Summary
EhlersOptimalTrackingFilter is RTTA's streaming implementation of: Adaptive tracking filter using Ehlers' price uncertainty tracking index.
Update API
result = rtta.EhlersOptimalTrackingFilter().update(high, low)
The update(...) call consumes one observation using high, low. advance(...)
uses the same inputs when the caller wants to update state without materializing
a Python return value.
Theory Of Operation
EhlersOptimalTrackingFilter implements the streaming form of Adaptive tracking filter using Ehlers' price uncertainty tracking index. Each update(...) call consumes exactly one new observation tuple and advances the internal state before returning the current value or result struct.
Recurrence
Let \(z_t = (high_t, low_t)\) denote the observation consumed by one
update(...) call and let \(\theta\) denote constructor parameters such as
window lengths, thresholds, and smoothing constants.
The return value is the current scalar indicator value.
Implementation Notes
The recurrence is implemented in src/rtta/indicator.cpp in class EhlersOptimalTrackingFilter.