HeikinAshiTransform

Incremental, causal technical analysis documentation

Summary

HeikinAshiTransform is RTTA's streaming implementation of: Incremental Heikin-Ashi OHLC transform for smoothing candles.

Update API

result = rtta.HeikinAshiTransform().update(open, high, low, close)

The update(...) call consumes one observation using open, high, low, close. advance(...) uses the same inputs when the caller wants to update state without materializing a Python return value.

Theory Of Operation

HeikinAshiTransform implements the streaming form of Incremental Heikin-Ashi OHLC transform for smoothing candles. Each update(...) call consumes exactly one new observation tuple and advances the internal state before returning the current value or result struct.

Recurrence

Let \(z_t = (open_t, high_t, low_t, close_t)\) denote the observation consumed by one update(...) call and let \(\theta\) denote constructor parameters such as window lengths, thresholds, and smoothing constants.

\[HAclose_t=\frac{open_t+high_t+low_t+close_t}{4}\]
\[HAopen_t=\frac{HAopen_{t-1}+HAclose_{t-1}}{2}\]
\[HAhigh_t=\max(high_t,HAopen_t,HAclose_t), \qquad HAlow_t=\min(low_t,HAopen_t,HAclose_t)\]

update(...) returns a result struct with fields open, high, low, close.

Implementation Notes

The recurrence is implemented in src/rtta/indicator.cpp in class HeikinAshiTransform.

Reference