Files
wickra/bindings/wasm
kingchenc a3a1ae4dba Add 10 pairwise stat-arb indicators to Price Statistics (#154)
Adds ten pairwise `(f64, f64)` indicators to the **Price Statistics** family, completing the A1 stat-arb expansion block.

## Indicators

**Scalar output:**
- **RollingCorrelation** — rolling Pearson correlation of period-over-period *returns* (distinct from level-based `PearsonCorrelation`).
- **RollingCovariance** — rolling covariance of returns.
- **OuHalfLife** — Ornstein–Uhlenbeck half-life of mean reversion of the spread `a − b`.
- **SpreadHurst** — Hurst exponent of the spread (variance-of-lagged-differences fit) for regime detection.
- **DistanceSsd** — Gatev sum-of-squared-deviations between two start-normalised series.
- **BetaNeutralSpread** — rolling OLS regression residual `a − (α + β·b)`.
- **VarianceRatio** — Lo–MacKinlay variance-ratio test on the spread (two params: `period`, `q`).
- **GrangerCausality** — F-statistic for whether `b` predicts `a` (two params: `period`, `lag`).

**Struct output (custom bindings):**
- **KalmanHedgeRatio** — dynamic hedge ratio via a Kalman filter → `{ hedgeRatio, intercept, spread }`.
- **SpreadBollingerBands** — Bollinger bands on the spread → `{ middle, upper, lower, percentB }`.

## Notes
- No new traits or input families: all use the native `Indicator<Input = (f64, f64)>` (precedent `Beta`, `Cointegration`).
- Adds `Error::InvalidParameter` for floating-point constructor parameters (Kalman `delta`/`observation_var`, `num_std`).
- Full Python/Node/WASM bindings; the two struct-output indicators are hand-written, the rest use the pair macros.
- Indicator count 315 → 325; README, family rows, `__init__`, fuzz target, and CHANGELOG updated.

## Verification
- `cargo test --workspace --all-features` — green (2676 core lib + 308 doc).
- `cargo clippy --workspace --all-targets --all-features -- -D warnings` — clean.
- Node: `npm run build && npm test` — 410 passing (`index.d.ts`/`index.js` regenerated).
- Python: `pytest` — 684 passing.
2026-06-03 15:39:55 +02:00
..

Wickra — WebAssembly

CI codecov npm License: PolyForm-NC

Streaming-first technical indicators in the browser. npm install wickra-wasm — pure WebAssembly, runs anywhere a modern JS engine does.

Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1) streaming state machine, so live trading dashboards and historical backtests share the exact same implementation. This package is the WebAssembly binding (wasm-bindgen, built for the web target); it exposes 200+ streaming-first indicators across sixteen families.

Install

npm install wickra-wasm

Quick start

The module ships a default init export that loads the .wasm payload; await it once before constructing indicators.

import init, { RSI } from 'wickra-wasm';

await init(); // load the WebAssembly module once

// Streaming: feed prices tick by tick in O(1).
const rsi = new RSI(14);
for (const price of liveFeed) {
  const value = rsi.update(price); // null during warmup
  if (value !== null && value > 70) {
    console.log('overbought');
  }
}

Constructors mirror the other bindings (new SMA(20), new MACD(12, 26, 9), new BollingerBands(20, 2.0), …); update() returns the latest value or null while the indicator is still warming up.

Documentation

The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:

Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all expose the same indicators from the shared, unsafe-forbidden Rust core.

Disclaimer

Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.

License

Licensed under the PolyForm Noncommercial License 1.0.0. Personal projects, research, education, non-profits, and hobby trading bots are all fine; the one thing not allowed is commercial sale of the software or of services built around it. See LICENSE.