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A column for minutes held, and what short and long holds tell you

I've been logging how long each trade was open, in minutes, from entry to exit. It's a simple number but it shows patterns I didn't expect.

When I group trades by hold time, the picture can look very different from the overall results. For example, trades closed within 2 minutes might show a low win rate because they're mostly stopped out quickly. Trades held 5 to 15 minutes might be the main source of profit. Trades held over 30 minutes might be breakeven or slightly negative, because they're often trades that didn't work but weren't stopped.

Illustrative breakdown, to show the format rather than my data:
0 to 2 minutes, 40 trades, win rate 35%, average result minus 1.2 pips.
2 to 15 minutes, 80 trades, win rate 60%, average plus 1.8 pips.
15 to 60 minutes, 30 trades, win rate 47%, average plus 0.2 pips.

If your data looks anything like this, the long holds deserve attention. Maybe a time stop, closing anything not in profit after 15 minutes, would improve things.

MT5 history has open and close times, so the column can be filled automatically from an export.

Grouping by hold time is very revealing. In my own logs, the longest holds were often trades where I moved the stop or hoped for a recovery, as you suggest. A rule that closes any trade still near entry after a set time, for example 20 minutes on M5, can remove many of those weak results. It is also worth checking whether the very short holds are mostly stopped out by spread spikes or by real moves, since the fix is different in each case.

A time stop test is easy to run from the journal. For each trade held over the threshold, look at the price at the threshold time and calculate what the result would have been if closed then. Comparing that with the actual result tells you whether a time stop would have helped, without needing a full backtest. It does need the price at that time, which you can get from M1 data. If a time stop improves results on past trades, run it live for a while before trusting it fully, since past trades were managed knowing there wasn't a time stop.

Hold time also interacts with session. A trade opened at 13:25 London and held 10 minutes runs into US data at 13:30. Its hold time looks normal but the result was decided by the news. Tagging trades that crossed a scheduled event helps separate these out, so they don't confuse the hold time picture. Tagging these trades as news-affected keeps them from distorting the averages. They can then be reviewed separately. If news trades are consistently worse, avoiding entries close to events might help. If they're better, consider the opposite. Either way, the tag makes the question answerable.

For prop accounts, hold time matters for rules too. Some firms have minimum hold times, like trades must be open at least a minute, to stop certain kinds of arbitrage. Logging hold time shows whether any trades fall under that threshold, which could matter in a review. A minimum hold rule is usually about one or two minutes, but it varies. If your trades often last under a minute, check whether this applies to your firm. Some firms only care about it in combination with other patterns, like many trades opened and closed in seconds. Reading the rule text and asking support if it's unclear avoids surprises.

One more use: comparing planned and actual hold times. If your system expects trades to reach targets within 10 minutes and the average winner takes 25, the market might be slower than when you designed the system. That's a sign to check whether targets should be smaller or the session choice adjusted. Market speed changes over time. A period of low volatility can make everything take longer, while busy markets compress hold times. If hold times have shifted a lot, it's a sign the market is different, and system parameters might need adjusting. The hold time column is a cheap way to see that shift.