Adaptive Position Sizing with Imaginary Equity and Indicator Signals

Summary

In this interview, Automated Trading Championship participant Matúš German explains the design of his EA, which combines a moving average for trend direction with Williams Percent Range for entries and exits. Its position sizing method tracks hypothetical equity based on the profit or loss each closed trade would have produced at a fixed one-lot size. An average of recent outcomes then informs whether the system uses more aggressive sizing or reduces trade volume as results weaken.

German reports that the EA rose sharply early in the competition, but attributes the move partly to luck and says its risk was excessive. He describes occasional indicator-triggered additions to losing positions, a fixed stop loss if the indicator does not exit, and no take-profit or trailing stop. He had optimized only a small subset of its inputs and cautions that the championship sizing would not suit a real account without adjustment. The interview provides a strategy description and the developer’s own reservations, not evidence of durable performance.

Key ideas

• The EA uses a moving average to assess trend and Williams Percent Range to time entries and exits.
• Its sizing rule uses recent hypothetical fixed-volume trade results to adjust aggressiveness.
• The system may add to losing positions when another indicator entry signal occurs.
• The developer warns that early competition gains may reflect luck and high risk.
• The author says position size needs adjustment for account conditions before real trading.

Tags

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