Most traders can tell you exactly where they got in and exactly where they got out. Ask them how far the trade ran in their favour before it turned, or how deep it dug against them before it came good, and you get a shrug. That gap is where the two most useful numbers in your journal live, and most people never write them down. MAE and MFE describe what happened inside a trade, not just at the two edges you already record. They are unglamorous, they take about thirty seconds a trade to note, and they will sharpen where you put stops and targets faster than almost anything else you track. What MAE and MFE actually mean MAE is Maximum Adverse Excursion. It is the worst unrealised loss a trade showed while it was open. If you bought EURUSD at 1.0850 and price dipped to 1.0820 before closing at 1.0900, your MAE was 30 pips, even though the trade was a winner. It measures the deepest heat you sat through. MFE is Maximum Favourable Excursion. It is the best unrealised profit a trade showed before you closed it. Same trade: if price touched 1.0930 before pulling back to your 1.0900 exit, your MFE was 80 pips. You captured 50 of the 80 that were on offer. Record them in whatever unit you use for everything else, whether that is pips, points, ticks, or R. Logging them in R (multiples of the risk you took on entry) is the version that travels best, because it puts a gold trade and a EURUSD trade on the same axis. If R is new to you, the risk reward ratio is the same idea measured before the trade rather than after. Why the space between entry and exit matters Your entry and your exit are decisions. MAE and MFE are the reality the market actually offered you between those decisions. A trade can be a winner and still tell you your stop was badly placed. A trade can hit your target and still tell you that target cost you two thirds of the move. You cannot see any of that from the profit and loss column alone, which is why it belongs alongside the other journal metrics that matter . MAE tells you whether your stop is in the right place Collect the MAE of your winning trades and look at the spread. If your winners almost never go more than 0.4R against you before working, a full 1R stop is loose. You are risking more than the trade needs, which caps your position size for no benefit. Tighten the stop and the same setup risks less per attempt. The opposite pattern is just as common. If you keep getting stopped out at 0.8R and then watch the trade run to target without you, your stop is sitting inside the noise the setup normally produces. That is the data that finally lets you stop fiddling mid trade, which is a different problem covered in moving your stop loss . MFE tells you whether you are leaving money on the table Now do the same with MFE. If your trades routinely show 3R of open profit but you bank an average of 1R, your exit is the leak, not your entry. The setup is finding the move. You are getting out before it finishes. The fix might be a trailing stop, a partial scale out, or simply a wider target, but you only know the gap exists because you measured it. The reverse matters too. If your MFE and your realised result are almost identical, you are getting close to the maximum a trade offers, and the honest read is that your exit is already efficient. Chasing a few more pips there is a smaller prize than fixing an entry that shows 4R of heat on winners. How to record them without making journaling a chore For each closed trade, note two extra prices: the furthest price against you and the furthest price in your favour while the position was live. On most charting platforms you can eyeball the wick extremes on the timeframe you traded. Convert each to R using the same stop distance you risked, and you have both numbers. Better still, let software do it. A journal that stores your entry, stop, and exit can calculate MAE and MFE from price data automatically, which is one of the things TradeSave+ tracks per trade so the excursion numbers build up without extra typing. Automating the capture is the difference between a habit that survives a busy week and one that quietly dies. Read the distribution, not the single trade One trade's MAE tells you nothing. You want a sample, ideally thirty to fifty trades of the same strategy, before you draw a line under anything. Split the sample by outcome and look at the averages: average MAE on winners, average MAE on losers, average MFE on winners. The interesting signal is usually the difference between those groups, not any single figure. A clean example: if the average MAE on your winners is 0.5R and the average on your losers is 0.9R, there may be an early exit rule hiding in your data. Trades that end up losing tend to show more heat sooner. That is a hypothesis to test, not a rule to adopt blindly, but it started as a column in a spreadsheet. Patterns worth watching for Winners with high MAE. Your setup works but you are entering early or into a zone that gets tested hard. Consider waiting for confirmation, or accept the heat and size accordingly. Big MFE, small realised profit. The classic exit leak. The move is there and you are not holding it. MAE clustered just past your stop. A sign your stop is a magnet parked exactly where the market likes to poke before reversing. Losers with low MFE. These trades never went anywhere. Often a filtering problem at entry rather than an exit problem. Where these numbers are useful and where they are not MAE and MFE are at their best for calibrating stops, targets, and position size against how your setups actually behave. They turn vague feelings (I always get stopped at the low) into a distribution you can act on. They are also honest about exit discipline in a way that a win rate never will be. They are weaker as an entry signal on their own, and they mean little on a handful of trades or on a strategy you keep changing every week. They describe how your current process behaves. If the process is a moving target, the numbers just measure the churn. Keep the strategy stable, log the excursions the same way every time, and review them in the same weekly pass you use for the rest of your trades. None of this needs new software or a maths degree. It needs two extra prices per trade and the discipline to look at them in bulk. Do that for a month and your exits stop being a mystery. They start telling you, trade after trade, exactly where your plan and the market disagree.
MAE and MFE explained: what your exits are actually telling you
You already log your entry and exit. MAE and MFE are the two numbers in between that tell you whether your stops and targets are in the right place.
Most traders can tell you exactly where they got in and exactly where they got out. Ask them how far the trade ran in their favour before it turned, or how deep it dug against them before it came good, and you get a shrug. That gap is where the two most useful numbers in your journal live, and most people never write them down. MAE and MFE describe what happened inside a trade, not just at the two edges you already record. They are unglamorous, they take about thirty seconds a trade to note, and they will sharpen where you put stops and targets faster than almost anything else you track. What MAE and MFE actually mean MAE is Maximum Adverse Excursion. It is the worst unrealised loss a trade showed while it was open. If you bought EURUSD at 1.0850 and price dipped to 1.0820 before closing at 1.0900, your MAE was 30 pips, even though the trade was a winner. It measures the deepest heat you sat through. MFE is Maximum Favourable Excursion. It is the best unrealised profit a trade showed before you closed it. Same trade: if price touched 1.0930 before pulling back to your 1.0900 exit, your MFE was 80 pips. You captured 50 of the 80 that were on offer. Record them in whatever unit you use for everything else, whether that is pips, points, ticks, or R. Logging them in R (multiples of the risk you took on entry) is the version that travels best, because it puts a gold trade and a EURUSD trade on the same axis. If R is new to you, the risk reward ratio is the same idea measured before the trade rather than after. Why the space between entry and exit matters Your entry and your exit are decisions. MAE and MFE are the reality the market actually offered you between those decisions. A trade can be a winner and still tell you your stop was badly placed. A trade can hit your target and still tell you that target cost you two thirds of the move. You cannot see any of that from the profit and loss column alone, which is why it belongs alongside the other journal metrics that matter . MAE tells you whether your stop is in the right place Collect the MAE of your winning trades and look at the spread. If your winners almost never go more than 0.4R against you before working, a full 1R stop is loose. You are risking more than the trade needs, which caps your position size for no benefit. Tighten the stop and the same setup risks less per attempt. The opposite pattern is just as common. If you keep getting stopped out at 0.8R and then watch the trade run to target without you, your stop is sitting inside the noise the setup normally produces. That is the data that finally lets you stop fiddling mid trade, which is a different problem covered in moving your stop loss . MFE tells you whether you are leaving money on the table Now do the same with MFE. If your trades routinely show 3R of open profit but you bank an average of 1R, your exit is the leak, not your entry. The setup is finding the move. You are getting out before it finishes. The fix might be a trailing stop, a partial scale out, or simply a wider target, but you only know the gap exists because you measured it. The reverse matters too. If your MFE and your realised result are almost identical, you are getting close to the maximum a trade offers, and the honest read is that your exit is already efficient. Chasing a few more pips there is a smaller prize than fixing an entry that shows 4R of heat on winners. How to record them without making journaling a chore For each closed trade, note two extra prices: the furthest price against you and the furthest price in your favour while the position was live. On most charting platforms you can eyeball the wick extremes on the timeframe you traded. Convert each to R using the same stop distance you risked, and you have both numbers. Better still, let software do it. A journal that stores your entry, stop, and exit can calculate MAE and MFE from price data automatically, which is one of the things TradeSave+ tracks per trade so the excursion numbers build up without extra typing. Automating the capture is the difference between a habit that survives a busy week and one that quietly dies. Read the distribution, not the single trade One trade's MAE tells you nothing. You want a sample, ideally thirty to fifty trades of the same strategy, before you draw a line under anything. Split the sample by outcome and look at the averages: average MAE on winners, average MAE on losers, average MFE on winners. The interesting signal is usually the difference between those groups, not any single figure. A clean example: if the average MAE on your winners is 0.5R and the average on your losers is 0.9R, there may be an early exit rule hiding in your data. Trades that end up losing tend to show more heat sooner. That is a hypothesis to test, not a rule to adopt blindly, but it started as a column in a spreadsheet. Patterns worth watching for Winners with high MAE. Your setup works but you are entering early or into a zone that gets tested hard. Consider waiting for confirmation, or accept the heat and size accordingly. Big MFE, small realised profit. The classic exit leak. The move is there and you are not holding it. MAE clustered just past your stop. A sign your stop is a magnet parked exactly where the market likes to poke before reversing. Losers with low MFE. These trades never went anywhere. Often a filtering problem at entry rather than an exit problem. Where these numbers are useful and where they are not MAE and MFE are at their best for calibrating stops, targets, and position size against how your setups actually behave. They turn vague feelings (I always get stopped at the low) into a distribution you can act on. They are also honest about exit discipline in a way that a win rate never will be. They are weaker as an entry signal on their own, and they mean little on a handful of trades or on a strategy you keep changing every week. They describe how your current process behaves. If the process is a moving target, the numbers just measure the churn. Keep the strategy stable, log the excursions the same way every time, and review them in the same weekly pass you use for the rest of your trades. None of this needs new software or a maths degree. It needs two extra prices per trade and the discipline to look at them in bulk. Do that for a month and your exits stop being a mystery. They start telling you, trade after trade, exactly where your plan and the market disagree.