RollingSpreadLiquidityShiftDetector

Summary

RollingSpreadLiquidityShiftDetector is RTTA's streaming implementation of: Causal adjacent-window quote spread/depth liquidity stress shift detector.

Update API

result = rtta.RollingSpreadLiquidityShiftDetector(window=20, threshold=1e-06).update(bid_price, bid_size, ask_price, ask_size)

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

Theory Of Operation

RollingSpreadLiquidityShiftDetector 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 \(z_t = (bid_price_t, bid_size_t, ask_price_t, ask_size_t)\) denote the observation consumed by one update(...) call and let \(\theta\) denote constructor parameters such as window lengths, thresholds, and smoothing constants.

\[s_t=\frac{\max(ask_t-bid_t,0)}{\max(bid\_size_t+ask\_size_t,\epsilon)}\]

\[q_t=\operatorname{mean}(R^s_t)-\operatorname{mean}(B^s_t)\]

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

The return value is the current scalar indicator value.

Implementation Notes

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

Reference

Background reference