Revenge trading: how to recognise it in your own data

Revenge trading is taking a trade to win back a loss rather than because your setup is present. Almost every trader recognises the description. Far fewer can say how often they do it, because in the moment it rarely feels like revenge — it feels like an opportunity.

It leaves traces

The good news is that revenge trading has a shape in the data, even when you did not label it at the time. Three traces are worth looking for.

• Timing: a new entry shortly after a losing trade closes.
• Size: a position larger than your usual size, following a loss.
• Frequency: more trades than usual on days that started badly.

Why your own baseline matters

There is no universal threshold. A scalper who takes twenty trades a day re-enters within minutes as a matter of course; for a swing trader, a second entry the same hour is unusual. Measuring against a fixed rule would flag one trader constantly and the other never. The useful comparison is against what is normal for you.

Measure the cost

Once you can identify the trades that followed a loss quickly, compare their results with the rest. If they perform noticeably worse — in R, not just in rupees — you have found a habit with a price. If they perform the same, the timing may not be the problem.

Label it when it happens

Detection after the fact is useful; a tag recorded at the time is better. If you catch yourself entering to recover a loss, tag the trade. Over a few months those tags become the most honest record of your trading you have.

TradeDrift checks every trader’s history for revenge entries, size escalation and overtrading, each judged against that trader’s own baseline, and shows the trades behind each finding.