Definition: what journal review means
A “journal review” is a structured way to examine what you wrote in a trading journal (your decisions, context, and rules) and compare it to what happened (execution outcome and key costs). The goal is to learn about decision quality—especially whether your process followed your stated rules—not to forecast the next outcome.
A “worked example” of journal review is a fully transparent, numerical scenario that shows each step of the calculation and lists every assumption. That makes it possible to independently verify the example using the same inputs.
How the worked example works (mechanics)
Journal review typically uses these inputs:
- Decision fields you recorded: entry/exit time (or decision time), whether a rule was followed, and the reason category.
- Outcome fields you recorded: realized result per position (or at least direction and whether the exit was later than planned).
- Cost fields you included: spread, commission, and swaps/financing if your journal tracks them.
Then you compute summary metrics that help you compare categories of decisions:
- Net result per trade = gross outcome − costs (assuming you recorded costs consistently).
- Rule adherence rate = number of trades where the stated rule conditions were met ÷ total reviewed trades.
- Average net result by category or by rule adherence.
Important: the “mechanics” are stable (how you compute and summarize). The “market/provider” parts are variable (prices, execution quality, costs, and jurisdiction). So you must treat your example as a demonstration of method, not as an indicator.
Evidence or example: a fully specified worked scenario
Assume a small journal contains 4 trades, and the journal already includes costs per trade. The goal is to compare “Rule A followed” versus “Rule A not followed.”
Assumptions (state them clearly):
- You review exactly these 4 trades.
- “Rule A” is a binary condition: either your rule checklist was satisfied at decision time or it was not.
- Each trade has a recorded gross result and a recorded total costs amount.
- Costs are already netted into the journal’s “net result” calculation.
- No additional fees occur after what is recorded.
Data (example numbers):
- Trade 1: Rule A followed = Yes; Gross = +120; Costs = 20 ⇒ Net = +100
- Trade 2: Rule A followed = Yes; Gross = −60; Costs = 15 ⇒ Net = −75
- Trade 3: Rule A followed = No; Gross = +90; Costs = 25 ⇒ Net = +65
- Trade 4: Rule A followed = No; Gross = −80; Costs = 10 ⇒ Net = −90
Step 1: Net totals and averages
- Rule A followed trades: Net = (+100) + (−75) = +25. Average net = +25 ÷ 2 = +12.5
- Rule A not followed trades: Net = (+65) + (−90) = −25. Average net = −25 ÷ 2 = −12.5
Step 2: Rule adherence rate
- Rule A followed count = 2, total trades = 4 ⇒ adherence rate = 2 ÷ 4 = 50%
Step 3: What you conclude from this example (method focus)
- In this example dataset, trades where Rule A was followed have a higher average net result than trades where it was not.
- However, this is a tiny sample (2 vs 2), so the result can change if you include more trades.
To keep it “worked” and verifiable, another reader should be able to recompute every number from the same table (Net = Gross − Costs; averages by group; adherence rate).
Limitations and risks (what can fail)
At least one material limitation matters because journal review can produce misleading learning:
- Small-sample noise: With only a few trades, average net results can swing due to randomness rather than process quality.
- Selection bias: If you later decide which trades to include, your review may overstate what works.
- Inconsistent cost recording: If costs are missing, estimated, or recorded differently across trades, “net result” comparisons become unreliable.
- Missing context: “Following a rule” may be correlated with market regimes you did not record (volatility, time of day, liquidity), so the review might credit the rule for effects caused by context.
- Historical pattern ≠ future expectation: Even if a rule looks better in past data, it does not establish predictable future performance.
These are not hypothetical edge cases—each one directly affects whether your calculations reflect your real execution and decision process.
Verification and next question
To verify journal review results independently, you can:
- Recalculate net results using your raw entries (Net = Gross − Costs) trade by trade. 2.