MAE/MFE Distributions

What are MAE/MFE distributions?

MAE/MFE distributions describe how far trades move against and in favor of the entry before they close. Maximum adverse excursion (MAE) is the worst intratrade drawdown a position suffered; maximum favorable excursion (MFE) is the best open profit it reached. Collected across a full trade list and plotted as distributions, they reveal the internal anatomy of a strategy that final profit-and-loss numbers hide: how much heat winners typically take, how much open profit losers gave back, and where stops and targets actually bind.

The concepts were popularized by John Sweeney, who proposed analyzing adverse excursion as a rational basis for stop placement. His core observation still drives the analysis: in many systems, eventual winners and eventual losers separate early, with winners rarely dipping far below entry and losers frequently plunging past any reasonable threshold. Where that separation exists, the MAE distribution locates a stop level that cuts losers while sparing most winners.

MFE tells the mirror-image story about exits. A distribution showing losers that regularly reached substantial open profit before closing red points to give-back, and argues for tighter profit-taking or trailing logic. Both excursions are usually normalized, in R-multiples via the R-multiple framework, in percent, or in units of ATR, so trades across instruments and volatility regimes are comparable.

How it's calculated

Excursions are computed per trade from the price extremes recorded while the position was open, then aggregated into distributions.

Values are commonly normalized by initial risk (R), by entry price (percent), or by ATR at entry.

Bar-based backtests only see bar extremes; intrabar path assumptions can distort excursions on coarse timeframes.

How traders use it

• Scatter-plotting MAE against final trade result, with winners and losers marked, to find a stop distance that would have removed a large share of losers at a small cost in sacrificed winners.
• Reading the MFE distribution of losing trades to quantify give-back and decide whether trailing stops, partial exits, or breakeven rules would have captured abandoned open profit.
• Sizing stop distances in volatility units by combining MAE percentiles with ATR-based stop distance logic, rather than picking round numbers.
• Feeding trade management rules, a practice covered under MAE/MFE informed management, where excursion statistics justify moves like tightening stops after a threshold of open profit.
• With the standard caveat that excursion statistics are descriptive of one historical sample; rules tuned tightly to past percentiles inherit all the fragility of any other fitted parameter.

MAE/MFE distributions vs related concepts