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wickra/bindings/node/index.js
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kingchenc 466faddd87 feat: Family 01 Moving Averages — ALMA / McGinley / FRAMA / VIDYA / JMA / Alligator / EVWMA (#39) 
* feat(alma): add Arnaud Legoux Moving Average

Gaussian-weighted moving average with configurable centre (offset in
[0, 1]) and kernel width (sigma > 0). Pre-computes normalised weights
at construction so each update is a single rolling window dot product.

Reference: Arnaud Legoux and Dimitrios Kouzis-Loukas, 2009.

Touchpoints:
- crates/wickra-core: alma.rs + mod.rs + lib.rs re-export
- bindings/python: PyAlma + __init__.py + test_new_indicators +
  test_known_values reference
- bindings/node: AlmaNode + index.d.ts/index.js + indicators.test.js
  factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers ALMA(9, 0.85, 6.0)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry

* feat(mcginley): add McGinley Dynamic moving average

John McGinley's self-adjusting moving average with the recurrence
MD + (price - MD) / (0.6 * period * (price / MD)^4). Speeds up when
price falls below the indicator and damps when price runs above the
indicator. Seeded with the simple average of the first period inputs.

Reference: McGinley, Technical Analysis of Stocks & Commodities, 1990.

Touchpoints:
- crates/wickra-core: mcginley_dynamic.rs + mod.rs + lib.rs re-export
- bindings/python: PyMcGinleyDynamic + __init__.py + test_new_indicators
  + test_known_values reference
- bindings/node: McGinleyDynamicNode (scalar macro) + index.d.ts/index.js
  + indicators.test.js factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers McGinleyDynamic(10)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry

* feat(frama): add Fractal Adaptive Moving Average

Ehlers' FRAMA adapts its smoothing constant to the fractal dimension of
the recent window: tight tracking in trends, heavy smoothing in chop.
Uses the close-only variant where max/min over each window half drive
the dimension estimate. Period must be even (default 16).

Reference: Ehlers, Fractal Adaptive Moving Average, 2005.

Touchpoints:
- crates/wickra-core: frama.rs + mod.rs + lib.rs re-export
- bindings/python: PyFrama + __init__.py + test_new_indicators +
  test_known_values reference (constant series + uptrend tracking)
- bindings/node: FramaNode (scalar macro) + index.d.ts/index.js +
  indicators.test.js factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers Frama(16)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry

* feat(vidya): add Variable Index Dynamic Average

Chande's VIDYA — an EMA whose alpha scales with |CMO(cmo_period)| / 100.
Strong directional momentum lifts the smoothing constant toward the
EMA-of-period rate; flat or choppy windows shrink it toward zero so
VIDYA coasts on its previous value. Two parameters: period (14) and
cmo_period (9). Reuses the existing wickra-core Cmo internally.

Reference: Chande, Stocks & Commodities, 1992.

Also fixes a silent gap from d37fbd1 (feat(frama)): the PyFrama Python
class wrapper and its add_class registration were dropped because the
two edits hit "File has not been read yet" errors that scrolled past
in a batch. Adds them here alongside VIDYA's bindings.

Touchpoints (VIDYA): vidya.rs + mod.rs + lib.rs re-export, PyVidya +
__init__.py + test_new_indicators + test_known_values reference,
VidyaNode (manual two-param binding) + index.d.ts/index.js +
indicators.test.js factory + reference, wasm_scalar_indicator! macro,
fuzz target, bench, README + CHANGELOG.

* feat(jma): add Jurik Moving Average

Three-stage filter reconstruction of Mark Jurik's adaptive MA (the
algorithm is proprietary; this is the form used by most open-source
ports since the 1999 TASC article). Parameters: period (14), phase in
[-100, 100] (0), power in 1..=4 (2). State is seeded by setting
e0 = JMA = first input so a constant input stream is reproduced exactly.

Touchpoints: jma.rs + mod.rs + lib.rs re-export, PyJma + __init__.py +
test_new_indicators + test_known_values reference, JmaNode (manual
three-param binding) + index.d.ts/index.js + indicators.test.js factory
+ reference, wasm_scalar_indicator! macro, fuzz target, bench, README +
CHANGELOG.

* feat(alligator): add Bill Williams Alligator

Three SMMA lines (Jaw / Teeth / Lips) over the median price
(high + low) / 2 with default periods 13 / 8 / 5. Multi-output
indicator returning AlligatorOutput { jaw, teeth, lips }. The
original chart variant shifts each line forward for display; we
publish the unshifted SMMA values and leave the visual shift to
the consumer.

Reference: Bill Williams, Trading Chaos, 1995.

Touchpoints: alligator.rs + mod.rs + lib.rs re-export, PyAlligator
(Candle input, returns 3-tuple, ndarray (n, 3) batch) + __init__.py
+ test_new_indicators + test_known_values reference, AlligatorNode +
AlligatorValue + index.d.ts/index.js + indicators.test.js multi
factory + reference, WasmAlligator (manual JsValue object) +
candle-fuzz target + README + CHANGELOG.

* feat(evwma): add Elastic Volume-Weighted Moving Average

Christian P. Fries' elastic recurrence where the smoothing weight is the
bar's volume relative to the running window total:

  V_sum_t = sum of volumes over the last period candles
  EVWMA_t = ((V_sum_t - v_t) * EVWMA_{t-1} + v_t * close_t) / V_sum_t

A bar whose volume is small barely moves the average; a bar that
dominates the window pulls it strongly toward that bar's close. Seeded
with the close of the first full window; holds its previous value if
the entire window has zero volume.

Reference: Fries, Wilmott Magazine, 2001.

Touchpoints: evwma.rs + mod.rs + lib.rs re-export, PyEvwma (close +
volume batch) + __init__.py + test_new_indicators CANDLE_SCALAR +
test_known_values reference, EvwmaNode + index.d.ts/index.js +
indicators.test.js candleScalar factory + reference, WasmEvwma,
candle-fuzz target + README + CHANGELOG.

* ci: Force local wheel install in Python jobs

Use --no-index --no-deps so the Python matrix installs the freshly
built wheel from dist/ and never falls back to PyPI. Previously pip
sometimes picked the released 0.2.x wheel on macOS / Windows when its
platform tag was a wider match than the local build, which made the
job test the released package and miss any new symbols added in the
PR (e.g. AttributeError: module 'wickra' has no attribute 'ALMA').
numpy is already installed by the preceding pip step, so --no-deps
is safe.
2026-05-25 15:01:14 +02:00

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const { version, SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA, MOM, CMO, DPO, StdDev, UlcerIndex, VerticalHorizontalFilter, ZScore, MACD, BollingerBands, ATR, Stochastic, OBV, ADX, CCI, WilliamsR, MFI, PSAR, Keltner, Donchian, VWAP, RollingVWAP, AwesomeOscillator, Aroon, KAMA, ALMA, McGinleyDynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA, T3, TSI, PMO, ADL, VolumePriceTrend, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex, EaseOfMovement, SuperTrend, ChandelierExit, ChandeKrollStop, AtrTrailingStop, TypicalPrice, MedianPrice, WeightedClose, LinearRegression, LinRegSlope, AcceleratorOscillator, BalanceOfPower, ChoppinessIndex, TrueRange, ChaikinVolatility, LinRegAngle, BollingerBandwidth, PercentB, NATR, HistoricalVolatility, AroonOscillator, Vortex, MassIndex, StochRSI, UltimateOscillator, PPO, Coppock, VWMA } = nativeBinding
module.exports.version = version
module.exports.SMA = SMA
module.exports.EMA = EMA
module.exports.WMA = WMA
module.exports.RSI = RSI
module.exports.DEMA = DEMA
module.exports.TEMA = TEMA
module.exports.HMA = HMA
module.exports.ROC = ROC
module.exports.TRIX = TRIX
module.exports.SMMA = SMMA
module.exports.TRIMA = TRIMA
module.exports.ZLEMA = ZLEMA
module.exports.MOM = MOM
module.exports.CMO = CMO
module.exports.DPO = DPO
module.exports.StdDev = StdDev
module.exports.UlcerIndex = UlcerIndex
module.exports.VerticalHorizontalFilter = VerticalHorizontalFilter
module.exports.ZScore = ZScore
module.exports.MACD = MACD
module.exports.BollingerBands = BollingerBands
module.exports.ATR = ATR
module.exports.Stochastic = Stochastic
module.exports.OBV = OBV
module.exports.ADX = ADX
module.exports.CCI = CCI
module.exports.WilliamsR = WilliamsR
module.exports.MFI = MFI
module.exports.PSAR = PSAR
module.exports.Keltner = Keltner
module.exports.Donchian = Donchian
module.exports.VWAP = VWAP
module.exports.RollingVWAP = RollingVWAP
module.exports.AwesomeOscillator = AwesomeOscillator
module.exports.Aroon = Aroon
module.exports.KAMA = KAMA
module.exports.ALMA = ALMA
module.exports.McGinleyDynamic = McGinleyDynamic
module.exports.FRAMA = FRAMA
module.exports.VIDYA = VIDYA
module.exports.JMA = JMA
module.exports.Alligator = Alligator
module.exports.EVWMA = EVWMA
module.exports.T3 = T3
module.exports.TSI = TSI
module.exports.PMO = PMO
module.exports.ADL = ADL
module.exports.VolumePriceTrend = VolumePriceTrend
module.exports.ChaikinMoneyFlow = ChaikinMoneyFlow
module.exports.ChaikinOscillator = ChaikinOscillator
module.exports.ForceIndex = ForceIndex
module.exports.EaseOfMovement = EaseOfMovement
module.exports.SuperTrend = SuperTrend
module.exports.ChandelierExit = ChandelierExit
module.exports.ChandeKrollStop = ChandeKrollStop
module.exports.AtrTrailingStop = AtrTrailingStop
module.exports.TypicalPrice = TypicalPrice
module.exports.MedianPrice = MedianPrice
module.exports.WeightedClose = WeightedClose
module.exports.LinearRegression = LinearRegression
module.exports.LinRegSlope = LinRegSlope
module.exports.AcceleratorOscillator = AcceleratorOscillator
module.exports.BalanceOfPower = BalanceOfPower
module.exports.ChoppinessIndex = ChoppinessIndex
module.exports.TrueRange = TrueRange
module.exports.ChaikinVolatility = ChaikinVolatility
module.exports.LinRegAngle = LinRegAngle
module.exports.BollingerBandwidth = BollingerBandwidth
module.exports.PercentB = PercentB
module.exports.NATR = NATR
module.exports.HistoricalVolatility = HistoricalVolatility
module.exports.AroonOscillator = AroonOscillator
module.exports.Vortex = Vortex
module.exports.MassIndex = MassIndex
module.exports.StochRSI = StochRSI
module.exports.UltimateOscillator = UltimateOscillator
module.exports.PPO = PPO
module.exports.Coppock = Coppock
module.exports.VWMA = VWMA
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