kingchenc
183ebec7ba
R13 — `HistoricalVolatility::update` previously substituted `0.0` for
the log-return whenever `prev <= 0` or `input <= 0`. The log-return is
undefined there, and silently treating bad ticks as "no movement"
underreports realised volatility on broken data feeds. The fix skips
non-positive prices entirely: `self.last` is returned, state is left
untouched, and the next real tick re-anchors against the previous
*valid* `prev_price`. This matches how every other indicator handles
invalid inputs (SMA / EMA / ROC / Bollinger).
A new test `skips_non_positive_prices` proves the invariant: after a
warmed-up indicator, two consecutive bad ticks (`-5.0` and `0.0`) must
return the baseline value, and a subsequent real positive tick must
produce the same output as a control indicator that simply never saw
the bad ticks.
R14 — `Tick::new` previously returned `Error::InvalidCandle` for
negative volume. A tick is not a candle; downstream tick-stream
pipelines should be able to match on a semantically-correct error. A
new `Error::InvalidTick { message }` variant is added; the existing
test is updated to assert against it. Python's `map_err` is extended
to forward the new variant as `PyValueError`; the Node and WASM
bindings format via `Error::to_string()` and pick the new variant up
automatically without source changes.
Wickra — Python bindings
Streaming-first technical indicators powered by a Rust core.
pip install wickra
Quick start
import numpy as np
import wickra as ta
# Batch — TA-Lib-style usage
prices = np.linspace(100, 200, 1000)
rsi = ta.RSI(14).batch(prices) # NumPy array; NaN during warmup
# Streaming — feed ticks one at a time
rsi = ta.RSI(14)
for price in live_prices:
v = rsi.update(price) # O(1) per tick
if v is not None and v > 70:
...
What's included
71 streaming-first indicators across eight families. Every one passes a
batch == streaming equivalence test and reference-value tests:
- Moving Averages — SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA
- Momentum Oscillators — RSI (Wilder), Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator
- Trend & Directional — MACD, ADX (+DI/-DI), Aroon, TRIX, Aroon Oscillator, Vortex, Mass Index, Choppiness Index, Vertical Horizontal Filter
- Price Oscillators — PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power
- Volatility & Bands — ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility
- Trailing Stops — Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop
- Volume — OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement
- Price Statistics — Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle
Why streaming-first matters
Classic TA libraries are batch-only: every live tick triggers a full recomputation over the entire history. Wickra updates indicator state in O(1) per tick. On a 5K-bar history the streaming RSI gap is ~17× over the nearest peer with a streaming API and 100×+ over batch-only libraries.
Full project
See https://github.com/kingchenc/wickra for benchmarks, the Rust core, Node.js and WebAssembly bindings, examples, and CI.
License
Licensed under the PolyForm Noncommercial License 1.0.0. Personal, research, educational, and non-profit use are all permitted. Commercial sale requires a separate license — contact via the GitHub repo.