VolumeWeightedMovingAverage

Incremental, causal technical analysis documentation

Summary

VolumeWeightedMovingAverage is RTTA's streaming implementation of: VWMA rolling close weighted by volume.

Update API

result = rtta.VolumeWeightedMovingAverage().update(close, volume)

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

Theory Of Operation

VolumeWeightedMovingAverage is a causal smoother or average. It updates compact rolling or exponential state with the newest observation and returns the current smoothed estimate.

Recurrence

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

\[PV_t = PV_{t-1}+price_t\,volume_t\]
\[V_t = V_{t-1}+volume_t, \qquad y_t = G(PV_t,V_t,z_t)\]

The return value is the current scalar indicator value.

Implementation Notes

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

Reference