Most traders review a day by glancing at the P&L, feeling good or bad, and moving on. That habit reinforces whatever happened to work, including luck. A $1,000 gain from breaking every rule teaches the wrong thing, and a $100 loss from a stop placed exactly where the plan said can be the best trade of the week. Reviewing properly means separating how you decided from what the market did afterward.
Here's a five-step review you can run on paper or in a spreadsheet. Software can organize the records, but the useful part is checking your decisions against rules you wrote before the trade.
1. Grade process separately from outcome
Give each trade two scores: a decision score and an outcome. The decision score asks whether the setup matched your written criteria, whether the stop was set before entry, whether size matched your rule, and whether you stayed with the plan once in. Outcome is just the dollars or R.
A hypothetical example. Four trades in a session:
| Trade | Followed rules? | Result | Lesson |
|---|---|---|---|
| 1 | Yes | -1R | Fine. Variance. |
| 2 | No, entered early | +2R | Lucky. Don't repeat. |
| 3 | Yes | +1.5R | Fine. |
| 4 | No, moved stop | -2.5R | Real mistake. |
Net is zero R, but two of four trades broke rules. The net number hides that. Tracking rule adherence over time shows where your attention should go. Which process measures you track is your call; common ones are rule adherence, R-multiple achieved against R planned, how far price moved against you before the exit, and whether you skipped valid setups.
2. Compress the day into a few lines
Your next step
Build the daily map before the session.
See how ES and NQ Key Price Levels fit the daily plan. Follow the room, practice in SIM, and review what happened around each level.
A trading day produces more notes than you'll reread. At the end of the session, reduce it to a short entry: one thing that confirmed a rule, one rule that needs changing, one mistake to prevent tomorrow, and any limit you came close to breaking. Whatever tool you use, the test is whether you can read it in under two minutes before the next session.
3. Scope each lesson to its context
One failed breakout becomes "never trade breakouts," which is usually an overreaction to one sample. Instead, tag each lesson with the conditions it applies to:
- Setup type: breakout, pullback, failed breakdown, mean reversion
- Condition: trending day, balanced chop, news-driven session
- Time window: opening range, midday, final hour
- Your state: planned, impulsive, revenge, or skipped
"Breakouts fail" gives you nothing to test. "Breakouts I took in the first minutes after a news release were entered without my criteria" is a narrow, testable statement. Keep in mind that a handful of trades can't prove an edge in either direction. The goal at this stage is to generate specific hypotheses, not conclusions.
4. Keep risk limits fixed
Reviews should never loosen risk rules in the same session you break them. If a lesson suggests changing max size, daily loss limit or stop requirement, write it down and apply it only after a deliberate decision, not after a good or bad day. A system that raises size after a winning streak is automated overconfidence. If a tool suggests a lesson, review the evidence before changing any risk limit. A suggestion isn't permission to increase risk.
5. Write tomorrow's plan from the review
The last step is what makes the review worth the time. Before the next session, list which setups are valid, which conditions call for waiting, your daily loss limit in dollars, and the single mistake you're watching for. Then at the end of that session, grade against it. If the review never changes a decision the next morning, it's a diary.
Run the five steps for two weeks and look at the pattern in rule breaks, not the equity curve. That tells you what to fix first.
About the Author
Founder, Young Money Investments · Quant Trader
Cameron trades ES, NQ, and futures across multiple market cycles. He founded Young Money Investments to teach systematic, data-driven trading and manages Magnum Opus Capital. His work emphasizes documented rules, risk controls, and review over outcome promises.
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