Using ATR-Normalized MAE and MFE to Evaluate Turtle-Style Entries

Summary

This tool records each entry's price, direction, and ATR, then tracks the highest and lowest observed prices over a chosen follow-up period. It aims to measure maximum adverse excursion (MAE) and maximum favorable excursion (MFE), normalize each by entry-time ATR, and compare their averages through an E-ratio. A sample entry generator uses 20-day price extremes with 50- and 300-day moving-average filters to mark directional changes; it is described as a simplified example rather than a complete Turtle breakout system.

The published setup references BTC/USDT daily data over a multi-year interval, but no calculated E-ratio or performance findings are shown. The implementation has important measurement problems: for both long and short entries, its MAE and MFE assignments appear reversed relative to adverse and favorable movement. Its running averages update by repeatedly averaging the prior value with the new observation, rather than maintaining a true arithmetic mean. These issues mean the resulting ratio should not be treated as a reliable strategy evaluation without correction.

Key ideas

• The tool tracks post-entry price extremes over a fixed horizon to estimate MAE and MFE.
• Dividing excursions by entry-time ATR is intended to make observations comparable across volatility levels.
• A simplified entry example combines 20-day extremes with moving-average trend filters.
• The shown calculations appear to swap adverse and favorable excursions and do not compute conventional cumulative averages.
• The backtest setup contains no reported E-ratio values or strategy results.

Tags

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