LiquidityDroughtDetector

Summary

LiquidityDroughtDetector is RTTA's streaming implementation of: Relative volume/depth drought detector using lower-threshold hysteresis.

Update API

result = rtta.LiquidityDroughtDetector().update(volume, bid_size, ask_size)

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

Theory Of Operation

LiquidityDroughtDetector first constructs a scalar market-state metric from the current observation and compact streaming state, then passes that metric through explicit entry/exit hysteresis. The metric is named in the recurrence below; the hysteresis keeps the output stable until the metric crosses the opposite exit band.

Recurrence

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

\[L_t=\max(volume_t,0)+\max(bidSize_t,0)+\max(askSize_t,0)\]

\[q_t=\frac{L_t}{\max(B_{t-1},\epsilon)}, \qquad B_t=\alpha L_t+(1-\alpha)B_{t-1}\]

\[r_t = \begin{cases} 1, & r_{t-1} = 0 \text{ and } q_t \le e \\ 0, & r_{t-1} = 1 \text{ and } q_t \ge x \\ r_{t-1}, & \text{otherwise} \end{cases}, \qquad e < x\]

The return value is the current scalar indicator value.

Implementation Notes

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

Reference

Background reference