RollingVarianceShiftDetector

Summary

RollingVarianceShiftDetector is RTTA's streaming implementation of: Causal adjacent-window variance shift detector using log variance ratio.

Update API

result = rtta.RollingVarianceShiftDetector(window=20, threshold=1.0).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

RollingVarianceShiftDetector compares two adjacent rolling windows: a reference window and a recent window. The C++ state moves expired recent samples into the reference window, maintains sufficient statistics, and emits the sign of the statistic difference when it exceeds the configured threshold.

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.

\[\sigma^{2,R}_t=\operatorname{var}(R_t), \qquad \sigma^{2,B}_t=\operatorname{var}(B_t)\]

\[q_t=\log\left(\frac{\sigma^{2,R}_t+\epsilon}{\sigma^{2,B}_t+\epsilon}\right)\]

\[r_t = \begin{cases} 1, & q_t > h \\ -1, & q_t < -h \\ 0, & \text{otherwise} \end{cases}\]

The return value is the current scalar indicator value.

Implementation Notes

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

Reference

Background reference