Nobody decides to revenge trade. What happens is smaller and more mechanical than that: a loss closes, the next entry comes faster than usual, and it is a size the previous ten trades were not. By the time it has a name it has already cost money. The useful thing about the sequence is that every step of it leaves a mark in the journal, and none of them require you to remember your emotional state.
Four measurements, not one feeling
1. How fast you got back in
Take every trade that followed a closed loss and group it by the gap since that loss closed — under a minute, one to five, five to fifteen, longer. Then read the result of each band.
There is no correct number of minutes and anyone who quotes you one is describing themselves. What your record can say is whether your fastest re-entries did worse than the rest. If they did, you have a rule worth writing down, in your own numbers, and a much better chance of keeping it than a rule you borrowed.
2. How big the next one was
This is the most valuable comparison in a trading journal and one of the least often made. Group your trades by what happened immediately before — after a win, after a loss, first of the session — and compare the average position size of each group.
| Preceded by | Trades | Avg size | Net | Win rate |
|---|---|---|---|---|
| A win | 148 | 2.1 | +$3,910 | 57% |
| A loss | 131 | 3.8 | −$2,740 | 44% |
| First of session | 96 | 2.0 | +$1,480 | 55% |
Nearly double the size on the trades that follow a loss, and it is the only group losing money. Sizing up after a loss empties accounts far more reliably than being wrong about direction, because it changes the arithmetic of the recovery: a bigger loser needs a bigger winner, taken by someone who has just been proven wrong.
Ten MNQ and ten MCL are not the same bet — one is $2 a point and the other $100. A size comparison pooled across instruments mostly measures which instrument you traded that day. Split it, or compare against your own median on that instrument.
3. How deep into the session it was
Group trades by sequence position — first of the day, second, third, later — and compare. Some traders warm up and their later trades are their best. Others are following a plan for two trades and improvising after that.
Both patterns are common and the belief you hold about yourself is a poor guide to which one you are. It is a question about your record.
4. How many losses were already behind it
Related but distinct: not where in the day the trade sat, but how much had already gone wrong before it. Trades taken with one loss behind them, two, three or more. This is the cut that finds the day that got away — the one where each trade was a response to the one before it rather than to anything on the chart.
Watch the sample, not the story
These cuts divide an already modest journal into small groups, and a bucket holding six trades will happily show a striking result that means nothing. Read the trade count on every row before the rate. A pattern worth acting on shows up across dozens of trades, not across a bad Tuesday.
And note what these numbers do not establish: a correlation is not a mechanism. Bigger positions after losses may be revenge, or you may size up deliberately when a setup you have been waiting for finally appears — which happens to be more common after a quiet losing stretch. Your record tells you the pattern is there. Only you can say which explanation fits.
Seeing it day by day
The cuts above are aggregates over a whole journal. A month laid out as a calendar — each day coloured by its result, with its totals — answers the neighbouring question: are the bad days clustered?
Isolated red days scattered through a green month are the cost of doing business. Three consecutive red days, each worse than the last, is a different thing entirely, and it is visible instantly in a grid and almost invisible in a list sorted by date.
What to do with it
The useful output is not a resolution to be more disciplined. It is a specific, small rule drawn from your own numbers: no trade within five minutes of a loss closing, or never more than twice my median size, or stop at three losses. Rules that come from your record are easier to keep than rules that came from a book, because you have already seen what breaking them costs.
What Choptick shows you
Every one of these cuts is built in, computed from the same journal, net of commissions.
- After a win / after a loss / first of session — with average position size beside the money, which is the comparison that matters here.
- Re-entry timing — trades that followed a loss, grouped by how long after that loss closed.
- Trade of the day and losing runs — sequence position, and how much had already gone wrong.
- Automatic flags on the trades themselves — a letter on each trade in the log, with the reason in your own numbers: “back in 12 seconds after the last loss closed”, “40 contracts against your usual 2 on MNQ”.
- What each of those habits costs — every check you score on, worst first, with the money attached.
- A P&L calendar for the clustering, and a daily reflection that shows the session’s flags beside your own discipline rating.
- Every row is clickable — open it and see which trades are in it and why each one qualifies.
Figures in the examples are invented and illustrative. Nothing here is financial advice.