass(
+    name = "OpenInterestMomentum",
+    module = "wickra._wickra",
+    skip_from_py_object
+)]
+#[derive(Clone)]
+struct PyOpenInterestMomentum {
+    inner: wc::OpenInterestMomentum,
+}
+
+#[pymethods]
+impl PyOpenInterestMomentum {
+    #[new]
+    fn new(period: usize) -> PyResult<Self> {
+        Ok(Self {
+            inner: wc::OpenInterestMomentum::new(period).map_err(map_err)?,
+        })
+    }
+    fn update(&mut self, open_interest: f64) -> PyResult<Option<f64>> {
+        Ok(self.inner.update(deriv_oi(open_interest)?))
+    }
+    fn batch<'py>(
+        &mut self,
+        py: Python<'py>,
+        open_interest: Vec<f64>,
+    ) -> PyResult<Bound<'py, PyArray1<f64>>> {
+        let mut out = Vec::with_capacity(open_interest.len());
+        for oi in open_interest {
+            out.push(self.inner.update(deriv_oi(oi)?).unwrap_or(f64::NAN));
+        }
+        Ok(out.into_pyarray(py))
+    }
+    fn reset(&mut self) {
+        self.inner.reset();
+    }
+    fn is_ready(&self) -> bool {
+        self.inner.is_ready()
+    }
+    fn warmup_period(&self) -> usize {
+        self.inner.warmup_period()
+    }
+    fn __repr__(&self) -> String {
+        format!("OpenInterestMomentum(period={})", self.inner.period())
+    }
+}
+
 // ============================== Market Breadth ==============================
 //
 // Market-breadth indicators consume a `CrossSection`: one tick carrying the
@@ -24743,6 +25253,7 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<PyCointegration>()?;
    m.add_class::<PyRelativeStrengthAB>()?;
    m.add_class::<PyRollingCorrelation>()?;
+    m.add_class::<PyHasbrouckInformationShare>()?;
    m.add_class::<PyRollingCovariance>()?;
    m.add_class::<PyOuHalfLife>()?;
    m.add_class::<PySpreadHurst>()?;
@@ -24833,6 +25344,8 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<PySignedVolume>()?;
    m.add_class::<PyCumulativeVolumeDelta>()?;
    m.add_class::<PyTradeImbalance>()?;
+    m.add_class::<PyTradeSignAutocorrelation>()?;
+    m.add_class::<PyPin>()?;
    m.add_class::<PyOrderFlowImbalance>()?;
    m.add_class::<PyVpin>()?;
    m.add_class::<PyAmihudIlliquidity>()?;
@@ -24856,6 +25369,11 @@ fn _wickra(_py: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<PyLiquidationFeatures>()?;
    m.add_class::<PyTermStructureBasis>()?;
    m.add_class::<PyCalendarSpread>()?;
+    m.add_class::<PyEstimatedLeverageRatio>()?;
+    m.add_class::<PyOiToVolumeRatio>()?;
+    m.add_class::<PyPerpetualPremiumIndex>()?;
+    m.add_class::<PyFundingImpliedApr>()?;
+    m.add_class::<PyOpenInterestMomentum>()?;
    m.add_class::<PyAdvanceDecline>()?;
    m.add_class::<PyAdvanceDeclineRatio>()?;
    m.add_class::<PyAdVolumeLine>()?;
@@ -217,6 +217,7 @@ 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)),
@@ -3323,6 +3324,13 @@ def test_tower_top_bottom_reference():
    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)
+
 # --- Lifecycle ------------------------------------------------------------


@@ -3663,6 +3671,8 @@ 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()
@@ -3674,6 +3684,34 @@ 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)
@@ -4044,6 +4082,71 @@ 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 ------------------------------------------------------


@@ -563,6 +563,11 @@ wasm_pair_indicator!(
    "BetaNeutralSpread",
    wc::BetaNeutralSpread
 );
+wasm_pair_indicator!(
+    WasmHasbrouckInformationShare,
+    "HasbrouckInformationShare",
+    wc::HasbrouckInformationShare
+);

 // ---------- PairSpreadZScore (two params) ----------

@@ -9279,6 +9284,66 @@ 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 {
@@ -9868,6 +9933,50 @@ 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,
@@ -10191,6 +10300,195 @@ 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)]
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -131,6 +131,7 @@ mod ema;
 mod empirical_mode_decomposition;
 mod engulfing;
 mod equivolume;
+mod estimated_leverage_ratio;
 mod even_better_sinewave;
 mod evening_doji_star;
 mod evwma;
@@ -156,6 +157,7 @@ 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;
@@ -174,6 +176,7 @@ 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;
@@ -277,9 +280,11 @@ 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;
@@ -294,8 +299,10 @@ 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;
@@ -423,6 +430,7 @@ 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;
@@ -616,6 +624,7 @@ 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;
@@ -641,6 +650,7 @@ 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;
@@ -659,6 +669,7 @@ 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;
@@ -762,9 +773,11 @@ 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;
@@ -779,8 +792,10 @@ 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;
@@ -908,6 +923,7 @@ pub use time_of_day_return_profile::{TimeOfDayReturnProfile, TimeOfDayReturnProf
 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;
@@ -1452,6 +1468,9 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
            "Vpin",
            "AmihudIlliquidity",
            "RollMeasure",
+            "TradeSignAutocorrelation",
+            "Pin",
+            "HasbrouckInformationShare",
        ],
    ),
    (
@@ -1469,6 +1488,11 @@ pub const FAMILIES: &[(&str, &[&str])] = &[
            "LiquidationFeatures",
            "TermStructureBasis",
            "CalendarSpread",
+            "EstimatedLeverageRatio",
+            "OiToVolumeRatio",
+            "PerpetualPremiumIndex",
+            "FundingImpliedApr",
+            "OpenInterestMomentum",
        ],
    ),
    (
@@ -1615,6 +1639,6 @@ 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, 485, "FAMILIES total drifted from indicator count");
+        assert_eq!(total, 493, "FAMILIES total drifted from indicator count");
    }
 }
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -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);
+    }
+}
@@ -81,17 +81,18 @@ pub use indicators::{
    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, FryPanBottom, FundingBasis, FundingRate,
-    FundingRateMean, FundingRateZScore, GainLossRatio, GapSideBySideWhite, Garch11,
-    GarmanKlassVolatility, Gartley, GatorOscillator, GatorOscillatorOutput, GeneralizedDema,
-    GeometricMa, GoldenPocket, GoldenPocketOutput, GrangerCausality, GravestoneDoji, Hammer,
-    HangingMan, Harami, HaramiCross, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator,
+    EmpiricalModeDecomposition, 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,
+    GapSideBySideWhite, Garch11, GarmanKlassVolatility, Gartley, GatorOscillator,
+    GatorOscillatorOutput, GeneralizedDema, GeometricMa, GoldenPocket, GoldenPocketOutput,
+    GrangerCausality, GravestoneDoji, Hammer, HangingMan, Harami, HaramiCross,
+    HasbrouckInformationShare, HeadAndShoulders, HeikinAshi, HeikinAshiOscillator,
    HeikinAshiOutput, HiLoActivator, HighLowIndex, HighLowRange, HighWave, HighpassFilter, Hikkake,
    HikkakeModified, HilbertDominantCycle, HistoricalVolatility, Hma, HoltWinters, HomingPigeon,
    HtDcPhase, HtPhasor, HtPhasorOutput, HtTrendMode, HurstChannel, HurstChannelOutput,
@@ -112,11 +113,12 @@ pub use indicators::{
    MedianPrice, Mfi, Microprice, MidPoint, MidPrice, MinusDi, MinusDm, ModifiedMaStop,
    ModifiedMaStopOutput, Mom, MorningDojiStar, MorningEveningStar, MurreyMathLines,
    MurreyMathLinesOutput, Natr, NewHighsNewLows, NewPriceLines, 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,
+    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,
@@ -140,20 +142,21 @@ pub use indicators::{
    TdSequentialOutput, TdSetup, TdTrap, Tema, TermStructureBasis, ThreeDrives, ThreeInside,
    ThreeLineBreak, ThreeLineStrike, ThreeOutside, ThreeSoldiersOrCrows, ThreeStarsInSouth,
    Thrusting, TickIndex, Tii, TimeBasedStop, TimeOfDayReturnProfile, TimeOfDayReturnProfileOutput,
-    TowerTopBottom, TpoProfile, TpoProfileOutput, TradeImbalance, 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,
+    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,
 };
 // `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
@@ -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 **485 indicators** across
+- A per-indicator deep dive for every one of the **493 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 &
@@ -17,7 +17,7 @@
    },
    "../../bindings/node": {
      "name": "wickra",
-      "version": "0.6.9",
+      "version": "0.7.1",
      "license": "MIT OR Apache-2.0",
      "devDependencies": {
        "@napi-rs/cli": "^2.18.0"
@@ -26,12 +26,12 @@
        "node": ">= 18"
      },
      "optionalDependencies": {
-        "wickra-darwin-arm64": "0.6.9",
-        "wickra-darwin-x64": "0.6.9",
-        "wickra-linux-arm64-gnu": "0.6.9",
-        "wickra-linux-x64-gnu": "0.6.9",
-        "wickra-win32-arm64-msvc": "0.6.9",
-        "wickra-win32-x64-msvc": "0.6.9"
+        "wickra-darwin-arm64": "0.7.1",
+        "wickra-darwin-x64": "0.7.1",
+        "wickra-linux-arm64-gnu": "0.7.1",
+        "wickra-linux-x64-gnu": "0.7.1",
+        "wickra-win32-arm64-msvc": "0.7.1",
+        "wickra-win32-x64-msvc": "0.7.1"
      }
    },
    "node_modules/wickra": {
@@ -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();
@@ -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`).
@@ -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.
Author	SHA1	Message	Date
kingchenc	5862401958	release: bump 0.7.0 -> 0.7.1 (#215 ) Version bump 0.7.0 -> 0.7.1 for the B16 Derivatives batch (493 indicators).	2026-06-08 03:35:31 +02:00
kingchenc	ff5a047078	feat(derivatives): leverage, OI/volume, perpetual premium, funding APR, OI momentum (B16) (#214 ) ## B16 Derivatives — five new indicators (488 → 493) All consume a `DerivativesTick` and emit `f64`: \| Indicator \| Reads \| Formula \| \|-----------\|-------\|---------\| \| `EstimatedLeverageRatio` \| open_interest, long_size, short_size \| `OI / (long + short)` \| \| `OiToVolumeRatio` \| open_interest, taker_buy_volume, taker_sell_volume \| `OI / (buy + sell)` \| \| `PerpetualPremiumIndex` \| mark_price, index_price \| `(mark − index) / index` \| \| `FundingImpliedApr` \| funding_rate \| `rate × intervals_per_year` \| \| `OpenInterestMomentum` \| open_interest \| `100 · (OI_t − OI_{t−period}) / OI_{t−period}` \| ### Wiring - Core structs + full unit tests (incl. zero-denominator branches). - Hand-written Python/Node/WASM tick bindings; two new tick helpers (`deriv_oi_long_short`, `deriv_oi_taker`). - Fuzz drives in `indicator_update_derivatives.rs`; dedicated reference + streaming-vs-batch tests (Python + Node). - README counter + `docs/README.md` + `FAMILIES` assert bumped to 493. ### Verify (local, all green) - `cargo test -p wickra-core --lib`: 4028 · `--doc`: 443 - clippy workspace: clean - node: 563 · pytest: 928	2026-06-08 03:33:59 +02:00
kingchenc	dc415a77fd	release: bump 0.6.9 -> 0.7.0 (#213 ) Version bump 0.6.9 -> 0.7.0 for the B15 Microstructure batch (488 indicators).	2026-06-08 03:10:16 +02:00
kingchenc	e385734275	feat(microstructure): trade-sign autocorrelation, PIN, Hasbrouck information share (B15) (#212 ) ## B15 Microstructure — three new indicators (485 → 488) \| Indicator \| Input \| Output \| Notes \| \|-----------\|-------\|--------\|-------\| \| `TradeSignAutocorrelation` \| `Trade` \| `f64` ∈ [-1,1] \| lag-1 autocorrelation of the signed aggressor (order-flow persistence) \| \| `Pin` \| `Trade` \| `f64` ∈ [0,1] \| probability of informed trading from rolling buy/sell imbalance (EKOP single-window estimator); `name()` = `"PIN"` \| \| `HasbrouckInformationShare` \| `(f64, f64)` \| `f64` ∈ [0,1] \| variance-ratio proxy for each venue's share of price discovery \| ### Wiring - Core structs + full unit tests (every branch). - Hand-written Python/Node/WASM bindings for the two `Trade`-input indicators (precedent `TradeImbalance`); `node_pair_indicator!` / `wasm_pair_indicator!` macro bindings + hand Python pyclass for the pairwise Hasbrouck (precedent `RollingCorrelation`). - Fuzz drives added to `indicator_update_trade.rs` and `indicator_update_pair.rs`. - Dedicated Python + Node streaming-vs-batch and reference tests; Hasbrouck in the `PAIR` registry. - README counter (3 spots) + `docs/README.md` + `FAMILIES` assert bumped to 488. ### Verify (all green, local) - `cargo test -p wickra-core --lib`: 3991 passed - `cargo test -p wickra-core --doc`: 438 passed - `cargo clippy --workspace --all-targets --all-features -- -D warnings`: clean - node: 561 passed · pytest: 926 passed	2026-06-08 03:07:50 +02:00