Change-point Detection

What is Change-point Detection?

Change-point detection is the statistical problem of locating when a time series' generating process shifted: a change in mean, in variance, or in distribution, as opposed to where price is heading next. The classic sequential detector is CUSUM (Page, 1954), built for industrial quality control. It maintains running sums of deviations above and below a reference level, subtracts a small slack allowance each bar so pure noise decays back toward zero, and raises an alarm when an accumulated sum crosses a decision threshold. Because evidence accumulates, a persistent small drift eventually trips the detector even when no single bar looks unusual.

Applied to returns, an alarm marks a candidate shift in drift (a trend starting or dying); applied to squared or absolute returns, it flags volatility regime switches. The tuning is an explicit trade-off: tighter thresholds detect changes sooner but fire more false alarms, looser ones are quieter but slower. Detection is also inherently after the fact, since a change must accumulate evidence before it becomes visible, which is why change points pair naturally with persistence gauges like the Hurst exponent rather than acting as standalone entries.

How traders use it

• As a regime alarm: CUSUM on returns timestamps candidate shifts in drift, prompting a re-read of structure and bias or an update to a trend regime label, rather than triggering trades by itself.
• As a volatility monitor: run on squared or absolute returns to flag transitions between quiet and turbulent conditions that sizing and stop rules should respond to.
• As an adaptive anchor: restart lookbacks, distributions, or averages from the most recent detected change point so statistics describe only the current regime instead of blending regimes.