AveragePrice

Incremental, causal technical analysis documentation

Summary

AveragePrice is RTTA's streaming implementation of: Average of open, high, low, and close.

Update API

result = rtta.AveragePrice().update(open, high, low, close)

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

Theory Of Operation

AveragePrice is a causal smoother or average. It updates compact rolling or exponential state with the newest observation and returns the current smoothed estimate.

Recurrence

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

\[AP_t = \frac{open_t + high_t + low_t + close_t}{4}\]

The return value is the current scalar indicator value.

Implementation Notes

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

Reference