TRADE REVIEW & JOURNAL PROCESS

Before entering, record the market context while your decision is still unbiased. Write the instrument, date, session, direction, higher-timeframe context, setup name, entry reason, invalidation level, target, planned risk in R, and the condition that would make you cancel the trade. Do not write a perfect story after the trade. Record the information that was actually available at the time. This preserves the difference between a good decision and a lucky outcome.

Use the same screenshot structure every time so trades can be compared later. A useful minimum set is: higher-timeframe context, execution timeframe, entry/stop/target markings, and the key liquidity or imbalance level you used. Keep the chart clean. Do not add indicators after the fact. Your future review should answer three questions quickly: what did I see, what did I do, and what invalidated the idea?

Track every outcome in R rather than only in dollars. A +2R trade and a +$200 trade are difficult to compare when account sizes change; R normalizes the result. Also track maximum adverse excursion (MAE) and maximum favorable excursion (MFE) when your platform or manual review allows it. MAE shows how far a trade moved against you before resolving. MFE shows how much unrealized profit was available. Across a meaningful sample, these measures can reveal whether stops are too tight, targets are unrealistic, or management rules are giving back too much. These are descriptive statistics, not guarantees. Small samples can produce misleading patterns.

Create a small controlled list of tags instead of writing a different description every time. Example tags: setup, session, direction, HTF alignment, entry quality, management error, rule violation, news exposure, and execution error. Separate model failure from process failure. If the setup met your rules and still lost, that is different from entering early, moving the stop, or trading outside your session. You need that distinction before changing the strategy itself.

Once per week, review the whole sample rather than the most emotional trade. Calculate total R, win rate, average winner, average loser, largest losing streak, rule-violation count, and performance by setup or session when you have enough observations. Then inspect representative trades: one clean winner, one clean loser, one avoidable loss, and one trade you missed. The goal is not a motivational speech. The goal is to identify one repeatable behavior to preserve and one behavior to remove.

Make changes slowly. If a review shows that losses cluster around a specific session, news window or entry condition, test that hypothesis on historical data before changing the live rules. Use a simple experiment: define the hypothesis, select the historical sample, apply the same rule consistently, compare the old and revised results, and only then decide whether the change deserves a forward test. This prevents the common cycle of losing money, changing the strategy, winning once, changing it again, and never knowing what actually worked.