SavitzkyGolayFilter

Incremental, causal technical analysis documentation

Summary

SavitzkyGolayFilter is RTTA's streaming implementation of: Rolling polynomial least-squares smoother with first and second derivative outputs.

Update API

result = rtta.SavitzkyGolayFilter().update(close)

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

Theory Of Operation

SavitzkyGolayFilter implements the streaming form of Rolling polynomial least-squares smoother with first and second derivative outputs. Each update(...) call consumes exactly one new observation tuple and advances the internal state before returning the current value or result struct.

Recurrence

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

\[W_t = \operatorname{push}(W_{t-1}, z_t, n)\]
\[y_t = G(W_t)\]

update(...) returns a result struct with fields smooth, first_derivative, second_derivative.

Implementation Notes

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

Reference