DonchianChannel

Incremental, causal technical analysis documentation

Summary

DonchianChannel is RTTA's streaming implementation of: Channel from rolling highest high and lowest low.

Update API

result = rtta.DonchianChannel().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

DonchianChannel maintains rolling extrema, ranges, or envelopes. The C++ state updates the relevant window/range statistics once per input sample.

Recurrence

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

\[H_t=\max_{i\in W_t} high_i, \qquad L_t=\min_{i\in W_t} low_i\]
\[y_t = G(H_t,L_t,close_t)\]

update(...) returns a result struct with fields upper, lower, middle, width, percent.

Implementation Notes

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

Reference