AwesomeOscillator

Incremental, causal technical analysis documentation

Summary

AwesomeOscillator is RTTA's streaming implementation of: Difference between short and long median-price moving averages.

Update API

result = rtta.AwesomeOscillator().update(high, low)

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

Theory Of Operation

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

\[E_t=\alpha z_t+(1-\alpha)E_{t-1}\]
\[y_t = G(E_t,E^{(2)}_t,\ldots,z_t)\]

The return value is the current scalar indicator value.

Implementation Notes

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

Reference