Investment Journal Review
Own learning after a decision. Support two modes: a single-decision postmortem and a multi-decision pattern review. Never judge process solely from P&L.
Read references/journal-protocol.md. Use scripts/journal_metrics.py for a normalized trade CSV when available. Use $probabilistic-market-forecast scoring for matured probability records and $investment-thesis-tracker for evidence deltas.
Workflow
- Freeze provenance. Preserve the original timestamped thesis, evidence cutoff, forecast, entry/exit plan, size, loss limit and any amendments. Never edit the old record; append review fields.
- Reconstruct execution. Record actual entry/exit, fees, spread/slippage, partial fills, holding time, deviations and whether the planned invalidation or review rule was observable.
- Separate four outcomes. Classify good process/good outcome, good process/bad outcome, bad process/good outcome and bad process/bad outcome. Luck does not repair a broken process; a valid process can lose.
- Score the forecast. When a probability or interval matured, compare the frozen forecast with the realized outcome and a declared naive/market benchmark. Preserve unresolved or early-closed cases separately.
- Diagnose cause. Distinguish research/evidence, thesis, timing, sizing, portfolio concentration, product mechanics, execution, discipline and unforeseeable shock. Avoid vague labels such as “emotion” without observable behavior.
- Analyze patterns. Normalize P&L by planned risk (
R) and segment only when sample size permits. Compare repeated errors, regime, horizon, strategy and instrument; report missing data and selection bias.
- Change little. Recommend at most one or two falsifiable process changes for the next sample, with a measurement and review date. Do not optimize rules to explain the past perfectly.
Hard rules
- Never use later information to claim it should have been known at the original cutoff.
- Never celebrate a rule-breaking winner as a good decision.
- Never infer skill from a handful of trades, one regime or selected successes.
- Include costs, abandoned ideas and no-trade decisions when available; survivor-only journals overstate quality.
- Do not respond to losses by automatically increasing risk, leverage or trading frequency.
Output
For one decision: original plan, evidence available then, execution delta, process/outcome quadrant, forecast score, cause, retained lesson and one next experiment.
For a journal: coverage/sample warnings, expectancy in R, win/loss distribution, drawdown, process adherence, forecast calibration when available, recurring strengths/errors, regime dependence and one or two measurable changes.
1---2name: investment-journal-review3description: Review one completed investment/trade or a journal of many decisions while preserving the original plan, separating process quality from profit/loss, testing thesis and forecast accuracy, identifying repeated evidence/sizing/execution errors, and proposing one or two measurable improvements. Use for post-trade reviews, recommendation scorecards, “why did this lose”, “what am I doing wrong”, and Turkish intents such as “işlem günlüğümü analiz et”, “işlem sonrası analiz”, “tahminlerin ne kadar tuttu”, “zararımdan ders çıkar”, “geçmiş al-satları incele”. Do not rewrite the original plan with hindsight or infer a stable edge from a small sample.4---56# Investment Journal Review78Own learning after a decision. Support two modes: a single-decision postmortem and a multi-decision pattern review. Never judge process solely from P&L.910Read [references/journal-protocol.md](references/journal-protocol.md). Use `scripts/journal_metrics.py` for a normalized trade CSV when available. Use `$probabilistic-market-forecast` scoring for matured probability records and `$investment-thesis-tracker` for evidence deltas.1112## Workflow13141. **Freeze provenance.** Preserve the original timestamped thesis, evidence cutoff, forecast, entry/exit plan, size, loss limit and any amendments. Never edit the old record; append review fields.152. **Reconstruct execution.** Record actual entry/exit, fees, spread/slippage, partial fills, holding time, deviations and whether the planned invalidation or review rule was observable.163. **Separate four outcomes.** Classify good process/good outcome, good process/bad outcome, bad process/good outcome and bad process/bad outcome. Luck does not repair a broken process; a valid process can lose.174. **Score the forecast.** When a probability or interval matured, compare the frozen forecast with the realized outcome and a declared naive/market benchmark. Preserve unresolved or early-closed cases separately.185. **Diagnose cause.** Distinguish research/evidence, thesis, timing, sizing, portfolio concentration, product mechanics, execution, discipline and unforeseeable shock. Avoid vague labels such as “emotion” without observable behavior.196. **Analyze patterns.** Normalize P&L by planned risk (`R`) and segment only when sample size permits. Compare repeated errors, regime, horizon, strategy and instrument; report missing data and selection bias.207. **Change little.** Recommend at most one or two falsifiable process changes for the next sample, with a measurement and review date. Do not optimize rules to explain the past perfectly.2122## Hard rules2324- Never use later information to claim it should have been known at the original cutoff.25- Never celebrate a rule-breaking winner as a good decision.26- Never infer skill from a handful of trades, one regime or selected successes.27- Include costs, abandoned ideas and no-trade decisions when available; survivor-only journals overstate quality.28- Do not respond to losses by automatically increasing risk, leverage or trading frequency.2930## Output3132For one decision: original plan, evidence available then, execution delta, process/outcome quadrant, forecast score, cause, retained lesson and one next experiment.3334For a journal: coverage/sample warnings, expectancy in R, win/loss distribution, drawdown, process adherence, forecast calibration when available, recurring strengths/errors, regime dependence and one or two measurable changes.
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