Discussing the article: "Automating Trading Strategies in MQL5 (Part 39): Statistical Mean Reversion with Confidence Intervals and Dashboard"

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Check out the new article: Automating Trading Strategies in MQL5 (Part 39): Statistical Mean Reversion with Confidence Intervals and Dashboard.

In this article, we develop an MQL5 Expert Advisor for statistical mean reversion trading, calculating moments like mean, variance, skewness, kurtosis, and Jarque-Bera statistics over a specified period to identify non-normal distributions and generate buy/sell signals based on confidence intervals with adaptive thresholds.

The statistical mean reversion strategy leverages the tendency of prices to revert to their historical mean after significant deviations, enhanced by statistical analysis to identify non-normal distributions where such reversions are more probable due to asymmetry and tail risks.

For a buy setup, the price drops below the lower confidence interval with negative skewness signaling potential upside momentum from oversold conditions; for a sell setup, the price exceeds the upper interval with positive skewness indicating overbought conditions likely to correct downward, both filtered by Jarque-Bera statistics for non-normality confirmation and kurtosis thresholds to avoid excessively leptokurtic markets.

When using this strategy, we further refine entries by aligning them with higher timeframes for trend context. We implement dynamic risk controls, such as equity percentage sizing, base stop-loss and take-profit distances, trailing stops for profit locking, partial position closures at predefined profit levels, and time-based exits, to mitigate prolonged exposure. By integrating these statistical and risk elements, we aim to capture reliable reversion opportunities in volatile markets. Have a look below at the statistical distributions expressed diagrammatically that we will be using.

Author: Allan Munene Mutiiria