What you will learn
- Store before-and-after evidence
- Classify valid losses
- Separate rule changes from execution errors
- Compare playbooks net of costs
Store before-and-after evidence
Store a before-entry record with context, trigger and planned risk, followed by the actual result. A post-trade screenshot alone can hide what was visible when the decision was made.
Classify valid losses
A valid loss follows the rules and loses within the observed execution process. It belongs in the sample. Calling every loss a mistake prevents honest estimation of the strategy's outcome distribution.
Separate rule changes from execution errors
Separate strategy changes from execution errors. A rejected order or incorrect size is not the same issue as an eligible setup that loses. Different problems require different corrective actions and evaluation records.
Compare playbooks net of costs
Compare playbooks using the same accounting and sample conventions. Net results, exposure, drawdown and uncertainty matter alongside win rate. A method with more winners can still have worse average losses and lower net expectancy.
Worked example
Playbook A wins 60% with average win 1 and average loss 2. Before costs, expectancy is 0.6×1−0.4×2 = −0.2. A high win rate alone does not establish a favorable result.
Try it yourself
Calculate expectancy for a playbook winning 40% with average win 3 and average loss 1, then subtract cost of 0.3 per trade.
Show the worked solution
Gross expectancy is 0.4×3−0.6×1 = 0.6. Net expectancy under the stated cost is 0.3. These are sample assumptions, not guaranteed future probabilities.
Apply this to your course project
Create two contrasting playbooks and replay them on a reserved chart sample.
Keep the calculation inputs, assumptions and decisions with your work. Practical exercises are self-reviewed; the scored knowledge checks assess the questions shown, not an independent certification of practical competence.