Balance Curve Slope Feedback for Adaptive Expert Advisor Position Sizing

Summary

The article describes a feedback mechanism that adjusts an Expert Advisor’s trade volume according to the slope of its balance curve. Before a prospective trade, the system estimates slope from recent closed trades; when the slope weakens, it reduces volume, and when it recovers, it restores volume. It outlines stepped, linear, and hysteresis-based transitions between normal and reduced volume, and discusses implementation as a reusable MQL5 library.

A backtest comparison reports lower balance and equity drawdowns and a higher profit factor with the control enabled, alongside modestly lower net profit and expected payoff. These results come from the example EA and do not establish that the method generalizes. The author notes that the system cannot make a losing strategy profitable, may react too slowly if trading conditions change quickly, and is not directly suitable for strategies whose volume is integral to their logic, such as Martingale systems. The transition rules require testing against the EA being controlled.

Key ideas

• The system adjusts trade volume using the recent slope of the balance curve as feedback.
• Reduced volume is used when the slope deteriorates, with gradual or stepped restoration as it improves.
• Stepped, linear, and hysteresis-based rules offer different reaction and switching behavior.
• The example backtest shows reduced drawdowns and a higher profit factor, but slightly lower profit and expected payoff.
• The method depends on strategy behavior and cannot turn a losing Expert Advisor into a profitable one.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.