A conventional report tells you net profit, win rate, drawdown, Maximum Adverse Excursion (MAE) and Maximum Favorable Excursion (MFE). BackTest Forensics asks what those numbers were doing through time, in what sequence, under which market conditions, and whether the explanation survives a counter-test.
Maximum Adverse Excursion (MAE) is the largest move against a position while the trade is open. It is only the starting point. The useful information is in the path: when the heat arrived, how long it lasted, whether the trade recovered, what happened next, and whether that behavior repeated under the same conditions.
Measure maximum heat, time underwater, time to Maximum Adverse Excursion (MAE), repeated adverse waves, recovery time, and whether the worst adverse move occurred before or after favorable excursion. Then compare that path across winners, losers, direction, session, volatility and market state.
Maximum Favorable Excursion (MFE) is the largest move in the trade's favor while it is open. Measure time to MFE, realized-P&L-to-MFE capture, post-MFE giveback, and whether the exit occurred during a normal retracement or after genuine deterioration. Two +$80 winners can be radically different if one reached only +$110 and the other reached +$500 first.
Maximum Adverse Excursion (MAE) → Maximum Favorable Excursion (MFE) is different from MFE → MAE. A trade that suffers early, recovers and trends is not the same setup as one that moves immediately in favor and later gives everything back. Sequence can expose entry quality, stop pressure and exit inefficiency.
The optimizer asks which threshold improves historical results. Forensics first asks what kind of trades the threshold would remove—and what valuable trades it would accidentally destroy.
In one SATS study, losing long trades averaged about 107 points of Maximum Adverse Excursion (MAE) against only about 54 points of Maximum Favorable Excursion (MFE). In plain English, those losing longs moved almost twice as far against the position as they ever moved in its favor. That was more useful than simply knowing the longs lost money. It suggested a recurring trade path: substantial heat with limited opportunity.
A backtester can tell you a trade made $80. We ask how much opportunity existed before that $80 was realized, how long it existed, and how much was surrendered.
We group trade paths, not just losing outcomes. The goal is to find whether the same adverse behavior keeps appearing under related conditions.
Trade-path evidence becomes more useful when attached to the environment surrounding the trade. Where data supports it, EdgeQuery IQ compares excursion behavior with trend, volatility, session, macro and structural market-state context.
The same entry logic may encounter more adverse excursion, less follow-through or more giveback because the surrounding environment changed.
If Maximum Adverse Excursion (MAE), Maximum Favorable Excursion (MFE), recovery time or capture efficiency deteriorates even inside comparable market states, the evidence points back toward strategy-side behavior.
A strategy can keep firing the same nominal setup while its trade path changes because the environment changed. We test the interaction rather than forcing a one-cause story.
The output is not “here is the parameter that maximized the old equity curve.” It is a chain of evidence that produces a testable explanation and then tries to disprove it.
Maximum Adverse Excursion (MAE), Maximum Favorable Excursion (MFE), time underwater, recovery, sequencing, giveback, duration and realized outcome.
Direction, time, volatility, regime, market structure, macro context and other available states.
Use matched controls, chronology, holdouts and out-of-sample checks where the dataset permits them.