How to Design a Proper Database Model for a Trading Journal

Most traders begin journaling in spreadsheets but quickly abandon them because the format cannot answer meaningful performance questions. A well-structured relational database, built around a core trades table, separates key facts from supplementary data like notes, emotions, and rule checks. Storing the original stop-loss at entry time enables calculation of R multiples — a risk-adjusted performance metric more useful than raw dollar profit or loss. Many-to-many relationships between trades, emotions, and strategy rules allow traders to query patterns such as the cost of revenge trading or early exits. Using database views for derived metrics like R multiples ensures that any correction to entry data automatically recalculates all downstream figures.