The worst unrealised loss a trade experienced before it closed, which tells you whether your stops are too wide or too tight.
Record, for every trade, how far it went against you in R before resolving. Then compare the distributions for winners and losers. The pattern is usually stark: winners rarely dip beyond a certain point, while losers keep going.
That threshold is actionable. If 90% of your winning trades never traded worse than minus 0.6R, a stop at minus 1.0R is spending 40% more risk than the strategy needs, and tightening it to minus 0.7R raises R-multiples across the board while sacrificing a modest number of eventual winners. Test the change on historical trades before adopting it - the tighter stop also raises the loss rate, and the net effect on expectancy is what matters.
MAE also exposes entry timing. Consistently large adverse excursions on eventual winners means you are entering early, which is a signal-quality problem rather than a stop problem.
Original diagrams for the ideas on this page. Illustrative, not real market data.
Expectancy: the average trade. Forty trades sorted by outcome: 24 small losses and 16 larger wins. Weighting each side by how often it happens gives the average result per trade, marked here by the dashed line at +$120.
Educational only, not advice. Spotted an error? Post in Site Feedback.