Guide
Three trading playbook examples you can turn into testable rules.
A useful playbook does more than name a pattern. Each setup needs market context, an observable entry trigger, a price-based invalidation, a risk limit, a target plan, and review criteria. Use these examples as structure, then replace the numbers with evidence from your own trades.
Example 1: trend pullback
Context: the session holds above a higher-timeframe level and prints higher highs and higher lows. Trigger: price pulls back to the prior breakout area and closes back with the trend. Invalidation: the pullback closes through the defended level. Risk: size the position from the entry-to-stop distance and cap the loss at 1R. Review: grade patience, stop placement, and MFE captured at the exit.
Example 2: failed breakout reversal
Context: price tests a defined session high or low after an extended move. Trigger: the breakout fails and price reclaims the level from the opposite side. Invalidation: price accepts beyond the failed-breakout extreme. Target: the next liquidity area or a predefined R multiple. Review: confirm the reclaim happened before entry and separate a planned reversal from a reactive fade.
Example 3: no-trade playbook
Context: the setup appears during a restricted condition. Rule: skip the trade after the daily loss limit, immediately before a scheduled high-impact release, when the stop cannot fit the risk cap, or after the planned entry has already moved away. Review skipped trades too: record whether the filter protected capital or excluded valid opportunities.
Turn each example into a checklist
Write one yes-or-no check for context, trigger, invalidation, position risk, target, and prohibited conditions. A setup is ready only when every required check is observable before entry; discretionary notes belong after those rules, not instead of them.
Review the playbook with trade evidence
Attach screenshots and real trades to the setup, then compare rule adherence, outcome in R, MAE, and MFE across at least 20 similar examples. Change one rule at a time and track the next sample separately so a short streak does not rewrite the entire playbook.