Max Favorable Excursion (MFE)

Max Favorable Excursion (MFE) is a important concept in trading analytics that measures the maximum unrealized profit a trade achieves during its lifecycle. By analyzing MFE, traders can better understand how much potential profit a trade might offer before its conclusion and improve their strategies accordingly.

Trading Systems and Methods (6th Edition, 2020, Wiley) — Perry J. Kaufman

How to Calculate MFE?

Maximum Favorable Excursion (MFE) measures the largest unrealized profit a trade achieves while it is still open.
Expressing MFE as a percentage allows consistent comparison across different assets, and averaging MFE% over multiple trades provides insights for realistic profit targets.

MFE% for a Single Trade

For a long trade:

MFE_{\text{long}\%} = \frac{HighestPrice - EntryPrice}{EntryPrice} \times 100

For a short trade:

MFE_{\text{short}\%} = \frac{EntryPrice - LowestPrice}{EntryPrice} \times 100

MFE% with Multiple Orders (Scaling In)

If you enter at multiple prices, calculate a Volume-Weighted Average Price (VWAP) for your blended entry:

VWAP = \frac{\sum(EntryPrice_i \times Size_i)}{\sum Size_i}

Then:

MFE_{\%} = \frac{|ExtremePrice - VWAP|}{VWAP} \times 100

Where:

ExtremePrice = Highest price (for long trades) or lowest price (for short trades) while the position was open
VWAP = Weighted average entry price based on trade size

For a stricter analysis, calculate MFE% from the first entry price.

Average MFE% Across Multiple Trades

To measure overall trade performance, calculate Average MFE% across N trades:

AvgMFE\% = \frac{\sum_{i=1}^{N} MFE_{i}\%}{N}

Where:

$MFE_{i}\%$ = MFE% for trade i
N = Total number of trades analyzed

Maximum Adverse Excursion: Analyzing Price Fluctuations for Trading Management (1996, Wiley) — John Sweeney

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Track Peak Potential: Max Favorable Excursion (MFE) helps you see the peak profit a trade achieved before reversing. Use it to identify patterns in missed opportunities.

Importance of Max Favorable Excursion in Trading

Maximum Favorable Excursion (MFE) is a valuable metric for evaluating the potential profit a trade could achieve before reversing. By analyzing MFE, traders can identify whether their exit strategies align with the actual price movements and refine their approach to maximize returns. It also helps in optimizing stop-loss and take-profit levels, ensuring they are realistic based on historical performance. Regularly reviewing MFE allows traders to adjust their strategies to better capture profits while minimizing missed opportunities.

Trading Systems and Methods (6th Edition, 2020, Wiley) — Perry J. Kaufman

Trading Examples

The following examples demonstrate how to calculate MFE (Maximum Favorable Excursion) using percentage-based metrics, scaling in, and averaging across trades. These scenarios help traders evaluate potential trade profitability beyond the final realized result.

Single Trade MFE%

A trader enters a long position at $100. The price climbs to a high of $108 during the trade before closing at $107.

Metric	Value
Asset	Stock XYZ
Entry Price	$100
Highest Price Reached	$108
Exit Price	$107 (Profit Target Hit)

Calculation:

MFE_{\text{long}\%} = \frac{108 - 100}{100} \times 100 = 8\%

Analysis:

The trade reached a maximum 8% unrealized profit.
Although it closed at a 7% gain, MFE% reveals the peak opportunity that could have been locked in.

Losing Trade MFE%

A trader enters a long position at $50. The price rises briefly to $53 before reversing sharply and hitting the stop-loss at $47.

Metric	Value
Asset	Stock ABC
Entry Price	$50
Highest Price Reached	$53
Exit Price	$47 (Stop Loss Hit)

Calculation:

MFE_{\text{long}\%} = \frac{53 - 50}{50} \times 100 = 6\%

Analysis:

The trade had a 6% potential gain before reversing.
This shows how MFE highlights missed opportunities even in losing trades.

Scaling In with VWAP

A trader scales into a position:

Buys 50 shares at $100
Buys 50 shares at $95

The highest price reached during the trade is $110.

VWAP Calculation:

VWAP = \frac{(100 \times 50) + (95 \times 50)}{50 + 50} = 97.5

MFE% Calculation:

MFE_{\%} = \frac{110 - 97.5}{97.5} \times 100 \approx 12.8\%

Analysis:

Based on VWAP, the trade peaked at 12.8% unrealized profit.
Calculating from the first entry ($100) would show a slightly lower 10% gain at the peak.

Average MFE% Across Multiple Trades

Trade #	Entry Price	Extreme Price	MFE%
1	$100	$108	8%
2	$50	$53	6%
3	$97.5 (VWAP)	$110	12.8%

Average MFE% Calculation:

AvgMFE\% = \frac{8 + 6 + 12.8}{3} \approx 8.9\%

Analysis:

On average, trades had a ~8.9% peak unrealized gain before resolution.
This metric helps set realistic profit targets aligned with actual price behavior.

Trade Comparison: Profitable vs Losing

Profitable Trade

Entry Price$100

Stop Loss$95

Highest Price Reached$108

Exit Price$107 (Profit Hit)

MFE%8%

Losing Trade

Entry Price$50

Stop Loss$47

Highest Price Reached$53

Exit Price$47 (Stop Hit)

MFE%6%

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Spot Unrealized Potential: Analyze MFE to understand whether your profit targets are too conservative. Fine-tuning your exit strategy can capture more of the market’s move.

Combining MFE with Other Tools

To gain deeper insights, MFE should be used with:

Max Adverse Excursion (MAE): Measures the maximum unrealized loss during a trade to balance risk-reward analysis.
Risk-Reward Ratio: Helps compare potential profits (MFE) to risks (MAE or initial stop-loss).
Position sizing Models: Ensures trades align with risk tolerance based on MFE insights.
Technical Indicators: Combine MFE analysis with tools like Fibonacci Retracement, moving averages, or RSI for better trade management.

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Balance Risk and Reward: High MFE values without corresponding exits can indicate overconfidence or poor risk management. Always balance potential gains with realistic outcomes.

Key Points

Profit Potential Indicator: Max Favorable Excursion (MFE) measures the highest unrealized gain a trade achieves while it is open, providing insight into potential profit opportunities.
Entry and Exit Optimization: MFE analysis helps refine entry and exit strategies by identifying whether profits are being captured effectively or left unrealized.
Risk-Reward Evaluation: Combine MFE with Max Adverse Excursion (MAE) to assess the balance between potential profits and risks for each trade.
Trailing Stop Adjustment: Use MFE data to fine-tune trailing stop levels, maximizing profit capture while minimizing the risk of giving back gains.
Strategy Validation: High MFE values relative to actual trade outcomes may signal inefficiencies in taking profits or poor trade management.
Market Context: MFE values can vary significantly based on market conditions; understanding these patterns helps adapt strategies for different environments.
Portfolio Insights: Aggregating MFE across trades or strategies highlights areas of underperformance or opportunities for improved profit-taking.
Support for Backtesting: Analyze historical MFE to validate strategy performance and identify potential improvements in trade execution.
Complement to Risk Metrics: Pair MFE with metrics like Risk-Reward Ratio and profit factor to gain a holistic view of trade quality.
Continuous Monitoring: Regularly track MFE in live trading to ensure strategies are capturing sufficient profit relative to market opportunities.

Conclusion

Max Favorable Excursion is a powerful tool for assessing a trade’s potential and refining strategies. By understanding MFE, traders can: set realistic profit targets, enhance trade management and learn from historical performance.

However, its limitations mean it should never be used in isolation. Pairing MFE with complementary tools like MAE and technical indicators leads to a more holistic trading approach.

Max Adverse Excursion Portfolio Metrics