EfficiencyRatio

Summary

EfficiencyRatio is RTTA's streaming implementation of: Kaufman efficiency ratio of net directional move to path length over a rolling window.

Update API

result = rtta.EfficiencyRatio().update(close)

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

Theory Of Operation

EfficiencyRatio is the direction/noise ratio that drives Kama. Values near 1 mean a clean directional move; values near 0 mean a noisy path with little net displacement.

Recurrence

Let \(c_t = close_t\) and \(n\) the window.

\[ER_t = \frac{|c_t - c_{t-n}|}{\sum_{i=0}^{n-1} |c_{t-i} - c_{t-i-1}|}\]

The denominator is a rolling sum of absolute one-step changes. The numerator uses the close from \(n\) samples earlier, matching the efficiency term inside KAMA.

The return value is the current scalar indicator value.

Composed Primitives

Kama

Implementation Notes

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

Reference

Background reference