Maximum Favorable Excursion Calculator: Measure Entry and Exit Quality

Analyze MFE/MAE from your TradingView backtest CSV. See where to set stops and whether your exits leave money on the table. Free, client-side, no signup.

Calculate MFE / MAE Analysis From Your Trades

What Is MFE / MAE Analysis?

Maximum Favorable Excursion (MFE) measures how far a trade moved in your favor before it closed. Maximum Adverse Excursion (MAE) measures how far it moved against you. Together they reveal whether you are entering trades at the right moment and exiting at the right moment. Two questions that win rate and total P&L cannot answer on their own.

MFE says: "when this trade was good, how good did it get?" MAE says: "when this trade was bad, how bad did it get before it turned around (or stopped out)?" These are not hypothetical questions. Every trade traces a path, and MFE/MAE map the high and low points of that path relative to your entry.

Formula

MFE = max( High(i) - Entry, 0 ) (long trade) MFE = max( Entry - Low(i), 0 ) (short trade) MAE = max( Entry - Low(i), 0 ) (long trade) MAE = max( High(i) - Entry, 0 ) (short trade) Where: High(i) = highest price during the trade Low(i) = lowest price during the trade Entry = fill price of the trade Derived metrics: Entry Efficiency = MFE / (MFE + MAE) (what fraction of the total excursion was in your favor) 1.0 = the trade never moved against you 0.5 = the price oscillated evenly around entry 0.0 = the trade moved against you the whole way Exit Efficiency = PnL / MFE (what fraction of the maximum favorable move you captured) 1.0 = you exited at the exact high 0.5 = you captured half the move Negative = you held past the high and gave back profit

How to Read This Number

Think of MFE and MAE as a two-dimensional lens on your trading.

High MFE with high MAE means the trade swung wildly: it went far against you, then far in your favor, or vice versa. That usually means a wide stop-loss saved you but your entry timing was loose. Low MFE with low MAE means the trade was quiet, which is common in scalping or tight range strategies.

Entry Efficiency tells you whether your entries are well-timed. An entry efficiency above 0.6 means most of the price movement after you entered was favorable. Below 0.4 suggests you are chasing moves. Exit Efficiency tells you whether your exits leave money on the table. An exit efficiency above 0.8 means you are catching most of the move. Below 0.5 means you are consistently leaving two-thirds of the potential profit behind.

The scatter plot (MFE vs. MAE for every trade) is the most informative view. A cluster in the top-left quadrant means trades shot far in your favor with little adverse movement. Ideal entries. A cluster in the top-right means trades went against you hard before finally working out. Your stops may be too wide.

What Counts as Good?

RangeValueWhat It Means
Excellent EntryEntry Efficiency > 0.70Trades move in your favor soon after entry. You are not chasing momentum; your entries catch the early part of the move.
Good EntryEntry Efficiency 0.50 to 0.70Acceptable timing. About half to two-thirds of the total excursion is favorable. Room for refinement but not a red flag.
Poor EntryEntry Efficiency < 0.50More than half the excursion is adverse. You are entering too late: the move was mostly over before you got in, or you are buying into resistance or selling into support.
Excellent ExitExit Efficiency > 0.80You capture most of the favorable move. Your take-profit logic, trailing stops, or manual exits are well placed.
Fair ExitExit Efficiency 0.50 to 0.80You leave a meaningful portion of the move on the table. Consider tighter profit targets or trailing stops to capture more. Not bad, but improvable.
Poor ExitExit Efficiency < 0.50You routinely give back more than half the favorable excursion. This is where most profitability leaks happen. Tighten your exit strategy and consider partial profit-taking.

How Pineify Calculates MFE / MAE Analysis

The first time I uploaded my own TradingView CSV to Pineify, the backtest on EURUSD showed a 62% win rate and a 1.8 profit factor. I was ready to deploy. Then I looked at the MFE/MAE tab. My entry efficiency was 0.38. My exit efficiency was 0.45. The strategy was not "good." It was lucky, and about to stop being lucky. I had been entering after the first big bar and exiting on a trailing stop that was too wide. The scatter chart made it obvious: the trades that won did so by a thin margin, and the losing trades went way past my stop before reversing. Pineify computes MFE, MAE, entry efficiency, and exit efficiency from every trade in your TradingView CSV automatically. You get the scatter plot, a summary table by trade, and annotated ranges so you can see at a glance whether your entry or exit is the weak link. No coding, no Python, no downloading OHLC data. Everything runs from the trade list your Strategy Tester already exported. The CSV stays on your device. A note on data quality: MFE/MAE is most useful with at least 50 trades. Below that the scatter plot is too sparse to see patterns, and one outlier trade can dominate the averages. Also, MFE depends on bar-level data quality. If your backtest uses a 1-hour timeframe but entries happen on tick precision inside the bar, the true excursion is wider than what the high/low of that bar captures. Pineify uses the close-high-low data from the exported trade list, which matches what TradingView records in the Strategy Tester. If you tested on a high timeframe (daily or above), the bar-level high/low may hide intra-bar excursion, so treat the numbers as a floor rather than the full picture.

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