Discussing the article: "Adaptive Malaysian Engulfing Indicator (Part 2): Optimized Retest Bar Range"
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Check out the new article: Adaptive Malaysian Engulfing Indicator (Part 2): Optimized Retest Bar Range.
The article adds a self-adaptive layer to the Malaysian Engulfing indicator by optimizing the retest bar range with a constrained brute-force search scored by MFE and MAE. It details the data model, helper routines, and an MQL5 implementation that gathers historical setups, computes excursions, and selects the best parameter. Readers learn how to remove manual tuning and run the indicator with context-appropriate settings across symbols and timeframes.
You already have a working Malaysian Engulfing detector and a retest-confirmation routine, but a single practical problem blocks reliable scaling: the retest bar range cannot be “set once” for all markets and timeframes. On one symbol a fixed range captures valid pullbacks; on another it misses setups or admits noisy false confirmations. As volatility, momentum and structural rhythm change, manual tuning becomes trial-and-error and strategy performance drifts.
This article adds a data-driven adaptive layer that chooses the retest range objectively for the current context. Instead of guessing, we evaluate historical setups using MFE (Maximum Favorable Excursion) and MAE (Maximum Adverse Excursion) measured from a consistent entry rule, score candidate retest distances (avgMFE − avgMAE) with a constrained brute-force search over a single parameter, and select per-symbol/per-timeframe optimal values. The output is reproducible: optimalBullishRetestRange and optimalBearishRetestRange (and a run-time summary) that can be validated and applied automatically.
Author: Chukwubuikem Okeke