Maximum Favourable Excursion (MFE) is the furthest a trade moved in your favour at any point while you held it. Maximum Adverse Excursion (MAE) is the furthest it moved against you. Both are measured from your entry price, using the highest high and lowest low over the holding period — not the open or close.
Your profit and loss tells you where a trade finished. It says nothing about where it went along the way, and that journey is where most fixable mistakes live.
MFE and MAE describe the journey. For a long trade:
For a short, the two swap: your favourable excursion is the lowest low, your adverse excursion is the highest high.
Note that both use intraday highs and lows, not closing prices. A stop sitting 6% below your entry gets hit by a low of −6.2%, even if the candle closes at −1%. Measuring on closes hides exactly the event you care about.
You buy a stock at $71.65 and sell nine days later at $75.08. Your P&L is +4.79%. That is the whole story your broker tells you.
Now add the path. Over those nine sessions the stock printed a high of $77.50 and a low of $69.69.
Three facts fall out of this that the P&L alone could never give you:
You are exiting too early. One trade giving back 3% means nothing. Forty trades where the average MFE is 9% and the average win is 4% means your exit rule is systematically leaving more than half the move behind.
The fix is a rule, not a resolution: a trailing stop, scaling out in thirds, or holding to a moving average rather than a fixed percentage.
Your stops are too wide, or your entries are early. If winning trades routinely go 6–7% against you before working, you are paying for entry timing with risk — and any trade that does not recover becomes an outsized loss.
This is the most useful pattern of all. If your stop is at −5% and your losers show an MAE of −5.4% before the stock recovers, you are not being wrong. You are being stopped out by ordinary noise and then watching the trade work without you.
The test is whether the MAE distribution clusters just beyond your stop or well past it. It is also the input that tells you how tight your stop could safely be. Clustering just past means widen slightly. Spread well past means those trades genuinely failed and the stop did its job.
A single trade's MFE and MAE are anecdotes. Across fifty trades they become a distribution, and three comparisons matter:
| Comparison | What it answers |
|---|---|
| Average MFE vs average win | How much of the available move you actually capture |
| MAE on winners vs MAE on losers | Whether your stop can separate the two at all |
| MFE on losers | How many losers were profitable at some point and gave it all back |
That last one is the uncomfortable number. A loser with an MFE of +6% was not a bad trade. It was a good trade that you managed badly, and it belongs in a different bucket from a trade that never worked at all.
Because doing it by hand is miserable. For every trade you need the intraday high and low across the entire holding period, measured from your actual fill price, for the exact dates you held — and if you scaled in or out, from a weighted average.
That is a data problem, not an insight problem. The insight is straightforward once the numbers exist.
TradePiko calculates maximum favourable and adverse excursion automatically for every trade in your journal, measured from your real fill price over your actual holding period. No spreadsheets, no manual chart reading.
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