What Is a Worked Example of Trade Journal?

Direct answer

A worked example of a trade journal is a complete, step-by-step demonstration of how someone records a trade and calculates a few review numbers—using explicit assumptions—so another person can independently reproduce the same results.

In practice, a trade journal is a structured log of trade planning and execution details. The “worked example” is the numeric walk-through: what data gets recorded, how the calculations are done, and which parts are stable mechanics versus variable conditions (such as market moves, execution quality, and costs).

Mechanism: what you record and how the example works

A useful trade journal typically separates two layers:

Inputs you can record at the time

Entry decision context (e.g., what you expected to happen, and why)
Trade parameters (e.g., direction, entry price, stop distance, position size)
Execution details (e.g., the actual fill price you got)
Costs you want included (e.g., spread/commission or an estimated total per trade)

Derived outputs you calculate for review

Gross movement from entry to exit (or to stop)
Total costs for the specific trade
Net outcome after costs
Optional performance tags (e.g., whether the plan was followed)

Important: The journal’s calculations are mechanical. The market outcome and the real execution/costs are variable, so the example must state assumptions.

Worked example (numerical scenario with stated assumptions)

Below is one self-contained trade journal entry with a fully worked calculation. This is a scenario for explanation, not live data.

Assumptions (state everything used)

You record one long trade.
Entry (actual fill) price: 1.1000
Exit (actual fill) price: 1.1020
Position size: 10,000 units (often called “one lot” in many FX contexts, but the exact meaning depends on the venue)
Total transaction cost for this trade (spread/commission combined): $2
No other fees, financing charges, or taxes are included.

Step 1: Compute price movement

Price change = Exit − Entry
Price change = 1.1020 − 1.1000 = 0.0020

Step 2: Convert movement to a currency outcome (simplified mechanics)

Because this example must remain general (and because different platforms quote contract values differently), we state a simplification:

We assume the trade’s value change is $10 per 0.0010 move for the stated position size.

Then:

0.0020 move = 0.0010 × 2
Gross movement = $10 × 2 = $20

Step 3: Subtract costs to get net outcome

Net outcome = Gross movement − Total costs
Net outcome = $20 − $2 = $18

Step 4: What the journal would log

A clear journal row for review could include:

Entry: 1.1000 (actual fill)
Exit: 1.1020 (actual fill)
Position size: 10,000 units
Gross movement: +$20 (based on the stated $/move assumption)
Costs: $2
Net outcome: +$18
Plan-followed note (e.g., “stop level adjusted” vs “stop not touched”)—if applicable

Evidence of “independent verification”

A reader can verify the example by checking that each step is internally consistent:

The price movement arithmetic (1.1020 − 1.1000 = 0.0020)
The mapping from price movement to dollars using the explicit simplification ($10 per 0.0010)
The cost subtraction ($20 − $2 = $18)

If any assumption differs from the reader’s understanding (for example, the $/move mapping), then the net outcome will differ. That is why a worked example must expose assumptions.

Limitations and risks (at least one failure mode)

A trade journal is not a guarantee of future performance. Common material limitations include:

Inaccurate or inconsistent input data If you log entry/exit prices from memory, or you record estimates instead of actual fills, your derived metrics become unreliable.
Missing costs or fees If your journal excludes transaction costs (spread/commission) or other charges relevant to your account, comparisons across trades can be misleading.
Execution slippage and different fills than expected (failure mode) A journal can look “right” on paper if you assume entry at the displayed price, but the real fill may differ. Over time, that can break the connection between decision quality and outcomes.
Market variability Historical outcomes do not establish future results. Relationships you notice in a journal may change when volatility, liquidity, or market conditions differ.