What Is a Worked Example of Mistake Tracking?

Direct answer

A worked example of mistake tracking is a fully specified scenario where you (1) define a decision that went wrong, (2) list every assumption behind any numbers you compute, (3) quantify the mistake’s impact in a consistent way, and (4) document limitations so someone else can verify the logic using the same inputs.

Mechanism or definition

Mistake tracking is a structured way to turn “I think I made an error” into a record with observable elements: what you decided, what you expected, what actually happened, what evidence supports the label, and what process change you will try next time.

A key mechanic is separating stable tracking steps from variable conditions.

Stable mechanics: the categories you use (decision, context, rule violated, evidence), the timing of the record, and the method for calculating an impact estimate from the recorded inputs.
Variable conditions: market movement, execution quality, and trading costs. These change from one instance to the next, so they affect results even if your tracking method is consistent.

A limitation that often matters is failure mode: you can record “mistakes” inaccurately (e.g., hindsight bias), which makes later analysis less trustworthy.

Evidence or example

Worked scenario with explicit assumptions

Assume you are running a simple trade-management process with a single rule: “Set a stop-loss at entry and do not move it.” You want to estimate the impact of breaking that rule.

Recorded facts (from your journal, not live data):

You entered at 100.00.
Your original stop-loss was 99.50.
Later, you moved the stop-loss to 99.80.
The position was eventually closed at 99.20.

Assumptions (state them clearly):

You track impact only by price difference, ignoring fees and spreads.
Moving the stop-loss did not change the entry price.
The close at 99.20 is the actual outcome you recorded.

Step 1: Calculate the “if you followed the rule” loss (estimate).

If the stop-loss had stayed at 99.50, then the loss would be:
- Entry minus stop = 100.00 − 99.50 = 0.50 (price units per unit size).

Step 2: Calculate the “what actually happened” loss (estimate).

Actual loss relative to entry:
- Entry minus close = 100.00 − 99.20 = 0.80.

Step 3: Estimate the incremental impact of moving the stop.

Incremental difference = 0.80 − 0.50 = 0.30 price units per unit size.

How to interpret this: This number is not a guarantee of future performance. It is a transparent, assumption-based estimate of additional loss in this one scenario.

Verification criteria for a reader

Another person can verify the math by checking that:

The same three recorded prices are used (entry, original stop, close).
The calculation uses the same rule definition (rule-break means stop moved from 99.50 to 99.80).
The assumption “ignore costs” is applied consistently.

Limitations and risks

Material limitations to consider:

Mislabeling the mistake: If you later decide the “real” cause was something else (e.g., a bad setup, not the stop move), your analysis mixes causes.
Double-counting: If you record both “moved stop” and “chose the trade” as separate mistakes for the same event, you may count the same error twice.
Missing variable costs: Ignoring spreads, commissions, and slippage can materially change the impact estimate when they differ across trades.
Hindsight bias: In many cases, what you label as “what went wrong” can be influenced by the final outcome.
Non-stationary conditions: Even if this worked example is correct, repeated historical relationships do not establish future results.

Verification or next question

To make mistake tracking independently verifiable, keep two lists for every entry: (a) recorded inputs (prices, timestamps, what rule you intended) and (b) assumptions (what you ignored, how you defined impact). Then ask: “If I removed one assumption (for example, included a cost estimate), would my impact calculation change a lot?” If the result swings strongly, the tracking conclusion depends on that assumption rather than on the recorded decision.

If you want the next worked example, tell me the type of rule you track (risk sizing, entry trigger, stop management, or exit discipline) and what fields you record in your journal, and I can format a second fully assumed scenario.