Splitting your journal results by hour of entry

[Fairman]

Splitting your journal results by hour of entry

Most journals group results by setup or by pair. One split that's easy to add and often surprising is the hour you entered the trade.

To do it, you just need the entry time for each trade, which most platforms export. Group trades by hour, using a consistent time zone, and look at the number of trades, average R, and win rate for each hour. You don't need many trades per hour to start seeing whether some hours stand out, although with small samples it's better to look for big differences rather than reading much into small ones.

What people often find is that their results aren't spread evenly through the session. There may be an hour where most of the good trades come from, and another hour where trades are frequent but don't add much, or even lose. That might reflect the market, the strategy, or the trader's focus, such as getting tired late in the session.

What you do with it depends on what you find. If one hour is consistently weak, you might stop trading it, or trade it with smaller size, and then check whether that improves the overall results without giving up too much.

It takes maybe half an hour to set up in a spreadsheet with a pivot table, and then it's automatic.

[Fairman]

I'd recommend splitting by time zone of the market rather than your local time, especially if daylight saving changes affect you. If you're in a place that changes clocks on different dates from London or New York, your local hours shift relative to the sessions for a few weeks each year. Using London or New York time for the grouping keeps each hour comparable. Otherwise trades from the same session part can end up in different buckets depending on the time of year. Converting everything to one zone in the spreadsheet before grouping takes a few minutes.

[Fairman]

Another split that pairs well with this is day of the week. Some traders find Mondays or Fridays behave differently for their strategy, and combining day and hour can show something like a particular hour on a particular day being weaker. The catch is sample size. With day and hour combined, each group gets small quickly, so it's easy to see patterns that are just noise. I'd look at each split separately first and only combine them if both show something on their own. Patterns that show up in both splits are the ones to take more seriously.