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Logging early exits and the reason you gave yourself

Most journals record when a trade closed and at what price. Few record why, when the trade was closed before its stop or target. Early exits are a category of their own and they deserve a column.

A trade that you closed by hand, ahead of plan, could be good discipline or plain fear. In the moment it always feels justified. The journal is where you find out which one it was.

Add two fields. One for the reason in a few words, written right after closing, like momentum stalled, news in two minutes, couldn't watch, felt wrong. One for what happened afterwards: did price go on to hit the target, hit the stop, or neither?

After a month or two, sort the early exits by reason. Some reasons will turn out to protect you, like closing before news. Others, like felt wrong, will often show price going on to the target. That's the reason to work on.

It's also useful to total up the R you gave up or saved with early exits. That number is often a surprise, and it settles arguments with yourself about whether your management helps or hurts.

Write the reason immediately, before looking at what price does next. If you wait even ten minutes, you'll know whether the exit was right, and the reason you write will bend to fit. Thirty seconds after closing is the honest window. A quick note in the platform's comment field or a voice memo works if the journal is too slow to open. The goal is to capture what you actually thought at the moment, not what makes sense afterwards when you already know the answer. The platform comment field is underused for exactly this.

Separate partial closes from full early exits. Taking half off at a level before the target might be part of the plan, and that's not an early exit. Closing the remaining half because you got nervous is. If you mix the two, the stats get muddy and you can't tell whether the plan or the deviation is responsible for the result. A basic tag for planned partial and unplanned exit keeps them apart and makes the monthly review much cleaner and more useful. The tags take a second each and save a lot of confusion later.

Check what the alternative would have been with real numbers. For each early exit, note the R at exit and the R the trade would have reached under the original plan, whether that was the target or the stop. The difference is the cost or benefit of the early exit. Adding these up over a month gives one number. If it's clearly negative, your early exits are costing you, and the default should be to let trades run. If it's positive, your instincts might be better than the plan in certain spots.

Look at whether early exits happen more often on certain pairs or in certain sessions. Many traders exit early much more on fast pairs like GBPJPY or gold, where the swings feel bigger, or late in the session when they want to finish. If the pattern is strong, the fix might be structural, like smaller size on those pairs so the swings feel less threatening, or a firm session end that stops new trades early enough that you don't need to rush the open ones. Both are easy changes once the journal shows the pattern clearly.

A reason column for early exits is a great addition. Adding the time of the exit next to the reason makes it even more useful. Early exits tend to cluster, for example in the minutes before US data or around 12:00 London when the morning move stalls. If the reason says nervous and the time says 13:28, the exit may have been sensible. If the reason says nervous and the time says 09:10, in the middle of a clean move, that is more likely fear. After a month the pattern is usually clear.

A scalp is up two pips with a target of five. Price twitches back a pip. The trade gets closed at plus one. A few seconds later, price runs to the target and beyond.

This is micro-win bias: the urge to lock in small gains before they vanish. It's a result of loss aversion, where giving back unrealized profit hurts more than the gain pleased. On short timeframes, where fluctuation is constant, the pull is relentless.

The mathematical effect is brutal. If average winners shrink to one or two pips while losers stay at the full stop distance, the win rate would need to exceed what the strategy produces.

Backtest results rely on trades running to the target. Live behavior deviates, and the live equity curve falls short with no obvious reason.

An audit helps. Compare the intended exit with the actual exit for every trade. Count how many were closed manually before the target. Calculate what the result would have been had they run.

If the sum is large, the strategy's edge is being cut by hand. Automated exits, such as a bracket order placed at entry, remove the temptation.

There is a numerical way to see how costly the habit is. Suppose the plan is a 5-pip target and a 5-pip stop, with a 55 percent win rate. The expectancy is positive. Now suppose half the winners are closed early at 2.5 pips while the stops stay at 5. The expectancy shifts, and the strategy turns slightly negative once costs are included.

The effect isn't visible in the win rate, which may even increase, since early exits turn more trades into wins. It's visible in the average winner, which shrinks.

A good diagnostic is a histogram of winning trade sizes. If the plan has a fixed target, there should be a spike at the target. A spread of results below it means exits are being done by hand.

Fixes include placing the take-profit order at entry and not touching it, or using a rule that allows moving the stop but not the target.

What fraction of winning trades were closed before the planned target?

One thing that would make the early-exit column actionable rather than just a record: convert each early exit into the R it gave up, measured against the original plan. Then split it by the reason you wrote at the time. The interesting split is not "early exits were good" or "early exits were bad" in general, but which reasons paid and which cost. In my experience the reason written as "felt wrong" and the reason written as "news in two minutes" behave very differently once they are counted in R, and only one of them is worth keeping as a rule.

TradeLock wrote: Sun Nov 01, 2026 3:30 am One thing that would make the early-exit column actionable rather than just a record: convert each early exit into the R it gave up, measured against the original plan. Then split it by the reason you wrote at the time. The interesting split is not "early exits were good" or "early exits were bad" in general, but which reasons paid and which cost. In my experience the reason written as "felt wrong" and the reason written as "news in two minutes" behave very differently once they are counted in R, and only one of them is worth keeping as a rule.

Yeah, but on another hand how to backtest such strategy?