c78b84e186fa57b35977cababe664f4103f4e884
55 Commits
| Author | SHA1 | Message | Date | |
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 kingchenc
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c78b84e186 |
Add B8 Volume family deepening (7 indicators) (#195)
Deepens the **Volume** family (B8) with seven indicators (440 -> 447):
- **VolumeRsi** — Wilder RSI computed on signed volume flow.
- **WilliamsAd** — Williams Accumulation/Distribution cumulative line (distinct from Chaikin A/D).
- **TwiggsMoneyFlow** — true-range volume accumulation with Wilder smoothing (distinct from CMF).
- **TradeVolumeIndex** — tick-direction volume accumulation past a min-tick threshold (distinct from TSV).
- **IntradayIntensity** — volume weighted by close position within the bar range.
- **BetterVolume** — VSA volume-vs-spread effort/result classifier.
- **VolumeWeightedMacd** — MACD computed on VWMA with signal line and histogram (struct output).
("Up/Down Volume Ratio" already ships from A2.) All Candle input; the six scalar stops emit f64, VolumeWeightedMacd a {macd, signal, histogram} struct. Hand-written Python/Node/WASM bindings for the volume signature. Verified locally: 3620 core lib + 405 doc tests, clippy clean, 522 node tests, 865 pytest, counter 447.
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kingchenc
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2991ba411d |
Add B7 Trailing Stops family (6 indicators) (#193)
Adds the **Trailing Stops** family deepening (B7), six new indicators (434 -> 440):
- **KaseDevStop** — Cynthia Kase's volatility stop on the standard deviation of the two-bar true range.
- **ElderSafeZone** — Alexander Elder's stop offset by a multiple of average market noise.
- **AtrRatchet** — Kaufman ATR ratchet that tightens its multiple by a per-bar increment.
- **Nrtr** — Nick Rypock Trailing Reverse (percentage band).
- **TimeBasedStop** — exits after a fixed number of bars (scalar fraction of elapsed life).
- **ModifiedMaStop** — moving-average based trailing stop.
("Wilder Volatility System" is intentionally skipped — it overlaps the existing VoltyStop/Psar/SarExt.)
Each takes Candle input; the five band/structure stops emit a {value, direction} struct, TimeBasedStop a scalar. Wired across core, Python/Node/WASM bindings, fuzz target and tests. Verified locally: 3560 core lib + 398 doc tests, clippy clean, 515 node tests, 852 pytest, counter 440.
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kingchenc
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67feec598a |
feat(indicators): add B6 Bands & Channels family (429 -> 434) (#191)
Adds the **B6 Bands & Channels** batch — five band/channel indicators, taking the catalogue from 429 to 434.
| Indicator | Input → Output | Summary |
|-----------|----------------|---------|
| `ProjectionBands` | `Candle` → `{upper,middle,lower}` | Widner forward-projected high/low regression envelope |
| `ProjectionOscillator` | `Candle` → `f64` | Close position inside the projection bands, scaled 0..100 |
| `QuartileBands` | `f64` → `{upper,middle,lower}` | Rolling 25th/50th/75th-percentile (Q1/median/Q3) envelope |
| `BomarBands` | `f64` → `{upper,middle,lower}` | Adaptive percentage bands containing a target coverage fraction of recent closes |
| `MedianChannel` | `f64` → `{upper,middle,lower}` | Robust median ± multiplier·MAD envelope |
All five are distinct from existing indicators (verified against the core: `LinRegChannel`, `StandardErrorBands`, `Donchian`, `RollingQuantile`, `HurstChannel`). SKIPped from the roadmap: Price Channel (= `Donchian`) and Moving-Average Channel (≈ `MaEnvelope`/`Keltner`).
Each ships:
- Core indicator with per-branch unit tests (Codecov-strict 100%).
- python / node / wasm bindings (struct outputs are hand-written; `ProjectionOscillator` uses the generated candle→f64 path).
- Fuzz drives, python (`MULTI`/`SCALAR_MULTI`/`CANDLE_SCALAR`) + node test registries, README + CHANGELOG counter bump to 434.
Verified locally: `cargo fmt`, `clippy --workspace --all-targets --all-features -D warnings` (clean), `wickra-core` 3511 lib + 392 doc tests, node 509 tests, pytest 840.
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kingchenc
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6b8c6a0e7f |
B5 volatility & bands batch (423 -> 429) (#189)
Adds six **Volatility & Bands** indicators (Part B5 of the expansion roadmap), 423 → 429. | Indicator | Input → Output | Summary | |-----------|----------------|---------| | `EwmaVolatility` | `f64` → `f64` | RiskMetrics exponentially-weighted volatility (λ decay) | | `Garch11` | `f64` → `f64` | GARCH(1,1) conditional volatility with a long-run-variance anchor | | `BipowerVariation` | `f64` → `f64` | jump-robust realized bipower variation (π/2 · Σ\|rₜ\|\|rₜ₋₁\|) | | `VolatilityRatio` | `Candle` → `f64` | Schwager's true range over the EMA of prior true ranges (>2 = wide-ranging day) | | `VolatilityCone` | `Candle` → `VolatilityConeOutput` | current realized volatility within its min/median/max envelope + percentile | | `VolatilityOfVolatility` | `f64` → `f64` | sample stddev of a rolling realized-volatility series | ### Notes - Two B5 roadmap items were dropped as duplicates/by-construction: `RealizedVolatility` already ships (v0.5.4); `Downside Semi-Deviation` is internal to Sortino. `Bipower Variation` confirmed distinct from `JumpIndicator` (a ±1 flag, not a variance measure). - `VolatilityRatio` implements the widely-charted EMA-of-true-range convention (denominator excludes the current bar so the 2.0 threshold means "twice typical"), distinct from the existing pairwise `variance_ratio`. - `Garch11` mean-reverts to `ω/(1−β)` on a flat series (does not decay to 0 like EWMA) — pinned by a dedicated test. ### Coverage / verification - Full core + Python/Node/WASM bindings, fuzz drivers (scalar + candle), registries, CHANGELOG, README + docs counter sync. - 100% unit-test coverage per indicator (every branch). - Green locally: `cargo clippy --workspace --all-targets --all-features -D warnings`, core lib (3479) + doc (387), node (504), python (830). Deep-dive docs for all six are staged for `wickra-docs` and pushed after release (gated). |
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kingchenc
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1f4bf9e3a6 |
feat(core): B4 price oscillators (TsfOscillator, MacdHistogram, PpoHistogram) (#184)
Adds three **Price Oscillators** family indicators (420 → 423). ## Indicators - **TsfOscillator** — `100·(close − TSF)/close`, the percentage gap of the close to the **one-bar-ahead** time-series forecast. Close-relative companion to `Cfo`, which measures the same gap against the regression value at the *current* bar; the two differ by exactly the slope term `100·b/close`. - **MacdHistogram** — the standalone `macd − signal` bar of MACD exposed as a plain `f64` series. - **PpoHistogram** — the Percentage Price Oscillator with its 9-period signal EMA and the resulting scale-free, zero-centered histogram (PPO itself only emits the line). All three are scalar `f64` indicators wrapping existing, already-tested building blocks (`MacdIndicator`, `Ppo` + `Ema`, `Tsf`). ## Scope notes (VORAB-CHECK) The B4 roadmap listed six items; three were dropped to avoid duplicates: - *Forecast Oscillator* already ships as `Cfo`. - *Derivative Oscillator* already ships (`DerivativeOscillator`, B2). - *Detrended Synthetic Price* deferred — no citable formula distinct from the existing `Apo`/`Dpo`. ## Touchpoints Core (`tsf_oscillator.rs`, `macd_histogram.rs`, `ppo_histogram.rs`) with full per-branch unit tests, `mod.rs`/`lib.rs`, python/node/wasm bindings (wasm via typed-arg macro, python/node hand-written for the multi-arg histograms), fuzz drivers, python reference + streaming-vs-batch tests, node factories, README family row + counter, CHANGELOG. Local verify: `cargo test --workspace` green, `clippy -D warnings` clean, node 498 tests, full python suite green. |
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kingchenc
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13bc801f89 |
feat(indicators): B3 Trend & Directional batch (413 -> 420) (#181)
Adds the **B3 — Trend & Directional** batch: seven new indicators, taking the catalog from 413 to 420 (Trend & Directional family). | Indicator | Input → Output | Summary | |-----------|----------------|---------| | `Qstick` | candle → f64 | Chande's SMA of the candle body (close − open) | | `TtmTrend` | candle → f64 (±1) | John Carter close-vs-median-SMA trend filter | | `TrendStrengthIndex` | f64 → f64 | signed r² of an OLS regression of price vs time | | `PolarizedFractalEfficiency` | f64 → f64 | Hannula directional trend efficiency | | `WavePm` | f64 → f64 | Kase variance-normalised peak-momentum statistic (reconstruction) | | `GatorOscillator` | candle → struct | Bill Williams Alligator convergence/divergence histogram | | `KasePermissionStochastic` | candle → struct | double-smoothed stochastic permission filter | Note: the roadmap's "Directional Indicator +DI/−DI" item is already covered by the existing standalone `PlusDi` / `MinusDi` / `Dx`, so it is intentionally not re-added. All touchpoints wired: core (every-branch unit tests), Python/Node/WASM bindings, fuzz drivers, Python test registries + reference tests, Node factories, README/CHANGELOG counters. Local verify: `cargo test -p wickra-core` (lib 3389 + doc 378), `cargo clippy --workspace --all-targets --all-features -- -D warnings`, node build + 495 tests, maturin + 815 pytest, counter 420 == 420. |
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kingchenc
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4f81222aed |
Deepen Momentum Oscillators family with ten additions (#179)
Deepens the **Momentum Oscillators** family with ten widely-used oscillators (403 → 413 indicators), the second batch of Part B (family deepening). | Indicator | Binding | Input → Output | |-----------|---------|----------------| | `DisparityIndex` | `DisparityIndex` | scalar → scalar | | `FisherRsi` | `FisherRSI` | scalar → scalar | | `Rmi` | `RMI` | scalar (period, momentum) → scalar | | `DerivativeOscillator` | `DerivativeOscillator` | scalar (4 periods) → scalar | | `Rsx` | `RSX` | scalar → scalar | | `DynamicMomentumIndex` | `DynamicMomentumIndex` | scalar → scalar | | `IntradayMomentumIndex` | `IMI` | candle (open+close) → scalar | | `StochasticCci` | `StochasticCCI` | candle → scalar | | `ElderRay` | `ElderRay` | candle → struct (bull/bear) | | `Qqe` | `QQE` | scalar → struct (rsi_ma/trailing) | LSMA was dropped from the planned set: it already ships as `LinearRegression`. The single-period scalars use generated macro bindings; `Rmi` / `DerivativeOscillator` use hand node/python bindings with the typed wasm macro; `ElderRay`/`Qqe` use custom struct bindings; `IntradayMomentumIndex` uses custom candle bindings carrying the open. Full coverage: core modules with per-branch unit tests, mod/lib catalogue, FAMILIES + assert, README + docs counters, CHANGELOG, all three bindings (regenerated `index.d.ts`/`index.js`), fuzz drivers, and the python/node test registries. Local verification: `cargo test -p wickra-core` (lib 3335 + doc 371), `cargo clippy --workspace --all-targets --all-features -D warnings` clean, node `npm run build && npm test` (488), python `pytest` (802). |
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kingchenc
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b228a70d7d |
Deepen Moving Averages family with seven additions (#177)
Deepens the **Moving Averages** family with seven widely-used variants (396 → 403 indicators), the first batch of Part B (family deepening). All are scalar `f64 → f64`: | Indicator | Binding | Notes | |-----------|---------|-------| | `SineWeightedMa` | `SWMA` | symmetric half-cycle sine-weighted window | | `GeometricMa` | `GMA` | rolling geometric mean (log-space average) | | `Ehma` | `EHMA` | exponential Hull MA (Hull construction over EMAs) | | `MedianMa` | `MedianMA` | rolling median, robust to single outliers | | `AdaptiveLaguerreFilter` | `AdaptiveLaguerre` | Ehlers' adaptive Laguerre filter (median-of-normalised-error γ) | | `GeneralizedDema` | `GD` | Tillson's volume-factor double EMA; `v=1` is DEMA, `v=0` is EMA | | `HoltWinters` | `HoltWinters` | Holt's linear double exponential smoothing (level + trend) | LSMA was dropped from the planned set: it already ships as `LinearRegression` (TA-Lib `LINEARREG`, the rolling least-squares endpoint). The five single-period filters use the generated scalar macro bindings; `GeneralizedDema` (period, v) and `HoltWinters` (alpha, beta) use hand-written node/python bindings with the typed wasm macro (precedent `T3` / `Alma`). Full coverage: core modules with per-branch unit tests (100% intent), mod/lib catalogue, FAMILIES group + assert, README + docs counters, CHANGELOG, all three bindings (regenerated `index.d.ts` / `index.js`), fuzz drivers, and the python/node test registries. Local verification: `cargo test -p wickra-core` (lib 3255 + doc 361), `cargo clippy --workspace --all-targets --all-features -D warnings` clean, node `npm run build && npm test` (478), python `pytest` (791). |
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kingchenc
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fcb221ec03 |
feat: add 19 indicators for external feature-extractor coverage (377 -> 396) (#175)
Adds 19 streaming indicators so an external trading-bot feature extractor can replace its hand-built features with native, batch/streaming-equivalent ones. Each is a real gap (verified against the existing catalogue), production-only, with full Python/Node/WASM bindings, fuzz drivers, and tests. Five commits, one per family group; counter 377 -> 396. ## What's added **Price Statistics (6)** — `LogReturn`, `RealizedVolatility` (raw quadratic variation, the un-annualised counterpart to `HistoricalVolatility`), `RollingQuantile`, `RollingIqr`, `RollingPercentileRank`, `SpreadAr1Coefficient` (pairwise AR(1) rho of the spread; complements `OuHalfLife`). **Price Action (4)** — `CloseVsOpen`, `BodySizePct`, `WickRatio`, `HighLowRange` (stateless per-bar OHLC transforms). **Regime / Trend / Jump labels (3)** — `TrendLabel` (sign of the rolling OLS slope), `JumpIndicator` (return outliers vs trailing volatility, measured as deviation from the trailing mean so steady drift is not flagged), `RegimeLabel` (volatility-quantile regime split). **Risk / Performance (2)** — `WinRate`, `Expectancy` (R-multiple). **Microstructure (4)** — `OrderFlowImbalance` (Cont-Kukanov-Stoikov OFI), `Vpin`, `AmihudIlliquidity`, `RollMeasure`. These reuse the existing `OrderBook` / `Trade` inputs (no new input type). ## Intentionally NOT added (already present, would be duplicates) - **Population skew / kurtosis** — `skewness.rs` / `kurtosis.rs` are already population moments (divisor n). - **Hurst R/S** — `hurst_exponent.rs` already uses rescaled-range (R/S) analysis. - **Queue Imbalance** — exactly `OrderBookImbalanceTop1` ((bidSize - askSize) / (bidSize + askSize)). ## Verification `cargo test -p wickra-core` (lib 3187 + doc 354), `cargo clippy --workspace --all-targets --all-features -D warnings` clean, node `npm run build && npm test` (471), python `pytest` (784). Counter consistent across `mod.rs`, lib block, README, and docs/README at 396. |
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kingchenc
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5a1d607807 |
feat(indicators): A5b Fibonacci tools (geometric) (#172)
Completes the **Fibonacci** family with the four geometric/time tools (catalogue 373 -> 377). All extend the internal `pattern_swing` ZigZag tracker with a per-pivot bar index and a current-bar counter (additive — the chart/harmonic detectors are unaffected), and emit `Candle -> struct` outputs via custom Python/Node/WASM bindings. | Tool | Output | |------|--------| | `FibFan` | three trendlines fanning from a swing start through its 38.2/50/61.8% retracement levels, extended to the current bar | | `FibArcs` | semicircular retracement levels centred on the swing end, normalised by the leg's bar-width (chart-scale-free) | | `FibChannel` | a sloped base trendline plus parallel lines at Fibonacci multiples of the channel width | | `FibTimeZones` | markers at Fibonacci bar-distances (1/2/3/5/8/...) from the latest swing pivot | The geometric tools are novel as streaming indicators; each normalises its geometry to the swing leg's bar-width so the output is chart-scale-free. Formulas are documented in each module and deep-dive. Fully wired: core (100% unit-tested branches incl. the new `pattern_swing` bar tracking), Python/Node/WASM struct bindings, fuzz, reference + streaming-vs-batch tests. Verification: `cargo test --workspace` green, clippy `-D warnings` clean, node 454 tests, python 768 tests. |
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kingchenc
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716eb40206 |
feat(indicators): A5a Fibonacci tools (price-level) (#171)
Adds the six price-level Fibonacci tools as a new **Fibonacci** family (catalogue 367 -> 373, twenty-four families). All build on the internal `pattern_swing` ZigZag tracker, are parameter-free (baked 5% swing threshold), and emit `Candle -> struct` outputs via custom Python/Node/WASM bindings. | Tool | Output | |------|--------| | `FibRetracement` | seven levels (0/23.6/38.2/50/61.8/78.6/100%) of the last swing leg | | `FibExtension` | five extension ratios (127.2/141.4/161.8/200/261.8%) projected beyond the leg | | `FibProjection` | A-B-C measured-move target zone (61.8/100/161.8/261.8%) | | `AutoFib` | retracement anchored on the dominant (largest-magnitude) recent leg | | `GoldenPocket` | the 0.618-0.65 optimal-trade-entry band (low/mid/high) | | `FibConfluence` | densest cluster of retracement levels across recent legs (price + strength) | Fully wired: core (100% unit-tested branches), Python/Node/WASM struct bindings, fuzz driver, reference + streaming-vs-batch tests, README/docs counter. The four geometric/time tools (Fan, Arcs, Channel, Time Zones) follow in A5b. Verification: `cargo test --workspace` green, clippy `-D warnings` clean, node 450 tests, python 760 tests. |
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kingchenc
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4250ed99f4 |
feat(patterns): add the Harmonic Patterns family (8 XABCD detectors) (#169)
## Summary Adds a new **Harmonic Patterns** indicator family (counter 359 → 367, families 22 → 23) — the second half of the A4 roadmap item, following the Chart Patterns family in #166. Eight Fibonacci-ratio detectors built on the shared swing-pivot tracker (`indicators::pattern_swing`) plus two new helpers there — `xabcd` (reads the last five pivots as X-A-B-C-D) and `ratios_in` (checks a list of `(value, low, high)` Fibonacci windows in one expression, no multi-line `&&` coverage gaps). Each consumes candles and emits the uniform pattern sign convention — `+1.0` bullish (terminal point D a swing low), `-1.0` bearish (D a swing high), `0.0` otherwise, never `None`. Parameter-free, with the Fibonacci windows documented as constants per detector. ## Detectors | Indicator | Defining ratio | |-----------|----------------| | `Abcd` | four-point AB=CD (BC retraces AB, CD ≈ AB) | | `Gartley` | AD/XA ≈ 0.786 | | `Butterfly` | AD/XA ∈ 1.27–1.618 (extended D) | | `Bat` | AD/XA ≈ 0.886, shallow B | | `Crab` | AD/XA ≈ 1.618 (deepest D) | | `Shark` | expansion AB, AD/XA 0.886–1.13 | | `Cypher` | BC on XA, CD/XC ≈ 0.786 | | `ThreeDrives` | two symmetric extension drives | ## Touchpoints Core modules + `FAMILIES` group/assert, crate root re-exports, Python/Node/WASM bindings via the candle-pattern macros (Node `index.d.ts`/`index.js` regenerated), the candle fuzz target (`// --- Harmonic Patterns ---` section), Python reference + `CANDLE_SCALAR` registry tests and the Node candle-scalar factory, README catalogue counter + banner cache-buster + family table row + family-count word, `docs/README.md` counter, and the changelog. ## Verification - `cargo test -p wickra-core --lib` — 2966 passed - `cargo test -p wickra-core --doc` — 335 passed - `cargo clippy --workspace --all-targets --all-features -- -D warnings` — clean - Node `npm run build && npm test` — 444 passed - Python `maturin develop --release` + `pytest` — 748 passed Every detector branch is unit-tested, including a bullish and a bearish match per pattern to cover both output arms, plus an out-of-ratio non-match. Fibonacci windows use standard harmonic-trading ranges with documented tolerance bands. |
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kingchenc
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995f119010 |
feat(patterns): add the Chart Patterns family (8 swing-based detectors) (#166)
## Summary Adds a new **Chart Patterns** indicator family (counter 351 → 359, families 21 → 22), the first half of the A4 roadmap item (the harmonic patterns follow in a second PR). All eight detectors are built on a shared, non-repainting swing-pivot tracker — the internal, **uncounted** `indicators::pattern_swing` module (declared `pub(crate) mod`, re-exported nowhere). Each consumes candles and emits the uniform pattern sign convention already used by the candlestick family — `+1.0` bullish / `-1.0` bearish / `0.0` otherwise, never `None`. They are parameter-free, baking the swing threshold (5%) and level tolerance (3%) in as documented constants, mirroring how candlestick patterns bake in their geometric thresholds. ## Detectors | Indicator | Signal | |-----------|--------| | `DoubleTopBottom` | twin-peak / twin-trough reversal | | `TripleTopBottom` | three matching extremes (stronger reversal) | | `HeadAndShoulders` | central head + matching shoulders + flat neckline (and inverse) | | `Triangle` | ascending (+1) / descending (-1) / symmetrical | | `Wedge` | rising wedge (-1) / falling wedge (+1) | | `FlagPennant` | shallow consolidation against a pole → continuation | | `RectangleRange` | flat support/resistance mean-reversion | | `CupAndHandle` | rounded base + shallow handle (and inverse) | ## Touchpoints Core modules + `FAMILIES` group and assert, crate root re-exports, Python/Node/WASM bindings via the candle-pattern macros (Node `index.d.ts`/`index.js` regenerated), the candle fuzz target, Python reference + `CANDLE_SCALAR` registry tests and the Node candle-scalar factory, README catalogue counter + banner cache-buster + family table row + family-count word, `docs/README.md` counter, and the changelog. ## Verification - `cargo test -p wickra-core --lib` — 2915 passed - `cargo test -p wickra-core --doc` — 335 passed - `cargo clippy --workspace --all-targets --all-features -- -D warnings` — clean - Node `npm run build && npm test` — 436 passed - Python `maturin develop --release` + `pytest` — 732 passed Every detector branch is unit-tested; multi-condition predicates were flattened to single-line precomputed booleans to keep patch coverage at 100%. |
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kingchenc
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c096943bdf |
feat(breadth): complete the Market Breadth family (14 indicators) (#157)
Completes expansion-roadmap block **A2 — Market Breadth**: the 14 indicators that remained after the `AdvanceDecline` bootstrap, all built on the existing `CrossSection` input. ## Indicators (all scalar `Indicator<Input = CrossSection, Output = f64>`) | Indicator | Reading | |-----------|---------| | `AdvanceDeclineRatio` | advancers / decliners | | `AdVolumeLine` | cumulative net advancing volume | | `McClellanOscillator` | 19/39 EMAs of ratio-adjusted net advances | | `McClellanSummationIndex` | running total of the oscillator | | `Trin` (Arms Index) | A/D ratio over up/down volume ratio | | `BreadthThrust` (Zweig) | SMA of the advancing-issues share | | `NewHighsNewLows` | new highs − new lows | | `HighLowIndex` | SMA of the record-high percent | | `PercentAboveMa` | % of the universe above its MA | | `UpDownVolumeRatio` | advancing / declining volume | | `BullishPercentIndex` | % on a point-and-figure buy signal | | `CumulativeVolumeIndex` | volume-normalised cumulative net advancing volume | | `AbsoluteBreadthIndex` | \|advancers − decliners\| | | `TickIndex` | instantaneous net advancers − decliners | ## Input model `AdVolumeLine` and `CumulativeVolumeIndex` are kept distinct (the latter normalises each tick's net advancing volume by total volume, so it stays comparable across volume regimes). `PercentAboveMa` and `BullishPercentIndex` need a per-symbol state signal that `Member` did not carry, so `Member` gains two additive flags (`above_ma`, `on_buy_signal`) via a new `Member::with_signals` constructor; the 4-arg `Member::new` leaves both cleared, so every existing caller and binding is unchanged. `CrossSection` gains volume / new-extreme / state aggregation helpers. ## Wiring Fully wired across the Rust core, the python/node/wasm bindings, the cross-section fuzz target, the README + docs indicator counters (325 → 339), and dedicated python/node streaming-vs-batch tests. `fmt` / `test --workspace --all-features` / `clippy --workspace -D warnings` / node build+test / pytest all green locally. |
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kingchenc
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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.
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kingchenc
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53941b7b07 |
feat: add Market Breadth family with CrossSection input (#153)
## What Adds a new indicator input type and family for **market-breadth** analysis — indicators that aggregate the state of an entire universe of symbols at each tick, rather than a single instrument's price. This is the last open input-type on the expansion roadmap (S10) and unblocks the remaining breadth indicators (McClellan, TRIN, High-Low Index, ...). ## Core - **`CrossSection` input type** (`crates/wickra-core/src/cross_section.rs`) — one tick carrying the per-symbol state of the whole universe as a `Vec<Member>` + `timestamp`. Each `Member` precomputes a signed `change` (sign classifies advancing / declining / unchanged), a `volume`, and `new_high` / `new_low` extreme flags, so the breadth indicators stay stateless per tick. Both `Member` and `CrossSection` are `#[non_exhaustive]` for additive field growth. `CrossSection::new` validates the universe (non-empty, finite changes, finite non-negative volumes); `new_unchecked` skips validation for hot paths. `advancers()` / `decliners()` count by sign. - **`Error::InvalidCrossSection`** variant for the validation failures. - **`AdvanceDecline`** (`advance_decline.rs`) — the Advance/Decline Line: the running cumulative sum of net advancing-minus-declining issues. `Input = CrossSection`, `Output = f64`, ready after the first tick. - New **"Market Breadth"** `FAMILIES` group; indicator count **314 → 315**, family count nineteen → twenty. ## Bindings All custom (CrossSection is non-scalar, so no macros apply). The universe crosses each boundary as parallel arrays (`change`, `volume`, `new_high`, `new_low`): - **Python / Node** expose `update` + `batch` (one array group per tick). Node satisfies the completeness contract (`update`/`batch`/`reset`/`isReady`/`warmupPeriod`). - **WASM** exposes only `update` (the universe is ragged across ticks, matching the other multi-input wasm indicators) with numeric high/low flags. - Python `map_err` gains the new error arm; `__init__.py` gets a `# Market Breadth` section in both the import and `__all__` blocks. `index.d.ts` / `index.js` regenerated. ## Tests / Fuzz - Dedicated **streaming-vs-batch + reference-value + ragged-rejection** tests in Python (`test_new_indicators.py`) and Node (`indicators.test.js`) — kept out of the scalar/candle parametrize lists. - Rust unit tests cover every reject branch (empty / non-finite change / negative & non-finite volume) and every indicator branch. - New fuzz target `indicator_update_crosssection` drives `AdvanceDecline` over bounded ragged universes built with `new_unchecked`. ## Verify - `cargo fmt --all` clean - `cargo test -p wickra-core --lib` → 2593 passed; `--doc` → 298 passed - `cargo clippy --workspace --all-targets --all-features -- -D warnings` clean - `cd bindings/node && npm run build && npm test` → 398 passed - `maturin develop --release` + `pytest bindings/python/tests` → all passed - counter check: mod-count 315 == lib-block 315 |
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kingchenc
|
9eb46f144a |
feat: TA-Lib parity — 19 standalone indicators (DM components, price transforms, ROC/LinReg/MACD/SAR variants, Hilbert outputs) (#148)
Closes the remaining TA-Lib function-name gap by shipping each missing or bundled-only function as a real, standalone, fully-covered indicator. 19 new indicators across 5 families; mod-count 295 -> 314. ### Trend & Directional — Directional Movement components - `PlusDm` (`PLUS_DM`), `MinusDm` (`MINUS_DM`) — Wilder-smoothed ±DM. - `PlusDi` (`PLUS_DI`), `MinusDi` (`MINUS_DI`) — `100·smoothed(±DM)/ATR`. - `Dx` (`DX`) — `100·|+DI−−DI|/(+DI+−DI)`. ### Price Statistics - `AvgPrice` (`AVGPRICE`) — `(O+H+L+C)/4`. - `MidPoint` (`MIDPOINT`) — `(max+min)/2` of a scalar series over N. - `MidPrice` (`MIDPRICE`) — `(highestHigh+lowestLow)/2` over N. - `LinRegIntercept` (`LINEARREG_INTERCEPT`) — OLS intercept. - `Tsf` (`TSF`) — time series forecast `a + b·period`. ### Momentum Oscillators - `Rocp` (`ROCP`), `Rocr` (`ROCR`), `Rocr100` (`ROCR100`) — ROC ratio forms. ### Trailing Stops - `SarExt` (`SAREXT`) — Parabolic SAR with start value, reversal offset, separate long/short acceleration, signed output. ### Trend & Directional — MACD variants - `MacdFix` (`MACDFIX`) — MACD fixed 12/26. - `MacdExt` (`MACDEXT`) — MACD with a selectable moving-average type per line (new public `MaType` enum: SMA/EMA/WMA/DEMA/TEMA/TRIMA). ### Ehlers / Cycle (DSP) — Hilbert transform outputs - `HtPhasor` (`HT_PHASOR`) — in-phase / quadrature components. - `HtDcPhase` (`HT_DCPHASE`) — dominant-cycle phase (degrees). - `HtTrendMode` (`HT_TRENDMODE`) — trend (1) vs cycle (0) classification. Each indicator ships the full chain: core + every-branch unit tests, Python / Node / WASM bindings, fuzz coverage, README counter + family rows, CHANGELOG. `cargo test`, doctests, `clippy -D warnings`, `npm test` and pytest all green locally; mod-count == lib-block == README counter (314), FAMILIES total 309. |
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kingchenc
|
d4b3f9dbd1 |
feat: add Alt-Chart Bars (Renko, Kagi, Point & Figure) via a BarBuilder trait (#146)
Introduces a BarBuilder trait for price-driven chart constructors that emit a variable number of bars per candle (deliberately not Indicator). Adds Renko (box-size bricks, 2-box reversal), Kagi (reversal-amount segments) and Point & Figure (box-size X/O columns, N-box reversal) in a new Alt-Chart Bars family, with custom Python/Node/WASM bindings, a dedicated fuzz target, tests and docs. Indicator count 292 -> 295. |
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kingchenc
|
f37eedd44e |
feat: add Volume Profile and TPO Profile to the market profile family (#145)
Volume Profile exposes the full per-bin volume histogram (price bounds plus raw distribution) that Value Area reduces to POC/VAH/VAL. TPO Profile is the volume-agnostic Time-Price-Opportunity letter count over a rolling window. Both candle-input, Vec-output, Market Profile family, with custom Python/Node/WASM bindings, fuzz, benches, tests and docs. Indicator count 290 -> 292. |
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kingchenc
|
93097db482 |
feat: add Anchored RSI to the momentum oscillators family (#144)
Cumulative Relative Strength Index whose averaging begins at a runtime-chosen anchor bar (set_anchor), the momentum counterpart to Anchored VWAP. Scalar f64 input, 0..=100 output; wired through core, Python, Node and WASM bindings, fuzz, benches, tests and docs. Indicator count 289 -> 290. |
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kingchenc
|
124efb4432 |
feat: TA-Lib candlestick patterns — tasuki-gap/unique-three-river/marubozu-pair/concealing-baby-swallow (part 9 of 9) (#141)
The final batch of the TA-Lib candlestick roadmap. Adds five patterns, each a streaming `Indicator<Input = Candle, Output = f64>` emitting the family's uniform `±1.0 / 0.0` sign convention, fully wired across the Rust core, Python / Node / WASM bindings, fuzz target and reference tests. - **Tasuki Gap** (`CDLTASUKIGAP`) — a 3-bar continuation: two same-coloured candles gap in the trend direction, then an opposite candle opens within the second body and closes back into the gap without filling it; upside +1, downside -1. - **Unique Three River** (`CDLUNIQUE3RIVER`) — a 3-bar bullish reversal: a long black candle, a black candle probing a new low with its body inside the first, then a small white candle held below it; bullish +1. - **Closing Marubozu** (`CDLCLOSINGMARUBOZU`) — a single long-bodied candle with no shadow on the close end; +1 (white, closes at the high) or -1 (black, closes at the low). - **Opening Marubozu** — a single long-bodied candle with no shadow on the open end; +1 (white, opens at the low) or -1 (black, opens at the high). No direct TA-Lib equivalent — completes the pair with the closing marubozu. - **Concealing Baby Swallow** (`CDLCONCEALBABYSWALL`) — a rare 4-bar bullish capitulation: two black marubozu, a black candle gapping down with an upper shadow into the second, then a large black candle engulfing it entirely; bullish +1. Body and shadow thresholds follow the geometric house style (fixed fractions of the bar range) rather than TA-Lib's rolling averages. Counter 284 → 289 (mod-count == lib counted block; FAMILIES total 279 → 284). Stacked on #140 (`feat/cdl-gap-methods`); base retargets to `main` as the stack merges down. |
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kingchenc
|
4d0bc08efd |
feat: TA-Lib candlestick patterns — gap-three-methods/stalled/stick-sandwich/takuri (part 8 of 9) (#140)
Adds five TA-Lib candlestick patterns, each a streaming `Indicator<Input = Candle, Output = f64>` emitting the family's uniform `±1.0 / 0.0` sign convention, fully wired across the Rust core, Python / Node / WASM bindings, fuzz target and reference tests. - **Upside Gap Three Methods** (`CDLXSIDEGAP3METHODS`) — a 3-bar bullish continuation: two white candles gap up, then a black candle opens within the second body and closes within the first; bullish +1. - **Downside Gap Three Methods** (`CDLXSIDEGAP3METHODS`) — the bearish mirror: two black candles gap down, then a white candle opens within the second body and closes within the first; bearish -1. - **Stalled Pattern** (`CDLSTALLEDPATTERN`) — a 3-bar bearish reversal warning: two long white candles then a small white candle riding the shoulder, signalling the rally is stalling; bearish -1. - **Stick Sandwich** (`CDLSTICKSANDWICH`) — a 3-bar bullish reversal: two black candles closing at the same level sandwich a white candle, marking a support floor; bullish +1. - **Takuri** (`CDLTAKURI`) — a single-bar bullish reversal, a strict Dragonfly Doji with a negligible upper shadow and very long lower shadow; bullish +1. Body and shadow thresholds follow the geometric house style (fixed fractions of the bar range) rather than TA-Lib's rolling averages. Upside / Downside Gap Three Methods share the `CDLXSIDEGAP3METHODS` code, so the second carries a manual CHANGELOG entry (as with Rising / Falling Three Methods). Counter 279 → 284 (mod-count == lib counted block; FAMILIES total 274 → 279). Stacked on #139 (`feat/cdl-lines`); base retargets to `main` once the predecessor merges. |
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kingchenc
|
c2c85c7ecf |
feat: TA-Lib candlestick patterns — matching-low/lines/three-methods (part 7 of 9) (#139)
Adds five TA-Lib candlestick patterns, all `Input = Candle`, `Output = f64` (`+1.0` bullish / `-1.0` bearish / `0.0` no pattern), wired across core, Python/Node/WASM bindings, fuzz, and tests. - **Matching Low** (`CDLMATCHINGLOW`) — 2-bar bullish reversal: two black candles in a decline share the same close, signalling selling pressure is exhausting; bullish +1. - **Long Line** (`CDLLONGLINE`) — a candle whose range beats a rolling average of recent ranges with a body-dominated range; bullish +1 (white) / bearish -1 (black). - **Short Line** (`CDLSHORTLINE`) — a compact candle whose range falls below the rolling average with a body-dominated range; bullish +1 (white) / bearish -1 (black). - **Rising Three Methods** (`CDLRISEFALL3METHODS`) — 5-bar bullish continuation: a long white candle, three small bars holding within its range, then a white breakout to new highs; bullish +1. - **Falling Three Methods** (`CDLRISEFALL3METHODS`) — the bearish mirror: a long black candle, three small bars within its range, then a black breakdown to new lows; bearish -1. Counter 274 → 279 (mod-count == lib counted block; FAMILIES total 269 → 274). Stacked on #138 (part 6 of 9); base retargets to `main` as the chain merges. |
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kingchenc
|
04ae145126 | feat: TA-Lib candlestick patterns — separating/kicking/ladder/mat-hold (part 6 of 9) (#138) | ||
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kingchenc
|
e4ca9c3f8f |
feat: TA-Lib candlestick patterns — hikkake-mod/pigeon/neck-lines (part 5 of 9) (#137)
* feat: add hikkake-modified, homing-pigeon and neck-line candlestick patterns Five patterns, all `Input = Candle`, `Output = f64`: - Modified Hikkake (CDLHIKKAKEMOD) — a close-confirmed Hikkake: an inside bar then a breakout that closes back inside the inside-bar range; bullish +1, bearish -1. - Homing Pigeon (CDLHOMINGPIGEON) — two black candles, the second a small body inside the first, a bullish reversal; +1. - On-Neck (CDLONNECK) — long black bar then a white bar closing at its low (the neckline), a bearish continuation; -1. - In-Neck (CDLINNECK) — long black bar then a white bar closing just into its body, a bearish continuation; -1. - Thrusting (CDLTHRUSTING) — long black bar then a white bar closing well into but below the midpoint of its body, a bearish continuation; -1. Counter 264 -> 269 (mod-count == lib counted block; FAMILIES total 259 -> 264). * chore: sync indicator count to 269 --------- Co-authored-by: wickra-bot <wickra-bot@users.noreply.github.com> |
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kingchenc
|
d43bc9ddf3 |
feat: TA-Lib candlestick patterns — doji-star/gap/high-wave/hikkake (part 4 of 9) (#135)
* feat: add doji-star, gap, high-wave and hikkake candlestick patterns Five patterns, all `Input = Candle`, `Output = f64`: - Evening Doji Star (CDLEVENINGDOJISTAR) — bearish top reversal: long white bar, a doji gapping up, then a black bar closing deep into the first body; -1 (penetration configurable, default 0.3). - Morning Doji Star (CDLMORNINGDOJISTAR) — bullish bottom reversal mirror; +1. - Gap Side-by-Side White (CDLGAPSIDESIDEWHITE) — two similar white candles opening side by side after a gap, a continuation; gap up +1, gap down -1. - High-Wave (CDLHIGHWAVE) — a small body with very long shadows on both sides, an extreme indecision flag; +1 on detection. - Hikkake (CDLHIKKAKE) — an inside bar followed by a failed breakout (a trap); bullish +1, bearish -1. Counter 259 -> 264 (mod-count == lib counted block; FAMILIES total 254 -> 259). * chore: sync indicator count to 264 --------- Co-authored-by: wickra-bot <wickra-bot@users.noreply.github.com> |
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kingchenc
|
244d754707 |
feat: TA-Lib candlestick patterns — Doji family (part 3 of 9) (#134)
* feat: add Doji-family candlestick patterns Five single-/two-bar Doji patterns, all `Input = Candle`, `Output = f64`: - Doji Star (CDLDOJISTAR) — a long body followed by a doji gapping away in the trend direction; bullish +1 (after a black bar), bearish -1 (after a white bar). - Dragonfly Doji (CDLDRAGONFLYDOJI) — a doji opening and closing at the high with a long lower shadow; bullish +1. - Gravestone Doji (CDLGRAVESTONEDOJI) — a doji opening and closing at the low with a long upper shadow; bearish -1. - Long-Legged Doji (CDLLONGLEGGEDDOJI) — a doji with long shadows on both sides; a non-directional indecision flag, +1 on detection. - Rickshaw Man (CDLRICKSHAWMAN) — a long-legged doji with the body centred in the range; a non-directional indecision flag, +1 on detection. Counter 254 -> 259 (mod-count == lib counted block; FAMILIES total 249 -> 254). * chore: sync indicator count to 259 --------- Co-authored-by: wickra-bot <wickra-bot@users.noreply.github.com> |
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kingchenc
|
03ceac1f3b |
feat: TA-Lib candlestick patterns — abandoned/advance/belt/break/counter (part 2 of 9) (#132)
* feat: add Abandoned Baby candlestick pattern (CDLABANDONEDBABY) * feat: add Advance Block candlestick pattern (CDLADVANCEBLOCK) * feat: add Belt Hold candlestick pattern (CDLBELTHOLD) * feat: add Breakaway and Counterattack candlestick patterns (CDLBREAKAWAY, CDLCOUNTERATTACK) Breakaway is a 5-bar reversal: a trend gaps away on the second bar, drifts two more bars, then the fifth bar snaps back and closes inside the bar1/bar2 body gap (bullish +1, bearish -1). Counterattack is a 2-bar reversal where an opposite-coloured long second bar closes level with the first (the counterattack line; bullish +1, bearish -1). Also suppress libtest's spanless `large_stack_arrays` false positive in wickra-core test builds: the `#[test]` harness collects every test into a compiler-generated array of references that crosses clippy's 16 KB threshold once the suite passes ~2048 unit tests. The allow is scoped to `cfg(test)`, so library code is still linted for genuinely large stack arrays. * chore: sync indicator count to 254 --------- Co-authored-by: wickra-bot <wickra-bot@users.noreply.github.com> |
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kingchenc
|
f09057aaf1 |
feat: TA-Lib candlestick patterns — crows & three-line (part 1 of 9) (#130)
* feat: add Two Crows candlestick pattern (CDL2CROWS) * feat: add Upside Gap Two Crows candlestick pattern (CDLUPSIDEGAP2CROWS) * feat: add Identical Three Crows candlestick pattern (CDLIDENTICAL3CROWS) * feat: add Three Line Strike candlestick pattern (CDL3LINESTRIKE) * feat: add Three Stars in the South candlestick pattern (CDL3STARSINSOUTH) |
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kingchenc
|
2d140419bb |
feat: derivatives basis & calendar-spread indicators (part 3 of 3) (#128)
* feat(derivatives): TermStructureBasis indicator (core) * feat(derivatives): CalendarSpread indicator (core) * feat(derivatives): Python, Node and WASM bindings for basis & calendar-spread indicators * test(derivatives): Python and Node tests for basis & calendar-spread indicators * docs(derivatives): README row + counter 242->244, CHANGELOG part 3; fuzz basis indicators |
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kingchenc
|
8e5bfd07ce |
feat: derivatives open-interest, flow & liquidation indicators (part 2 of 3) (#127)
* feat(derivatives): OIPriceDivergence indicator (core) * feat(derivatives): OIWeighted indicator (core) * feat(derivatives): LongShortRatio indicator (core) * feat(derivatives): TakerBuySellRatio indicator (core) * feat(derivatives): LiquidationFeatures multi-output indicator (core) * feat(derivatives): Python, Node and WASM bindings for OI, flow & liquidation indicators * test(derivatives): Python and Node tests for OI, flow & liquidation indicators * fuzz(derivatives): drive OI, flow & liquidation indicators in derivatives target * docs(derivatives): README row + counter 237->242, CHANGELOG part 2 |
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kingchenc
|
5eb820a9c7 |
feat: derivatives funding & open-interest indicators (part 1 of 3) (#126)
* feat(derivatives): DerivativesTick input type + InvalidDerivatives error * feat(derivatives): FundingRate indicator (core) * feat(derivatives): FundingRateMean indicator (core) * feat(derivatives): FundingRateZScore indicator (core) * feat(derivatives): FundingBasis indicator (core) * feat(derivatives): OpenInterestDelta indicator (core) * feat(derivatives): Python, Node and WASM bindings for funding & OI-delta indicators * test(derivatives): Python and Node tests for funding & OI-delta indicators * bench(derivatives): synthetic-tick bench + derivatives fuzz target * docs(derivatives): README family row + counter 232->237, CHANGELOG entry |
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kingchenc
|
3dd7010129 | feat: footprint microstructure indicator (part 4 of 4) (#123) | ||
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kingchenc
|
4f11df0e33 |
feat: microstructure price-impact & depth indicators (part 3 of 4) (#122)
* feat: effective spread microstructure indicator (part 3 of 4) * feat: realized spread microstructure indicator (part 3 of 4) * feat: kyle's lambda microstructure indicator (part 3 of 4) * feat: depth slope microstructure indicator (part 3 of 4) |
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kingchenc
|
5867f71450 |
feat: trade-flow microstructure indicators (part 2 of 4) (#113)
* feat(core): add 3 trade-flow microstructure indicators SignedVolume (per-trade size signed by aggressor), CumulativeVolumeDelta (running signed-volume total), and TradeImbalance (rolling buy/sell volume imbalance over a trade window). All consume the Trade type, with full unit coverage. Extends the Microstructure family. * feat(bindings): expose trade-flow microstructure indicators Python, Node and WASM bindings for SignedVolume, CumulativeVolumeDelta and TradeImbalance. Each takes a trade via update(price, size, is_buy); Python and Node expose a batch over three parallel arrays, WASM exposes per-trade update. Regenerates node index.d.ts/.js. * test(bindings,fuzz,bench): cover trade-flow microstructure indicators Python and Node: reference values, streaming-vs-batch, lifecycle/repr and input validation (zero window, negative size, non-positive price, mismatched batch lengths). New indicator_update_trade fuzz target. Synthetic trade-tape benches (signed_volume cheapest, trade_imbalance windowed/expensive). * docs: add trade-flow indicators + bump counter to 227 README Microstructure family row gains signed volume / CVD / trade imbalance and the counter goes 224 -> 227; CHANGELOG records the trade-flow indicators. |
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kingchenc
|
2be21df803 |
feat: order-book microstructure indicators (part 1 of 4) (#112)
* feat(core): add microstructure input types (OrderBook, Trade, TradeQuote) New non-OHLCV value types for the order-book / trade-flow indicator family: Level, OrderBook (sorted, uncrossed depth snapshot), Side, Trade (with aggressor side), and TradeQuote (trade paired with prevailing mid). Each has a validating constructor plus a new_unchecked hot-path constructor, with full unit coverage. Adds InvalidOrderBook / InvalidTrade error variants. * feat(core): add 5 order-book microstructure indicators OrderBookImbalanceTop1/TopN/Full (signed depth imbalance), Microprice (size-weighted fair value), and QuotedSpread (top-of-book spread in bps). All consume the OrderBook snapshot type, emit f64, are stateless and ready after the first snapshot, with full unit coverage. Registers a new Microstructure family in the taxonomy. * feat(bindings): expose order-book microstructure indicators Python, Node, and WASM bindings for OrderBookImbalanceTop1/TopN/Full, Microprice and QuotedSpread. Each takes a depth snapshot via four equal-length (bid_px, bid_sz, ask_px, ask_sz) arrays. Python and Node expose a batch over a list of snapshots; WASM exposes per-snapshot update (the streaming model that fits a browser book feed). Regenerates node index.d.ts/.js and registers the new InvalidOrderBook/InvalidTrade arms in the Python error mapping. * test(bindings,fuzz): cover order-book microstructure indicators Python: smoke, reference values, streaming-vs-batch, lifecycle/repr and input validation (mismatched lengths, crossed book, misordered levels, zero levels) for all five order-book indicators. Node: reference values, streaming-vs-batch, and rejection cases. Adds an indicator_update_orderbook fuzz target driving every order-book indicator over arbitrary (incl. degenerate) snapshots. * bench(microstructure): synthetic order-book benchmarks Add a bench_orderbook_input harness and synthesise a five-level book around each candle close (no order-book dataset ships with the repo). Benches the cheapest (top-of-book imbalance) and most-expensive (full-depth imbalance) plus microprice, matching the curated cheapest/expensive-per-family approach. * docs: add Microstructure family + bump indicator counter to 224 README gains the Microstructure family row (order-book imbalance, microprice, quoted spread) and the indicator counter goes 219 -> 224 across seventeen families; CHANGELOG records the new order-book indicators and value types. |
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kingchenc
|
0b85142ad1 |
feat: cross-asset / pairwise indicators (5 new) (#109)
* feat(core): add PairwiseBeta cross-asset indicator
Rolling OLS slope of one asset's log-returns on another's. Unlike Beta,
which regresses the raw inputs it is fed, PairwiseBeta differences
consecutive prices into log-returns internally -- the conventional way to
measure cross-asset beta, where a beta on price levels would be dominated
by the shared trend.
Two-series Indicator<Input = (f64, f64)>, exposed in Rust, Python, Node
and WASM, with unit/known-value/streaming tests and a pair fuzz target.
* feat(core): add PairSpreadZScore cross-asset indicator
Standardised log-spread ln(a) - beta*ln(b) of a pair, where beta is a
rolling-OLS hedge ratio and the spread is z-scored over its own look-back.
The canonical mean-reversion / statistical-arbitrage entry signal, with
independent beta_period and z_period windows.
Two-series Indicator<Input = (f64, f64)>, exposed in Rust, Python, Node
and WASM, with sign/known-value/streaming tests and a pair fuzz target.
* feat(core): add LeadLagCrossCorrelation cross-asset indicator
Reports the integer offset k in [-max_lag, max_lag] that maximises
|corr(a[t], b[t+k])|, answering which of two assets leads the other and by
how many bars. A positive lag means a leads b. Fully causal: a's window is
held centred while b's window slides across the buffered history, so every
lag is evaluated only against data already seen.
Struct output { lag, correlation }, exposed in Rust, Python, Node and WASM
with lead-detection/streaming tests and a pair fuzz driver.
* feat(core): add Cointegration (Engle-Granger + ADF) indicator
Rolling pairs-trading screen: an OLS hedge ratio of a on b, the spread
(residual) a - (alpha + beta*b), and an augmented Dickey-Fuller t-statistic
on the spread with configurable lags. A strongly negative statistic flags a
mean-reverting, tradeable spread. Includes a small Gaussian-elimination
solver for the augmented regression.
Struct output { hedge_ratio, spread, adf_stat }, exposed in Rust, Python,
Node and WASM with stationarity/hedge-ratio/streaming tests and a pair fuzz
driver.
* feat(core): add RelativeStrengthAB cross-asset indicator
Comparative relative strength of two assets: the ratio line a/b together
with its moving average and its RSI, the classic asset-vs-asset /
asset-vs-index rotation screen. Composes the existing Sma and Rsi over the
ratio; a zero denominator or non-finite price is skipped.
Struct output { ratio, ratio_ma, ratio_rsi }, exposed in Rust, Python, Node
and WASM with flat/rising-ratio/streaming tests and a pair fuzz driver.
* test(cointegration): cover ADF guard branches
The ADF helper's short-series and degrees-of-freedom guards and the
zero-dispersion (perfect AR) path are unreachable through the public
Cointegration API (period >= 2*adf_lags + 4), so exercise them with direct
unit tests on adf_no_constant. The second linear solve cannot be singular
once the coefficient solve on the same matrix has succeeded, so it now uses
expect() instead of a dead error branch.
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kingchenc
|
4e3c41ea80 |
feat(family-15): add 17 risk/performance metrics (#54)
* feat(family-15): add 17 risk/performance metrics Implements Family 15 pragmatically as standard `Indicator`s instead of a separate `wickra-metrics` crate. Input is scalar `f64` per bar — period return, equity sample, or per-trade P&L depending on the metric. Scalar `Indicator<f64>` (14): - SharpeRatio(period, risk_free) - SortinoRatio(period, mar) - CalmarRatio(period) - OmegaRatio(period, threshold) - MaxDrawdown(period) — rolling, peak-to-trough - AverageDrawdown(period) - DrawdownDuration — cumulative, bars under water (u32 output) - PainIndex(period) - ValueAtRisk(period, confidence) - ConditionalValueAtRisk(period, confidence) - ProfitFactor(period) - GainLossRatio(period) - RecoveryFactor — cumulative, net return / max drawdown - KellyCriterion(period) Two-series `Indicator<(f64, f64)>` for (asset, benchmark) returns (3): - TreynorRatio(period, risk_free) - InformationRatio(period) - Alpha(period, risk_free) — Jensen / CAPM Touchpoints: - 17 new files under `crates/wickra-core/src/indicators/`. - `mod.rs` + `lib.rs` re-exports. - Python bindings (`bindings/python/src/lib.rs`, `__init__.py`). - Node bindings (`bindings/node/src/lib.rs`, `index.js`). - WASM bindings (`bindings/wasm/src/lib.rs`). - Fuzz: scalar metrics appended to `indicator_update.rs`; new `indicator_update_pair.rs` fuzz target for `(f64, f64)` indicators. - Python tests: SCALAR + new PAIR parameter lists in `test_new_indicators.py`, reference-value cases in `test_known_values.py`. - Node tests: scalar factories + new pair-factory block in `bindings/node/__tests__/indicators.test.js`. - Benches: 5 Family-15 benches added in `crates/wickra/benches/indicators.rs`. - Docs: README family-table row + counter (71 -> 88), CHANGELOG entry under [Unreleased]. Note: Family 12 (statistik-regression, PR #51) introduces `node_pair_indicator!` and `wasm_pair_indicator!` macros for Pearson / Beta / Spearman. Family 15 needs the same pair-input pattern but Family 12 is not yet in main, so the three pair wrappers below are written by hand in this PR. When PR #51 lands, the trivial merge-conflict is resolved by keeping the macros from Family 12 and re-using them for Treynor / IR / Alpha (drop the three handwritten wrappers). cargo check --workspace --all-features: green. * fix(family-15): satisfy clippy doc_markdown / if_not_else / digit_grouping * fix(family-15): unused TreynorRatio import, duplicate pairFactories, _eq_nan inf handling * fix(family-15): node eq() handles matching infinities for ratio indicators * test(family-15): cover cold paths flagged by codecov patch |
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kingchenc
|
55284a3042 |
feat(family-14): add 15 candlestick patterns (#53)
* feat(family-14): add 15 candlestick patterns Introduces the Candlestick Patterns family (block A of the family-14 spec) as scalar f64 indicators on Candle inputs. Each detector emits +1.0 for a bullish reading, -1.0 for a bearish reading, and 0.0 when no pattern is present. Doji is direction-less and emits +1.0 / 0.0 only. New indicators (15): - Doji - Hammer - InvertedHammer - HangingMan - ShootingStar - Engulfing - Harami - MorningEveningStar (signed: +1.0 morning star, -1.0 evening star) - ThreeSoldiersOrCrows (signed: +1.0 soldiers, -1.0 crows) - PiercingDarkCloud (signed: +1.0 piercing, -1.0 dark cloud) - Marubozu (signed: +1.0 bullish, -1.0 bearish, 5 percent shadow tolerance default) - Tweezer (signed: +1.0 bottom, -1.0 top, 10 bps relative tolerance default) - SpinningTop (direction-signed indecision) - ThreeInside (confirmed Harami) - ThreeOutside (confirmed Engulfing) MVP scope notes: - Pattern-shape check only, no trend filter applied. Caller combines with a trend indicator for actionable signals. Documented in every doc comment. - Block B (Harmonic patterns) and block C (Chart patterns) remain out-of-scope and will follow when the pattern-detection framework (pivot detector, multi-bar state machines) lands. Touched across all bindings: Python, Node, WASM. Fuzz target, Python tests (streaming-vs-batch + reference values), Node tests (streaming-vs-batch + reference values), and a representative bench subset (1-, 2- and 3-bar patterns) added. README family table + indicator counter (71 -> 86, eight -> nine families) and CHANGELOG [Unreleased] updated. * fix(family-14): unpack MULTI values with *_ to handle 3-element tuples * cov(family-14): cover Default impl cold paths and MorningEveningStar guard branches |
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kingchenc
|
9b8e1346ed |
feat(family-16): add ValueArea + InitialBalance + OpeningRange (#52)
* feat(family-16): add ValueArea + InitialBalance + OpeningRange Opens family #16 (Market Profile) with the three OHLCV-compatible scalar / multi-output indicators: - ValueArea(period, bin_count, value_area_pct) -> {poc, vah, val}. Rolling bin-approximation volume profile over the last `period` candles. Each candle's volume is spread uniformly across [low, high]; POC is the bin with highest cumulative volume; the value area expands symmetrically from POC and always absorbs the higher-volume neighbour next, until `value_area_pct` (default 0.70) of total volume is enclosed. Defaults (20, 50, 0.70). - InitialBalance(period) -> {high, low}. Tracks session-opening high and low over the first `period` bars, then locks. Default period = 12 (one-hour IB on 5-minute bars for US equities). Callers MUST invoke reset() at every session boundary, otherwise IB stays fixed for the lifetime of the instance. - OpeningRange(period) -> {high, low, breakout_distance}. Same lock-after-N-bars semantics as IB with a shorter default period (6 = 30 min on 5-minute bars) and a third output that tracks close - or_mid (positive above the range mid, negative below). Histogram-output Market Profile variants (Volume Profile, VPVR, Composite Profile) are deferred because they need a new histogram output API layer rather than fixed-arity scalars. Tick-data-only variants (TPO Profile, Single Print, Order Flow Delta, Cumulative Delta, Volume-Weighted Open) are out of scope because `wickra-data` does not currently expose tick / L2 data. All four bindings (Rust core, Python, Node, WASM) ship the new indicators with parity tests; benches added; fuzz target extended. Counter 71 -> 74 across 8 -> 9 families. cargo check --workspace --all-features green. * fix(family-16): cover cold paths in InitialBalance + ValueArea InitialBalance::value() public getter had no test covering the post-update Some(...) branch — extended accessors_and_metadata to call value() after one update. ValueArea single-print bar path (c.high == c.low) was unreachable in existing tests since the only single-print test used a uniform 100-price window which exits early via the span == 0 guard; added a mixed-window test that triggers the c.high <= c.low branch directly. The (None, None) arm of the expansion match was by-construction unreachable (the loop condition already requires at least one neighbour) and has been folded into an if/else. |
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kingchenc
|
05fcdd9a5e |
feat(family-12): add 13 Statistik/Regression indicators (#51)
* feat(family-12): add 13 Statistik/Regression indicators Brings the Price Statistics family to 20 indicators (7 → 20) and the total catalogue to 84 (71 → 84). Every indicator ships in the Rust core plus Python, Node, and WASM bindings with full streaming ↔ batch parity, fuzz coverage, and benches. Scalar (f64 → f64): - Variance, CoefficientOfVariation: rolling population variance and its dimensionless ratio with the mean. O(1) updates. - Skewness, Kurtosis: rolling Pearson skewness and excess kurtosis, derived from running sums of x, x², x³, x⁴ via the binomial identities — also O(1) per bar. - StandardError, DetrendedStdDev: standard error of estimate (n − 2) and population StdDev (n) of OLS residuals, sharing the LinReg O(1) sliding sums. - RSquared: coefficient of determination of the rolling OLS fit; the trend-quality filter, clamped to [0, 1]. - MedianAbsoluteDeviation: robust dispersion estimator; O(period log period) per emission via two in-place sorts of a reusable scratch buffer. - Autocorrelation(period, lag): rolling lag-k Pearson autocorrelation. - HurstExponent(period, chunks): R/S-analysis trend-persistence estimator clamped to [0, 1]. Pair indicators (Input = (f64, f64)): - PearsonCorrelation: rolling cross-series Pearson, O(1). - Beta: rolling OLS slope of asset vs. benchmark (CAPM). - SpearmanCorrelation: rolling rank correlation with mid-rank tie handling; O(period log period). Touchpoints: - crates/wickra-core: 13 new indicator modules + mod.rs / lib.rs re-exports. - bindings/python: pyclasses + add_class registration + __init__.py import & __all__ updates. The pair indicators expose update(x, y) and batch(x, y) over two equally-sized numpy arrays. - bindings/node: scalar indicators via node_scalar_indicator! macro; pair indicators via new node_pair_indicator! macro; explicit structs for Autocorrelation and HurstExponent (two-arg ctors). index.js extended with the new exports. - bindings/wasm: scalar wrappers via wasm_scalar_indicator!; pair wrappers via new wasm_pair_indicator! macro. - fuzz: every scalar drove through the generic helper; pair indicators stress-tested by pairing adjacent samples of the fuzz input. - Python tests (test_new_indicators.py): added to SCALAR parametrisation, plus algebraic reference values (variance of [2,4,6] = 8/3, MAD ignoring outlier = 0, monotone non-linear Spearman = 1, two-to-one Beta = 2, etc.) and a streaming-vs-batch test for the pair indicators. - Node tests (indicators.test.js): extended the scalar factories map and added a pair-indicator section with the same algebraic reference values. - crates/wickra/benches: bench_scalar entries for all 10 single- input new indicators. - README: counter 71 → 84; Price Statistics family-table row expanded with the 13 new indicators. - CHANGELOG: Unreleased section documents the family addition. Wiki drafts (ghost-ignored, manual sync to wickra.wiki at release time): indicator-ideas/families/wiki/family-12-statistik-regression/ contains 13 deep-dive pages plus _Sidebar / Indicators-Overview / Warmup-Periods / Home fragments for the curator merge. cargo check --workspace --all-features: clean. * fix(family-12): remove unreachable defensive guards in hurst_exponent The three guards (m < 2 continue, end > buf.len() break, denom == 0.0 return) are by-construction unreachable given the constructor invariant period >= 2 * chunks: m = period / k for k in 1..=chunks always satisfies m >= 2 and end = (c+1) * m <= k * m <= period = buf.len(), and m_1 = period and m_2 = period / 2 are always distinct so the slope denominator is strictly positive. Removing them brings codecov/patch back to 100%. |
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kingchenc
|
5aa0949bce |
feat(family-13): add Ichimoku + Heikin-Ashi (#50)
Two new indicators in a brand-new "Ichimoku & alternative charts" family: - `Ichimoku` (Ichimoku Kinko Hyo): the full five-line cloud system (Tenkan-sen, Kijun-sen, Senkou Span A/B, Chikou Span). Classic (9, 26, 52, 26) defaults; configurable. Forward displacement is handled in an O(1) ring buffer so the visible Senkou A/B at bar n are the values computed at bar n-displacement. - `HeikinAshi`: recursive candle smoothing transform emitting a four-field synthetic candle. Seeds ha_open from (open+close)/2 on the first bar. Touchpoints: core + unit tests, mod.rs/lib.rs re-exports, Python + Node + WASM bindings (multi-output via PyArray2 / interleaved Vec<f64> / Object+Float64Array), Python tests across smoke/new-indicators/ input-validation, Node parity tests, fuzz target (Candle), benches, README family table + counter (71 -> 73, 8 -> 9 families), CHANGELOG. Note: Renko, Kagi, and Point & Figure from the family-13 ideas list are intentionally skipped. They are bar generators (the bar boundary is defined by price moves, not by a fixed time interval) rather than indicators that consume a candle stream, and belong in wickra-data as candle/tick transforms alongside the existing tick-to-candle aggregator and resampler. |
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kingchenc
|
7a18a26daf |
feat(family-10): add 16 Ehlers / Cycle (DSP) indicators (#49)
Implements Family 10 (Ehlers / Cycle) end-to-end across Rust core,
Python / Node / WASM bindings, fuzz, tests, benches and docs. This
is an entirely new family covering John Ehlers' digital-signal-
processing school of cycle analytics — a strong differentiator
versus TA-Lib and pandas-ta, which ship only fragments.
Indicators:
- MAMA (Mesa Adaptive MA) — multi-output { mama, fama }
- FAMA (Following Adaptive MA) — scalar wrapper around MAMA's slow line
- Fisher Transform — Gaussian-normalising price transform
- Inverse Fisher Transform — bounded oscillator (tanh-based)
- SuperSmoother — 2-pole Butterworth lowpass
- Roofing Filter — high-pass + SuperSmoother bandpass
- Decycler — price minus 2-pole high-pass (lag-free trend)
- Decycler Oscillator — fast / slow Decycler difference (MACD-like)
- Hilbert Dominant Cycle — phase-derived period estimator [6, 50]
- Sine Wave Indicator — sin(phase) with 45° lead companion
- Adaptive Cycle Indicator — half-period driver for adaptive oscillators
- Center of Gravity Oscillator — weighted-mass momentum
- Cybernetic Cycle Component — EasyLanguage classic
- Empirical Mode Decomposition — bandpass + envelope mean
- Ehlers Stochastic — Stochastic on Roofing Filter input, [-1, +1]
- Instantaneous Trendline — Ehlers 2-pole lag-free trend
Indicator count rises 71 -> 87 across nine families (was eight).
All sixteen pass batch == streaming equivalence, expose the standard
Indicator surface (update / batch / reset / is_ready / warmup_period
/ name), are fuzz-tested, benchmarked against the checked-in BTCUSDT
1-minute dataset and reach across all four bindings.
Wiki deep-dive drafts for every indicator + Sidebar / Overview /
Home / Warmup updates are staged under indicator-ideas/families/
wiki/family-10-ehlers-cycle/ in the main repo (ghost-ignored) for
the maintainer to publish to the wiki repo manually.
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|
kingchenc
|
4f9ed34884 |
feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure) (#48)
* feat(family-11): add DeMark suite (TD Setup, Sequential, DeMarker, REI, Pressure)
Family 11 (DeMark) was previously empty; this PR adds five
streaming-first DeMark indicators in one batch.
- **TD Setup** (`TdSetup`): parameterised buy/sell setup counter.
Counts consecutive bars whose close is less-than (buy) or
greater-than (sell) the close `lookback` bars earlier, saturating
at `target`. Emits a signed `f64` so callers read direction from
the sign and run length from the magnitude. Classic config:
`lookback = 4`, `target = 9`.
- **TD Sequential** (`TdSequential`): the canonical Setup + Countdown
exhaustion pattern. Output struct `{ setup, countdown, direction }`
exposes both phase counts as signed numbers plus the active
countdown direction (+1 buy / -1 sell / 0 none). Countdown
activates when a setup completes and tracks the close-vs-high/low
comparison `countdown_lookback` bars back, capped at
`countdown_target`. Classic: 4/9/2/13.
- **TD DeMarker** (`TdDeMarker`): bounded [0, 1] oscillator from the
rolling average of upward high expansion (DeMax) and downward low
expansion (DeMin). Falls back to the neutral 0.5 on a flat market
(denominator zero).
- **TD REI** (`TdRei`): Range Expansion Index, bounded [-100, 100].
Per-bar numerator gated on a range-overlap condition vs the bars
5 and 6 back, normalised by a `period`-bar sum of absolute moves.
Classic period = 5. Saturates at +100 in a slow steady uptrend
and at -100 in the mirror downtrend; emits 0 on a flat market.
- **TD Pressure** (`TdPressure`): volume-weighted buying / selling
pressure normalised to [-100, 100]. Per-bar pressure is the
intra-bar close-vs-open ratio scaled by volume; the output is the
rolling mean divided by the rolling mean volume. Zero-range bars
contribute zero (avoid the undefined ratio) and a flat zero-volume
window falls back to 0.
Bindings: all five exposed in Python (`ta.TDSetup`, `ta.TDSequential`,
`ta.TDDeMarker`, `ta.TDREI`, `ta.TDPressure`), Node (`wickra.TDSetup`
etc.), and WASM. Multi-output classes (`TDSequential`) return either
a struct `{ setup, countdown, direction }` per bar (streaming) or a
flat interleaved Float64Array of length `3 * n` (batch).
Tests: 47 unit tests across the five new core files (pure-trend
saturation, flat-market neutral fallback, batch-equals-streaming,
zero-parameter rejection, reset semantics, accessors). Python
test_new_indicators.py picks up all five plus a multi-output TD
Sequential block. Node indicators.test.js picks up all five.
Reference values added to test_known_values.py.
Fuzz: candle fuzz target sweeps all five DeMark indicators with the
existing `Vec<f64>` -> `Vec<Candle>` driver.
Benches: BTCUSDT 1-minute dataset benches for each DeMark indicator
in `crates/wickra/benches/indicators.rs`.
Docs: README family table gains a "DeMark" row; indicator counter
bumped 71 -> 76. CHANGELOG entry added under [Unreleased]. Wiki
drafts (deep-dive pages + Sidebar / Overview / Warmup-Periods / Home
deltas) live under `indicator-ideas/families/wiki/family-11-demark/`
for manual merge into the wiki repo.
* feat(family-11): add 7 missing DeMark indicators
Complete the DeMark suite (family 11) with the seven indicators not
covered by the first commit: TD Combo, TD Countdown, TD Lines (TDST),
TD Range Projection, TD Differential, TD Open, and TD Risk Level.
- TdCombo: aggressive countdown variant with three strictness rules
on top of the classic close-vs-low/high lookback rule (monotone
low/high, monotone close vs prior bar).
- TdCountdown: standalone 13-bar countdown packaging only the signed
countdown count (the setup machine runs internally).
- TdLines: TDST horizontal support/resistance levels from the
highest-high / lowest-low bars of the most-recently-completed
setup, exposed as a multi-output struct.
- TdRangeProjection: DeMark X-projection of the next bar's high and
low from the current bar's OHLC via an open-vs-close-weighted
pivot (three branches: close<open, close>open, close==open).
- TdDifferential: two-bar buying-pressure vs selling-pressure
reversal pattern emitting +1/-1/0.
- TdOpen: gap-and-fade reversal pattern (open outside prior range
with subsequent recovery into it) emitting +1/-1/0.
- TdRiskLevel: protective stop levels derived from the setup
extreme bar +/- its true range.
All seven are wired through Rust core, Python, Node and WASM
bindings, registered in the candle-stream fuzz target, given
benchmark entries on the BTCUSDT 1-minute dataset, and covered by
streaming-vs-batch equivalence, reference-value, lifecycle and
input-validation tests on the Python and Node sides. README counter
moves 76 -> 83 and the CHANGELOG "family 11" entry is extended to
list all twelve indicators.
* fix(td_risk_level tests): check first emission at idx 12, not last bar
TdRiskLevel re-ratchets the sell-risk level on each subsequent setup
completion, so a strictly rising series produces 22.0 at idx 19 (latest
setup) rather than 15.0 (first setup). The test comment already named
idx 12 as the reference; switch the assertion from out[-1] to out[12]
to match the reference computation.
* test(family-11): cover buy-direction branches in TD indicators
Add downtrend tests to TdSequential, TdCombo and TdCountdown so the
buy-side countdown/combo increment branches are exercised; remove an
empty `if buy_countdown == target {}` block in TdSequential whose
behavior is already enforced by the outer strict `<` guard.
Closes codecov/patch gaps reported on PR #48 (10 missed lines across
the three files).
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kingchenc
|
7e1e988596 |
feat(family-08): Pivots & Support/Resistance (7 indicators) (#47)
* feat(family-08): add Classic, Fibonacci, Camarilla, Woodie and DeMark pivots + Williams Fractals + ZigZag
Seven new indicators land the previously empty Pivots & S/R family
(family 08), each implemented in wickra-core with the full Indicator
trait surface (update / reset / warmup_period / is_ready / name),
exposed across Python (PyO3), Node (napi-rs) and WASM (wasm-bindgen)
with the standard streaming + batch APIs, and covered by Rust unit
tests, Python streaming-vs-batch + reference-value tests, Node
streaming-vs-batch tests, the candle-input fuzz target and Rust
microbenchmarks.
- ClassicPivots (7 levels): PP = (H+L+C)/3, three R/S tiers per the
floor-trader formulas.
- FibonacciPivots (7 levels): PP plus R/S spaced by 0.382 / 0.618 /
1.000 of the prior range.
- Camarilla (9 levels): Nick Stott's four-tier `C +/- (H - L) * 1.1 /
{12, 6, 4, 2}` levels.
- WoodiePivots (5 levels): close-weighted PP = (H + L + 2*C) / 4 plus
two R/S tiers.
- DemarkPivots (3 levels): conditional X sum based on the previous
bar's open-vs-close relationship.
- WilliamsFractals: five-bar swing detector emitting optional up/down
fractal prices at the centre of each window.
- ZigZag: percent-threshold swing tracker, non-repainting; emits the
just-completed extreme and direction on confirmed reversals only.
README family table updated to nine families / 78 indicators;
CHANGELOG records the family-08 addition under [Unreleased].
* fix(family-08 tests): unify MULTI dict to 3-tuple (factory, batch_call, k)
The HEAD-side family-08 test parametrised MULTI[name] as
`(factory, batch_call, output_arity)` so that pivots with arity 3/5/7/9
fit the same harness. Main's entries arrived as 2-tuples; convert them
all to the 3-tuple shape so `make, batch_call, k = MULTI[name]` unpacks
cleanly. Lifecycle test now indexes the tuple instead of destructuring.
* test(zig_zag): tighten flat-oscillation test (drop dead counter branch)
The previous version of `small_oscillations_yield_no_swings` counted
emitted swings, but the assertion proves the counter never increments
so codecov flagged `emitted += 1` as uncovered. Switch to a per-bar
`assert!(...is_none())` — same coverage of the no-swing path, no dead
branch.
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kingchenc
|
f10b8c2e2d |
feat(family-09): add 7 trailing stops (HiLo, Volty, Yo-Yo, Donchian, Pct, Step, Renko) (#46)
* feat(family-09): add 7 trailing stops (HiLo, Volty, Yo-Yo, Donchian, Pct, Step, Renko)
Rounds out the Trailing Stops family from 5 to 12 indicators:
- HiLoActivator (Crabel): SMA-of-high/SMA-of-low trail with a one-bar
lag; emits the opposite-side SMA as the trailing stop.
- VoltyStop (Cynthia Kase): ATR trail anchored on the extreme close
since the trade was opened — tighter than AtrTrailingStop on
pullbacks.
- YoyoExit: long-only ATR trail with an explicit re-entry trigger at
trail + multiplier*ATR; exposes an in_trade flag.
- DonchianStop (Turtle): lowest low / highest high over the window;
multi-output {stop_long, stop_short}.
- PercentageTrailingStop: fixed-percent trail that scales across
instruments without per-asset tuning.
- StepTrailingStop: snaps to a step_size-aligned grid; mirrors
discretionary stop-by-hand workflow.
- RenkoTrailingStop: block-anchored trail; only moves on full-block
advances, ignores intra-block noise.
All seven are wired into wickra-core, the Python / Node / WASM
bindings, the indicator_update + indicator_update_candle fuzz targets,
the wickra bench harness, and the Python + Node test suites. README
counter bumps from 71 to 78; CHANGELOG entry under [Unreleased].
* fix(family-09): satisfy pedantic clippy lints
- hilo_activator: rewrite match-Some/None as if-let-else (single_match_else),
add backticks around the HiLo identifier in module/struct doc (doc_markdown).
- percentage / step / renko trailing stop tests: use f64::from(i32) instead
of `as f64` (cast_lossless).
- bench `benches()` is now >100 lines after Family 09 was wired in; allow
too_many_lines (matches the python pymodule fn).
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kingchenc
|
880a0e7430 |
feat: Family 07 Volume - 6 new volume-flow indicators (#45)
* feat(kvo): add Klinger Volume Oscillator
Stephen J. Klinger's trend-aware volume-force MACD. Each bar produces a 'volume force' (vf) signed by the local trend (+1 / -1 / carry) and scaled by the ratio of the current accumulation horizon to its previous trend. KVO = EMA(vf, fast) - EMA(vf, slow), classic (34, 55).
Rust core (Kvo) with 7 unit tests (rejects zero / fast>=slow, accessors, constant series collapses to 0, warmup lands at slow+1, batch == streaming, reset clears state), plus Python (PyKvo + KVO export), Node (KvoNode), and WASM (WasmKvo) bindings. Fuzz target adds Kvo to the candle-input sweep, bench adds the candle-input KVO benchmark, README counter 71 -> 72 + family table row, CHANGELOG [Unreleased].
* feat(volume-oscillator): add Volume Oscillator (VO)
Percent difference between a fast and a slow SMA of the bar volume: 100 * (SMA(vol, fast) - SMA(vol, slow)) / SMA(vol, slow). Default (14, 28). The line stays near zero in stable conditions; positive readings show rising short-term participation, negative readings show waning interest.
Rust core (VolumeOscillator) with 8 unit tests (period validation, accessors, constant volume == 0, zero-volume window defensive branch, two reference values verified algebraically, batch == streaming, reset), plus Python (PyVolumeOscillator + VolumeOscillator export), Node (VolumeOscillatorNode), and WASM (WasmVolumeOscillator) bindings. Fuzz target adds VolumeOscillator to the candle-input sweep, bench adds the volume_oscillator benchmark, README counter 72 -> 73 + family table row, CHANGELOG [Unreleased].
* feat(nvi-pvi): add Negative & Positive Volume Index
Paul Dysart's cumulative volume-flow indices, popularised by Norman Fosback in 'Stock Market Logic'. Both run from a 1000.0 baseline and only update on a specific direction of volume change:
- NVI updates on volume-contraction bars (volume_t < volume_{t-1}), absorbing the percent close change. Tracks the 'smart money' leg per Fosback.
- PVI updates on volume-expansion bars (volume_t > volume_{t-1}). Tracks the 'crowd' leg.
Both expose with_baseline(f64) for custom starting indexes. The NVI/PVI pair is listed as a single line in indicator-ideas/families/07-volume.md and shares the same lifecycle/test/binding surface, so they ship as one commit.
Rust core (Nvi, Pvi) with 9 unit tests each (accessors, baseline seed, volume direction branches, zero-prev-close guard, custom baseline, batch == streaming, reset), plus Python (PyNvi/PyPvi + NVI/PVI exports), Node (NviNode/PviNode), and WASM (WasmNvi/WasmPvi) bindings. Fuzz target adds Nvi+Pvi to the candle-input sweep, bench adds nvi+pvi entries, README counter 73 -> 75 + family table row, CHANGELOG [Unreleased].
* feat(family-07): add Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index
Finishes the volume-flow family with the remaining (new) entries from
indicator-ideas/families/07-volume.md.
Indicators added:
- Williams A/D (`WilliamsAD`): Larry Williams' volume-less cumulative
accumulation/distribution line. Anchors each bar's contribution to
the previous close via true-high/true-low (gap-aware).
- Anchored VWAP (`AnchoredVwap`): cumulative VWAP whose accumulation
starts at a user-chosen anchor bar. Exposes `set_anchor()` (queued
to the next `update`) for click-to-anchor workflows. Reset clears
both state and pending-anchor flag.
- Demand Index (`DemandIndex`): James Sibbet's smoothed buying-vs-
selling pressure, in the streaming-friendly textbook form
`EMA(volume * close-return * (1 + range/close), period)`.
- Time Segmented Volume (`Tsv`): Don Worden's rolling window-sum of
`(close_t - close_{t-1}) * volume_t`. Default `period = 18`.
- Volume Zone Oscillator (`Vzo`): Walid Khalil's normalised volume-flow
oscillator bounded in `[-100, +100]`, defined as
`100 * EMA(signed_volume) / EMA(volume)`.
- Market Facilitation Index (`MarketFacilitationIndex`): Bill Williams'
per-bar `(high - low) / volume`. Returns `None` on zero-volume bars.
All six indicators ship with unit tests (`rejects_zero_period` where
applicable, `accessors_and_metadata`, constant-series behaviour,
batch == streaming equivalence, reset semantics, and reference-value
or saturation-extreme tests), Python / Node / WASM bindings, fuzz
coverage in `indicator_update_candle`, a `bench_candle_input` line per
indicator, README + CHANGELOG entries, and Python reference-value
tests in `test_new_indicators.py`.
The README indicator counter advances 75 -> 81.
* test(family-07): cover defensive cold paths + Default impls
- ad_oscillator: exercise `value()` after first emission.
- kvo: cover the `cm == 0.0` zero-OHLC defensive branch.
- nvi / pvi: exercise the Default impls.
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kingchenc
|
6287bd48c1 |
feat: Family 06 Trend-Strength - 5 new directional/random-walk indicators (#44)
* feat(adxr): add Wilder Average Directional Movement Index Rating
ADXR is the trend-strength smoother Wilder published alongside ADX in
*New Concepts in Technical Trading Systems* (1978):
ADXR_t = (ADX_t + ADX_{t - (period - 1)}) / 2
The lookback length is the same period that feeds the underlying ADX.
Because the older ADX is period - 1 bars stale, ADXR responds more
slowly than ADX and is the canonical metric for comparing
trend-strength across instruments.
Implementation reuses the existing wickra_core::Adx engine plus a
period-length ring of past ADX values; warmup is 3 * period - 1
(41 for period = 14). Bindings: Python PyAdxr (PyArray1 batch),
Node AdxrNode (number scalar), WASM WasmAdxr. Fuzz target covers
the candle-input path. Python + Node streaming-vs-batch tests
parametrised, plus a pure-uptrend reference value (ADXR == 100
when ADX saturates at 100). Criterion bench added under crates/
wickra/benches/indicators.rs.
README family table and indicator counter updated (71 -> 72).
* feat(rwi): add Mike Poulos Random Walk Index
RWI compares actual price displacement to what a random walk would
produce over the same horizon: for each lookback i in [2, period],
RWI_High_t(i) = (high_t - low_{t-i+1}) / (ATR_i(t) * sqrt(i))
RWI_Low_t(i) = (high_{t-i+1} - low_t) / (ATR_i(t) * sqrt(i))
Per-bar output is the maximum across lookbacks for each direction;
a reading > 1 means the trend beats random-walk noise, > 2 is the
typical strong-trend threshold. Multi-output (high, low). period
must be >= 2 (the shortest meaningful lookback); period < 2 returns
InvalidPeriod. Warmup = period (e.g. 14 for the standard default).
Bindings: Python PyRwi (PyArray2 shape (n, 2)), Node RwiNode +
RwiValue struct, WASM WasmRwi (Object/Reflect for update,
Float64Array interleaved for batch). Fuzz target adds the candle
input case. Python parametric streaming-vs-batch test and pure
uptrend reference test (RWI_High dominates RWI_Low and exceeds 1).
Node parametric streaming-vs-interleaved-batch test. Criterion
bench under crates/wickra/benches/indicators.rs.
README family table and indicator counter updated (72 -> 73).
* feat(tii): add M.H. Pee Trend Intensity Index
TII is a [0, 100] oscillator that asks 'what fraction of the recent
SMA deviations are positive?'. The construction is
dev_t = close_t - SMA(close, sma_period)_t
SD_pos = sum of positive dev_t over the last dev_period bars
SD_neg = sum of |negative dev_t| over the last dev_period bars
TII = 100 * SD_pos / (SD_pos + SD_neg)
Saturates at 100 on a pure uptrend (every close above the lagging
SMA), at 0 on a pure downtrend, and returns the neutral mid-point 50
on a perfectly flat window. The output is clamped to [0, 100] as
the rolling-sum subtraction loop can accumulate a few ULP of error
on long histories. Canonical Pee parameters (sma_period=60,
dev_period=30) wired as Python defaults; warmup is
sma_period + dev_period - 1 (89 for the defaults).
Bindings: Python PyTii (PyArray1 batch), Node TiiNode (scalar
update + batch), WASM WasmTii via the two-arg wasm_scalar_indicator!
macro. Fuzz target adds the scalar path. Python parametric
streaming-vs-batch test plus pure-uptrend (TII == 100) and
flat-market (TII == 50) reference tests. Node parametric
streaming-vs-batch test. Criterion bench under crates/wickra/
benches/indicators.rs.
README family table and indicator counter updated (73 -> 74).
* feat(kst): add Pring Know Sure Thing oscillator
KST is Martin Pring's long-horizon momentum gauge: four smoothed
rate-of-change components combined with fixed weights (1, 2, 3, 4),
plus an SMA signal line.
RCMA_i = SMA(ROC(close, roc_i), sma_i) for i in 1..=4
KST = 1*RCMA_1 + 2*RCMA_2 + 3*RCMA_3 + 4*RCMA_4
Signal = SMA(KST, signal_period)
Kst::classic() exposes Pring's recommended parameter set
(roc = (10, 15, 20, 30), sma = (10, 10, 10, 15), signal = 9);
warmup = max(roc_i + sma_i) + signal_period - 1 (53 for the classic
parameters). All four parallel branches are fed unconditionally so
they warm in lock-step.
Bindings: Python PyKst (PyArray2 shape (n, 2)) with a KST.classic()
staticmethod, Node KstNode + KstValue with a KST.classic() factory,
WASM WasmKst with both new(...) and classic() constructors plus
Object/Reflect for update and Float64Array for batch. Fuzz target
adds the scalar multi-output path. Python tests gain a new
MULTI_SCALAR section parametric over scalar-input/multi-output
indicators, plus a classic-on-constant-series reference test. Node
tests gain a KST entry in the multi-output section. Criterion
benchmark added under crates/wickra/benches/indicators.rs.
README family table and indicator counter updated (74 -> 75).
* feat(wave-trend): add LazyBear Wave Trend Oscillator
Two-line mean-reverting momentum gauge built from the typical price
and three cascaded EMAs:
ap = (high + low + close) / 3
esa = EMA(ap, channel_period)
d = EMA(|ap - esa|, channel_period)
ci = (ap - esa) / (0.015 * d)
wt1 = EMA(ci, average_period)
wt2 = SMA(wt1, signal_period)
WaveTrend::classic() exposes LazyBear's defaults
(channel = 10, average = 21, signal = 4); warmup is
2 * channel_period + average_period + signal_period - 3 (42 for the
classic defaults). On a perfectly flat market the SMA-seeded EMA
introduces a single-ULP drift between ap and esa, which on a tiny d
would make the ratio explode to -1/0.015 = -66.67; a price-scaled
flat-tolerance guard (d <= 16 * EPSILON * max(|esa|, 1)) collapses
the channel index to 0 in that regime so both lines remain at zero.
Bindings: Python PyWaveTrend (PyArray2 shape (n, 2)) with a
WaveTrend.classic() staticmethod, Node WaveTrendNode + WaveTrendValue
with a WaveTrend.classic() factory, WASM WasmWaveTrend with both
new(...) and classic() constructors. Fuzz target adds the candle
multi-output path (sorted alphabetically). Python parametric
streaming-vs-batch test plus a flat-market reference test. Node
parametric streaming-vs-interleaved-batch test. Criterion bench
under crates/wickra/benches/indicators.rs.
README family table and indicator counter updated (75 -> 76).
* fix(family-06): re-add KST::classic() factory + drop dup fuzz block
Family-06 PR's tests call ta.KST.classic() / wickra.KST.classic() — main's
KST binding shipped without the static factory. Add classic() in Python
(staticmethod) and Node (napi factory); WASM already had it. Also drop the
duplicate Kst::classic().unwrap() block in fuzz/indicator_update.rs that
the merge left behind (main's API no longer returns Result).
* test(rwi): drop dead count==0 guard
The loop `for i in 2..=period` makes `count = tr_end - tr_start = i - 1`
which is always >= 1, so the `if count == 0 { continue; }` branch was
unreachable defensive code that codecov flagged on the family-06 PR.
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|
kingchenc
|
54194a4ff8 |
feat: Family 05 Bands & Channels - 11 new price-envelope indicators (#43)
* feat(bands-channels): add Family 05 with 11 indicators
Eleven price-envelope overlays organised into a new "Bands & Channels"
family, exposed across all four bindings (Rust core, Python, Node, WASM)
plus fuzz/test/bench/docs coverage:
- MaEnvelope - SMA centerline with fixed-percent envelope (the oldest
band overlay still in regular use).
- AccelerationBands (Price Headley) - momentum-biased bands that widen
with the bar's relative range (H - L) / (H + L).
- StarcBands (Stoller Average Range Channel) - SMA(close) +/- k*ATR;
Keltner's SMA-centerline sibling.
- AtrBands - close-anchored envelope of width k*ATR; the standard
volatility-targeting stop/target band.
- HurstChannel - SMA centerline wrapped by the rolling high-low range
(Brian Millard / Hurst-cycle channel).
- LinRegChannel - rolling OLS endpoint +/- k * population stddev of the
residuals; dispersion about the trend rather than the mean.
- StandardErrorBands - regression line +/- k * OLS standard error
(denominator n - 2) for prediction-interval bands.
- DoubleBollinger (Kathy Lien) - two concentric BB envelopes
(typically +/- 1 sigma and +/- 2 sigma) for the zone-partition setup.
- TtmSqueeze (John Carter) - BB-inside-KC squeeze flag paired with a
detrended-close linear-regression momentum reading.
- FractalChaosBands - Bill Williams 5-bar fractal high/low envelope.
- VwapStdDevBands - cumulative VWAP with volume-weighted population
standard deviation bands.
Each indicator ships:
- Core impl with the full Indicator trait, classic() where applicable,
and unit tests (rejects_zero_period / multiplier, accessors, flat
market, monotonic ordering, batch == streaming, reset, plus
algebraically verifiable reference values).
- Python PyO3 binding with multi-column NumPy batch (PyArray2).
- Node napi binding with #[napi(object)] struct + interleaved flat
batch.
- WASM wasm-bindgen binding via Object/Reflect for update +
Float64Array for batch.
- Fuzz coverage in fuzz_targets/indicator_update{,_candle}.rs.
- Python streaming-vs-batch parametric test + reference test.
- Node streaming-vs-interleaved-batch test + reference test.
- Criterion microbench under crates/wickra/benches/indicators.rs.
README family table, README indicator-count line, and CHANGELOG
Unreleased entry updated: indicator total rises from 71 to 82 across
nine families. Wiki pages are updated in a separate commit in the
wickra.wiki repo.
* test(acceleration-bands): cover sum_hl==0 zero-price guard
Exercises line 104 (`0.0` branch of the `sum_hl == 0.0` guard) which
was the last patch-coverage miss on the family-05 PR. `Candle::new`
accepts a fully-zero bar so the branch is reachable in principle —
add a degenerate-candle unit test to hit it.
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||
|
kingchenc
|
3ea0f12b7a |
feat: Family 04 Volatility — RVI / Parkinson / Garman-Klass / Rogers-Satchell / Yang-Zhang (#42)
* feat(rvi): add Relative Volatility Index
Donald Dorsey's RSI-shaped volatility gauge. Partitions the rolling
population standard deviation of close into "up" samples (close rose
since the previous bar) and "down" samples (close fell), Wilder-smooths
each side, and reports 100 * AvgUp / (AvgUp + AvgDown). Output bounded
on [0, 100]; saturates at 100 in pure uptrends, 0 in pure downtrends,
and falls back to 50 on a completely flat series (same undefined-RS
convention as RSI).
Single period parameter (default 10) drives both the stddev window and
the Wilder smoothing constant. First emit lands at index 2*period - 2
(2*period - 1 bars are needed: period to fill the stddev window plus
period - 1 to seed the Wilder averages, overlapping by one bar).
Touchpoints: rvi.rs + mod.rs + lib.rs re-export, PyRvi + __init__.py +
test_new_indicators SCALAR + test_known_values uptrend reference,
RviNode + index.d.ts/index.js + indicators.test.js factory +
reference, WasmRvi via scalar macro, scalar-fuzz target, bench_scalar
entry, README + CHANGELOG.
* feat(parkinson): add Parkinson Volatility
Michael Parkinson's (1980) high-low realised volatility estimator.
Under a driftless Geometric-Brownian-Motion assumption, the extreme
range of a bar carries roughly 5x the variance information of the
close-to-close estimator, so for a given statistical efficiency
Parkinson needs five times fewer samples.
Formula:
sigma^2 = (1 / (4n * ln 2)) * Sum_{i=1..n} (ln(H_i / L_i))^2
out = sqrt(sigma^2) * sqrt(trading_periods) * 100
The output is annualised to a percent in the same style as
HistoricalVolatility (pass `trading_periods = 1` for the raw per-bar
sigma * 100 figure). Two parameters: `period` (default 20) for the
rolling window, `trading_periods` (default 252) for the annualisation
factor. First emit at index `period - 1`.
Touchpoints: parkinson.rs + mod.rs + lib.rs re-export,
PyParkinsonVolatility + __init__.py + test_new_indicators CANDLE_SCALAR
+ test_known_values zero-range reference, ParkinsonVolatilityNode +
index.d.ts/index.js + indicators.test.js factory + reference,
WasmParkinsonVolatility hand-rolled, candle-fuzz target,
bench_candle_input entry, README + CHANGELOG.
* feat(garman-klass): add Garman-Klass Volatility
Garman & Klass (1980) OHLC realised-volatility estimator. Extends
Parkinson's high-low estimator with an open-to-close term, lifting
statistical efficiency from ~5x to ~7.4x relative to close-to-close
stddev under driftless Geometric Brownian Motion.
Formula (per bar):
s_t = 0.5 * (ln(H_t / L_t))^2 - (2*ln(2) - 1) * (ln(C_t / O_t))^2
out = sqrt(max(mean(s_t over `period`), 0)) * sqrt(trading_periods) * 100
The per-bar sample can be marginally negative when the bar has a small
range relative to its open-to-close move; a max(., 0) clamp on the
rolling mean absorbs that and the FP cancellation noise before the
square root.
Still biased on data with meaningful overnight drift -- use Yang-Zhang
when gaps matter. Defaults: `period = 20`, `trading_periods = 252`
(annualised percent, same convention as HistoricalVolatility).
Touchpoints: garman_klass.rs + mod.rs + lib.rs re-export,
PyGarmanKlassVolatility + __init__.py + test_new_indicators
CANDLE_SCALAR + test_known_values zero-movement reference,
GarmanKlassVolatilityNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmGarmanKlassVolatility hand-rolled,
candle-fuzz target, bench_candle_input entry, README + CHANGELOG.
* feat(rogers-satchell): add Rogers-Satchell Volatility
Rogers, Satchell & Yoon (1994) OHLC realised-volatility estimator.
Unlike Garman-Klass, the per-bar sample is exact under arbitrary
Brownian drift -- the drift component cancels algebraically.
Formula (per bar):
s_t = ln(H_t / C_t) * ln(H_t / O_t) + ln(L_t / C_t) * ln(L_t / O_t)
out = sqrt(max(mean(s_t over `period`), 0)) * sqrt(trading_periods) * 100
Each per-bar sample is also non-negative by construction: with
`Candle::new` guaranteeing H >= max(O, L, C) and L <= min(O, H, C), the
four log factors have predictable signs (ln(H/.) >= 0, ln(L/.) <= 0),
so both products contribute >= 0. The max(., 0) clamp on the rolling
mean is only there to absorb FP cancellation.
Defaults: `period = 20`, `trading_periods = 252` (annualised percent,
same convention as HistoricalVolatility / Parkinson / Garman-Klass).
Touchpoints: rogers_satchell.rs + mod.rs + lib.rs re-export,
PyRogersSatchellVolatility + __init__.py + test_new_indicators
CANDLE_SCALAR + test_known_values zero-movement reference,
RogersSatchellVolatilityNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmRogersSatchellVolatility hand-rolled,
candle-fuzz target, bench_candle_input entry, README + CHANGELOG.
* feat(yang-zhang): add Yang-Zhang Volatility
Yang & Zhang (2000) drift- and gap-robust OHLC realised-volatility
estimator. Combines three independent components into a single estimate
with minimum variance:
overnight = sample_var(ln(O_t / C_{t-1})) over n bars (close-to-open)
open_close = sample_var(ln(C_t / O_t)) over n bars
rs = mean(ln(H/C)*ln(H/O) + ln(L/C)*ln(L/O)) over n bars
sigma^2_YZ = overnight + k*open_close + (1-k)*rs
k = 0.34 / (1.34 + (n+1)/(n-1))
out = sqrt(max(sigma^2_YZ, 0)) * sqrt(trading_periods) * 100
The overnight and open-to-close variances use Bessel's correction (the
sample estimator, divisor n-1), same convention as
HistoricalVolatility. The blending factor `k` is the one that
minimises estimator variance under driftless Geometric Brownian Motion
with overnight gaps.
This is the gold-standard OHLC estimator for assets with both
close-to-open gaps and intraday drift: equities, futures, and any
market that does not trade continuously. For pure intraday data (where
O_t == C_{t-1} and the open-to-close return is constant), the
overnight and open-close terms vanish and the estimator collapses to
(1-k) * Rogers-Satchell -- this is the indicator's
intraday_data_collapses_to_rs_only unit test.
Period >= 2 (Bessel correction needs >= 2 samples). First emit at
index `period` (the (period+1)-th bar): one bar seeds prev_close, the
next `period` fill the rolling windows. Defaults: `period = 20`,
`trading_periods = 252`.
Touchpoints: yang_zhang.rs + mod.rs + lib.rs re-export,
PyYangZhangVolatility + __init__.py + test_new_indicators
CANDLE_SCALAR + test_known_values zero-movement reference,
YangZhangVolatilityNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmYangZhangVolatility hand-rolled, candle-fuzz
target, bench_candle_input entry, README + CHANGELOG.
* fix(rvi): rename to RviVolatility to avoid clash with family-02 RVI
Family 02 (PR #40) ships a separate `Rvi` struct for Relative Vigor
Index. The two indicators have nothing to do with each other beyond
sharing the acronym, so disambiguate by giving the volatility one a
longer name everywhere:
- Rust crate: `Rvi` -> `RviVolatility`
- Rust file: `rvi.rs` -> `rvi_volatility.rs`
- Python: `RVI` -> `RVIVolatility`
- Node: `RVI` -> `RVIVolatility`
- WASM: `RVI` -> `RVIVolatility`
Once the two PRs are both merged, callers get `wickra::Rvi` for Vigor
and `wickra::RviVolatility` for Volatility. The shorter `RVI` acronym
stays with the Momentum family per the existing wiki pages and the
implementation that shipped first.
Updates: rvi_volatility.rs (renamed), mod.rs, lib.rs re-export,
bindings/python/src/lib.rs + __init__.py + tests, bindings/node/src/lib.rs
+ index.d.ts + index.js + __tests__, bindings/wasm/src/lib.rs,
fuzz/fuzz_targets/indicator_update.rs, crates/wickra/benches/indicators.rs,
README family-table label, CHANGELOG entry.
* test(volatility): Rename test_rvi -> test_rvi_volatility + drop dead match arms
The Python test test_rvi_pure_uptrend_saturates_at_one_hundred was
calling ta.RVI() expecting the volatility version, but ta.RVI now
means Family 02's Relative Vigor Index (candle input). Renamed to
ta.RVIVolatility to match the binding rename done at merge time.
In all four OHLC volatility tests, the existing `match (r, a) { ...,
_ => panic!() }` arm is dead in passing runs (every aligned pair is
either (None, None) or (Some, Some)). Codecov flagged it as a patch
miss on each of parkinson / garman_klass / rogers_satchell /
yang_zhang. Refactored per CLAUDE.md cold-path guidance to
`assert_eq!(r.is_some(), a.is_some()); if let (Some, Some) ...`.
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