Summary
ChaikinVolatility is RTTA's streaming implementation of: Percent rate-of-change of an EMA of the high-low range.
Update API
result = rtta.ChaikinVolatility().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
ChaikinVolatility first smooths the bar range with an EMA, then reports the
percent change of that smoothed range versus its value roc_window samples
ago. Rising values mark expanding range; falling values mark contraction.
Recurrence
Let \(h_t,l_t\) be high and low, \(n\) the EMA window, and \(k\) the ROC lookback.
\[R_t = h_t - l_t, \qquad
E_t = \operatorname{EMA}_n(R_t)\]
\[CV_t = 100 \cdot \frac{E_t - E_{t-k}}{E_{t-k}}\]
The return value is the current scalar indicator value.
Composed Primitives
Implementation Notes
The recurrence is implemented in src/rtta/indicator.cpp in class ChaikinVolatility.