StochasticMomentumIndex

Summary

StochasticMomentumIndex is RTTA's streaming implementation of: Double-smoothed stochastic momentum index with signal line.

Update API

result = rtta.StochasticMomentumIndex().update(close, high, low)

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

Theory Of Operation

StochasticMomentumIndex measures where close sits relative to the midpoint of the recent high-low range, then double-smooths both the distance and the range before normalizing. A signal EMA is also produced.

Recurrence

Let \(c_t,h_t,l_t\) be close/high/low, \(n\) the range window, and \(s_1,s_2,s\) the smoothers.

\[HH_t=\max_{0\le i<n}h_{t-i},\quad LL_t=\min_{0\le i<n}l_{t-i},\quad M_t=\frac{HH_t+LL_t}{2}\]

\[D_t=c_t-M_t,\quad R_t=HH_t-LL_t\]

\[SM_t=\operatorname{EMA}_{s_2}(\operatorname{EMA}_{s_1}(D_t)),\quad SR_t=\operatorname{EMA}_{s_2}(\operatorname{EMA}_{s_1}(R_t))\]

\[SMI_t=100\frac{SM_t}{0.5\,SR_t},\quad signal_t=\operatorname{EMA}_s(SMI_t)\]

update(...) returns a result struct with fields smi, signal.

Implementation Notes

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

Reference

Background reference