Discussing the article: "Detecting Structural Breakpoints in Price Series Using CUSUM in MQL5 (Part 1): From Statistical Theory to a Working MQL5 Indicator"

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Check out the new article: Detecting Structural Breakpoints in Price Series Using CUSUM in MQL5 (Part 1): From Statistical Theory to a Working MQL5 Indicator.

This article builds a sequential CUSUM breakpoint detector for MetaTrader 5, starting from the statistical construction and ending with a working indicator. It explains standardized log-returns, dual accumulators, the role of k and h, and the ARL₀ baseline from Siegmund. The code walkthrough covers buffer persistence, recalculation handling, idempotent chart objects, and a three-pass engine, so you can compile, attach, and use the detector to flag structural regime shifts earlier than fixed-window smoothers.

Trading systems often degrade when market regimes shift. Fixed-window indicators such as moving averages or ATR react only after a structural change has already affected prices, because they summarize the recent past rather than test for an active change.

This article presents a sequential alternative based on the Cumulative Sum (CUSUM) control chart. The method processes returns bar by bar, accumulates evidence of a distributional shift, and declares a breakpoint as soon as a statistical threshold is crossed.

The first half explains the statistical construction of the detector: return standardization, dual accumulators, threshold selection, and reset logic. The second half translates the method into a MetaTrader 5 indicator, CUSUM_Breakpoint.mq5, with attention to buffer persistence, recalculation handling, and chart-object management. A second article follows with a full empirical validation across six instruments, three timeframes, and two macroeconomic periods.

CUSUM watches two running totals built from standardized returns. The moment either one crosses a threshold, a break is declared:

τ=inf{t≥1:S_t^+>h or S_t^-<-h}

Everything in this article explains how S_t^+, S_t^-, and h are built, and exactly what statistical guarantee this single rule provides.

Author: Ushana Kevin Iorkumbul