Trade Journal Schema

A trade journal schema is the architectural blueprint of a trading journal — it specifies not just that trades should be recorded, but precisely what information must be captured for every single entry. Without a defined schema, journals become inconsistent collections of notes where different trades are recorded with different levels of detail, making cross-trade analysis unreliable and pattern identification impossible. A well-designed schema divides trade data into three temporal layers. The pre-trade layer captures information recorded before execution: the setup type, the criteria that qualified the trade, the intended entry price, the planned stop-loss level, the target price, the calculated position size, and the trader's written rationale for taking the trade. This layer is critical because it documents the decision-making process before the outcome is known, preventing post-hoc justification from distorting the record. The execution layer captures the actual trade mechanics: the precise entry price achieved, the timestamp, the actual position size executed, any deviation from the intended entry, and whether a TSA Compliance Check was completed. Comparing this layer against the pre-trade layer reveals execution gaps — the difference between what was planned and what was actually done. The post-trade layer records the outcome and review: exit price, exit reason, profit or loss in both monetary and risk-unit terms, and a structured self-assessment of what was executed well and what deviated from the plan. This layer transforms each trade from a closed financial event into an active learning data point. The schema's value compounds over time. When every trade is recorded using identical fields, performance analytics become statistically valid — win rates, average risk-to-reward, compliance rates, and drawdown metrics all reflect consistent underlying data rather than selectively documented trades.