Post-Trade Review
Learn how to review trades by process before outcome, separate controllable errors from variance, and convert repeated mistakes into evidence-based improvements.
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Post-trade review evaluates whether a decision followed the intended process, what was controllable, and whether repeated evidence supports changing the strategy.
Learning objectives
- Grade setup, risk and execution separately from P&L.
- Distinguish controllable errors from uncontrollable market outcomes.
- Aggregate repeated issues before changing rules.
What it is
A post-trade review compares what actually happened with the plan documented before entry. It should ask whether the setup qualified, risk was sized correctly, execution matched the chosen method and exits followed the rules.
The first question is process, not "why did I lose?" A valid trade can encounter adverse news or normal randomness. Searching for a special explanation after every loss encourages overfitting.
Likewise, a profitable rule breach should be recorded as a process failure. Rewarding it because it made money can reinforce behaviour that creates larger future tail losses.
How to structure a review
Grade the decision in layers: setup quality, position/risk compliance, execution quality and exit compliance. A simple score such as pass/fail or 1-5 is enough if definitions remain stable.
Classify deviations as controllable or uncontrollable. Slippage beyond a realistic estimate may be partly market-driven; entering the wrong size is directly controllable. The distinction helps target improvement.
Write one counterfactual carefully: what would have happened if the documented rule had been followed? This is useful for repeated breaches but should not become endless hindsight optimisation.
Aggregate errors by category. One late entry may be noise; ten late entries concentrated after social-media alerts indicate a recurring process problem worth addressing.
Review framework
| Area | Question | Evidence |
|---|---|---|
| Setup | Did the trade qualify before entry? | Compare chart/data and checklist with plan criteria. |
| Risk | Was planned loss and portfolio exposure inside limits? | Use recorded size, stop and open-risk data. |
| Execution | Did fills and orders match the execution plan? | Compare intended and actual prices, slippage and fees. |
| Exit | Was the trade managed according to rules? | Review stop, target, trailing and discretionary changes. |
Worked example and thought exercise
Trade A follows every setup, sizing and execution rule and loses -1R. Trade B fails the checklist, uses double normal size and wins +3R.
A strong review can grade Trade A highly and Trade B poorly. If the trader rewards Trade B solely because of P&L, the review encourages exactly the behaviour the risk framework was designed to prevent.
Thought exercise: why can changing a rule after one compliant -1R loss make a strategy worse even when the proposed change would have avoided that specific loss?
Common mistakes and practical workflow
- Assuming every loss contains a unique lesson.
- Ignoring profitable rule breaches.
- Reconstructing the original thesis after seeing the outcome.
- Changing strategy from isolated examples instead of repeated evidence.
Practical workflow
- Retrieve the pre-trade plan and journal record.
- Grade setup, risk, execution and exit before focusing on P&L.
- Classify deviations as controllable or uncontrollable.
- Tag recurring errors using stable categories.
- Change rules only when a meaningful sample supports the change.
Knowledge checkpoint
- Why should process be reviewed before outcome?
- Can a winning trade receive a poor review score?
- What is the difference between controllable error and market variance?
- Why aggregate errors before changing strategy?
FAQs
❓ Does every loss need a lesson?
No. Losses are normal in probabilistic strategies; sometimes the correct lesson is that the process was followed.
❓ Can a winning trade be a bad trade?
Yes. A rule-breaking decision can be poor even when the market outcome is favourable.
❓ When should a rule change?
When repeated evidence from an adequate sample shows the current rule is inferior or no longer fits market structure.
❓ What is outcome bias?
It is judging decision quality mainly by whether the result happened to be good or bad.
Summary
Post-trade review should reward repeatable decision quality, identify controllable leaks and use aggregated evidence for change. P&L is important, but it is not a sufficient score for the decision.
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