Use this post-trade review workflow after a paper-trading exit to compare the result with the thesis, evaluate rule fit, tag behavior, inspect risk, and decide what should change.
A post-trade review is strongest when it compares the result against the pre-trade note. Profit and loss can be misleading in a small paper sample. The more useful question is whether the agent followed the rules, whether the thesis made sense, whether risk stayed inside limits, and what one process adjustment is justified.
| Step | Review question | Useful output |
|---|---|---|
| 1. Record the result | What happened in paper mode, including exit reason and result? | A clean journal event with context. |
| 2. Compare with thesis | Did the market behave the way the pre-trade note expected? | A thesis quality note, not just PnL commentary. |
| 3. Review rule fit | Did the agent follow watchlist, sizing, cadence, invalidation, and market-frame rules? | A pass, fail, or ambiguous rule-fit tag. |
| 4. Tag behavior | Was there overtrading, late reaction, ignored context, or good discipline? | A repeated pattern you can measure later. |
| 5. Choose action | Should the rule change, the watchlist change, risk change, or more evidence be collected? | A specific next step for the paper workflow. |
Original thesis: The agent was practicing breakout continuation after a pre-defined confirmation.
Result: The simulated trade exited at the target, but the entry happened before the confirmation rule was met.
Useful review: Tag the trade as profitable but rule-violating. Do not loosen the rule just because the result worked.
The post-trade review is only useful if the thesis and invalidation were written before the simulated decision. Start with the pre-trade review workflow or the trade entry checklist.
Do not promote a paper result into a live-capital conclusion. Compare decisions across sample size, drawdown, context, and rule consistency first.
Use a small tag set so reviews stay comparable. Good tags include rule-compliant, rule-violating, early entry, late entry, ignored invalidation, good patience, overtrading, oversized, and insufficient sample. The same tags should appear across the crypto journal and feedback loop.
A scorecard helps separate a good outcome from a good process. Review thesis clarity, invalidation quality, paper size discipline, agent rule fit, alert behavior, exit quality, and the usefulness of the next action. A profitable result with weak notes can receive a low process score, while a losing trade that followed a clear rule can still be valuable evidence.
The scorecard does not need to be complicated. A pass, fail, or unclear tag for each field is enough to make repeated problems visible across the journal.
Use the same scorecard fields across similar paper trades. Consistency matters more than precision because the goal is to see repeated process issues over time.
If a field is unclear, do not fill in the gap from memory. Mark it unclear and decide whether the pre-trade template needs a better required field.
The action log should capture why the next step was chosen. That note becomes part of the next pre-trade review and prevents the same lesson from being rediscovered later.
Over time, the action log should show fewer vague changes and more narrow improvements tied to repeated journal evidence.
A useful post-trade review includes the original thesis, exit result, rule fit, behavior tag, risk review, and one specific next action for the paper-trading process.
No. A profitable paper trade may still be a bad process sample, and one result is usually too small to justify a rule change without supporting evidence.
Review soon enough that context is fresh, but use the written pre-trade note instead of memory. Delayed reviews are still useful when the original thesis and evidence are complete.
This workflow is for paper-trading analysis and journaling. It does not provide financial advice or predict future trading performance.