A trade closes with a $500 profit. Good trade? Maybe.

What if it was up $2,500 before giving most of the move back? What if it went $4,000 against you before recovering? What if the same pattern happens repeatedly? Final P&L cannot answer those questions.

Maximum Favorable Excursion and Maximum Adverse Excursion can.

Two closely related parts of this decision are Why Win Rate Can Mislead You: Risk-Reward, Tail Losses and the Trades You Do Not See and Trading Costs: How Spread, Slippage and Commission Quietly Destroy a Backtest.

What is MFE?

Maximum Favorable Excursion, or MFE, is the furthest a trade moved in your favour while it was open. If you bought at 100, price reached 108 and you eventually exited at 104, the MFE was 8 even though the realised gain was 4.

What is MAE?

Maximum Adverse Excursion, or MAE, is the furthest the trade moved against you before it closed. If the same trade fell to 96 first, the MAE was 4.

Across one trade, these numbers are descriptive. Across hundreds of comparable candidates, they begin to show the geometry of the opportunity.

Why this matters for stop losses

Suppose most eventual winners experience only small adverse movement before working. A very wide stop may be taking unnecessary risk. If strong winners routinely experience deeper adverse excursions before recovering, a tight stop may be cutting the strategy off before its mechanism has time to work.

The answer should come from distributions, not one memorable trade.

Why this matters for targets

MFE can show whether the market regularly offered more than your exit captured, or whether your target is sitting beyond what similar opportunities usually delivered. A high win rate with tiny favourable excursion may be economically less attractive than a lower win rate with a much larger right tail.

Time belongs in the geometry

Two trades can have the same MFE and MAE and still be very different. One reaches the favourable excursion in twenty minutes. The other takes nine days while capital remains tied up. Time-to-resolution affects usability, financing, opportunity cost and the type of customer who can realistically act on the signal.

Costs belong in the geometry too

If the median favourable excursion is small relative to spread, commission and slippage, the opportunity may have very little room after execution. This is why QuantWeaver's Geometry work treats cost headroom as part of the economic question rather than an afterthought.

How Radar uses the idea

Radar is designed to qualify opportunities with evidence about what historically happened after a candidate signal, including favourable and adverse excursion, risk-reward geometry, costs, context, time-to-resolution and known failure conditions. The aim is to help the user understand why an opportunity deserves attention, rather than simply add another alert to the screen.

How X-Ray uses the idea

For an existing automated strategy, MFE and MAE can help distinguish entry quality from exit quality. A strategy may enter in useful places and then give too much back. Another may close winners efficiently but absorb excessive adverse movement first. Those are different diagnostic problems and they should not receive the same fix.