Maximum Favorable Excursion (MFE) is the highest mark-to-market profit a trade achieved at any tick or bar between entry and exit — regardless of where the trade ultimately closed. Introduced by John Sweeney in Campaign Trading (1996), MFE is the benchmark against which every exit should be measured: it shows not just what a trade made, but what it could have made.
Key Takeaways
- MFE measures the peak unrealized profit of a trade; dividing realized P&L by MFE gives exit efficiency, a ratio below 40% signals a systematic exit problem.
- Plotting MFE across 20–30 trades as a histogram reveals where your setups naturally peak, enabling data-driven take-profit and trailing stop placement.
- MFE paired with MAE diagnoses whether a trader’s real weakness is exits (low MFE efficiency) or stop placement (MAE too large relative to MFE).
How to Calculate Maximum Favorable Excursion
MFE is the maximum unrealized profit reached at any point during the trade’s lifetime:
MFE = Peak Price − Entry Price × Position Size (for long trades)
MFE = Entry Price − Trough Price × Position Size (for short trades)
The derived metric — exit efficiency — is what makes MFE actionable:
Exit Efficiency (%) = (Realized P&L ÷ MFE) × 100
An exit efficiency of 100% means the trade was closed at its exact high. A ratio of 47% means the trader captured less than half the move the trade offered. Aggregating this across a sample of trades separates noise from a systematic exit problem.
Quick Reference
| Aspect | Detail |
|---|---|
| Formula | Exit Efficiency = (Realized P&L ÷ MFE) × 100 |
| Good Range | Exit efficiency above 50–60% |
| Warning Signs | Consistent exit efficiency below 40% — revisit take-profit rules |
| Best Sample Size | Minimum 20–30 trades per setup before drawing conclusions |
| Data Source | Requires logging intra-trade high/low at the bar or tick level |
Practical Example
A trader buys 200 shares of AAPL at $185.00 on a breakout setup, with a stop at $183.50 (risk = $300). The stock runs to $188.20 — an unrealized gain of $640 — before reversing. That $640 is the MFE. The trader exits at $186.50, capturing $300.
Exit efficiency = $300 ÷ $640 = 47%.
After logging 30 similar breakout trades, the MFE histogram shows 70% of trades peaked between $500–$700 unrealized profit before reversing sharply. Armed with this data, the trader places a limit order at $188.00 (just below the histogram’s peak cluster) or sets a trailing stop that activates once the trade reaches $500 in profit. Either adjustment projects exit efficiency above 75% — without changing the entry setup at all.
On a 5-minute SPY chart, intraday breakout trades typically produce MFE of 0.3–0.8% before the first significant retracement, giving day traders a calibration range when no trade history exists yet for a new setup.
Maximum Favorable Excursion, or MFE, is the biggest unrealized profit a trade reached before you closed it. Comparing MFE to your actual profit shows how efficiently you exited, and logging it across many trades reveals whether you are leaving money on the table.
Common Mistakes
- Analyzing MFE without MAE. MFE in isolation is misleading. A trade with $800 MFE and $750 MAE is a different setup than one with $800 MFE and $150 MAE. Always compare the two — good setups show MFE consistently larger than MAE.
- Drawing conclusions from too few trades. MFE distributions need at least 20–30 samples per setup to be statistically meaningful. A 10-trade sample produces noisy histograms that justify bad decisions.
- Applying MFE benchmarks across setup types. Momentum breakout trades typically show high MFE with sharp reversals; mean-reversion trades show steadier, lower MFE. Blending both into one histogram and setting a single take-profit level misses this structural difference.
- Assuming low exit efficiency means exiting too early. Many traders discover through MFE data that they already exit near the peak — and the real problem is holding losers too long (high MAE), not cutting winners short. The data, not the gut feeling, determines the diagnosis.
How JournalPlus Tracks Maximum Favorable Excursion
JournalPlus automatically records MFE and MAE for every trade logged, then calculates exit efficiency per trade and aggregates it by setup tag or ticker. The MFE histogram view makes it straightforward to identify natural peak clusters for a given strategy and align take-profit levels with actual historical trade behavior — no spreadsheet required.
