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SuperTrend

Incremental, causal technical analysis documentation

Summary

SuperTrend is RTTA's streaming implementation of: ATR-band trend-following indicator.

Update API

result = rtta.SuperTrend().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

SuperTrend builds ATR-scaled bands around the high/low midpoint and trails the active band in the direction of the current trend. Crosses through the active band flip the trend side; otherwise the band only tightens, which makes the indicator a volatility-adjusted trailing stop.

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.

\[ATR_t=\operatorname{ATR}_n(close_t,high_t,low_t), \qquad B^+_t=\frac{high_t+low_t}{2}+mATR_t, \quad B^-_t=\frac{high_t+low_t}{2}-mATR_t\]
\[U_t=\begin{cases}B^+_t, & B^+_t<U_{t-1}\text{ or }close_{t-1}>U_{t-1}\\U_{t-1},&\text{otherwise}\end{cases}\]
\[L_t=\begin{cases}B^-_t, & B^-_t>L_{t-1}\text{ or }close_{t-1}<L_{t-1}\\L_{t-1},&\text{otherwise}\end{cases}\]
\[trend_t=\begin{cases}1,& close_t\ge L_t\\-1,& close_t\le U_t\\trend_{t-1},&\text{otherwise}\end{cases}, \qquad value_t=\begin{cases}L_t,& trend_t=1\\U_t,& trend_t=-1\end{cases}\]

update(...) returns a result struct with fields value, direction, upper, lower.

Composed Primitives

ATR

Implementation Notes

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

Reference