The Trading Journal Blueprint
Almost every trader starts a journal. Almost nobody keeps one past three weeks, because a journal that only stores memories gives nothing back. The Trading Journal Blueprint turns yours into a decision machine: log twelve fields per trade, calculate seven metrics each week and finish every review with one specific change.
- The 12 fields of a useful entry — and why “plan followed: yes or no” matters most
- Why measuring in R instead of money makes every week comparable
- The seven metrics, with formulas: expectancy, average R, compliance, drawdown
- A worked month of real-shaped data and the exact decision it produces
- The 20-minute weekly review and the monthly deep review
- Six behaviour patterns the data always exposes, and the mechanical fix for each
- How to journal an automated system: latency, slippage and manual overrides
- Printable trade log, weekly metrics sheet and single-change template
15-page PDF in English. Instant digital download. Educational content only; trading involves risk.
Frequently asked questions
How long before a trading journal shows anything useful? Two weeks for behaviour patterns, 50 trades for a trend, and 100 trades before trusting expectancy.
What is expectancy? The average result per trade in R: (win rate × average winner) minus (loss rate × average loser). It is the number that answers whether a process is worth repeating.
My expectancy is positive but I am losing money. Why? Usually costs, an inconsistent risk per trade, or a few oversized trades taken outside the plan. Check your average loser and risk per trade first.
Does journaling matter if I automate everything? Yes, but the content changes: you stop logging emotion and start logging latency, slippage and manual overrides.
