Win Rate, Expectancy and Drawdown

Captain · CP05: Journaling and Improvement · About 25–30 minutes

Safety rule: Preserve the original evidence and include every loss, rejected setup and cost in your analysis.

Your mission today

By the end you can calculate a cost-aware trade sample's expectancy and drawdown without equating a high win rate to profit.

Before you start

Use the frozen CP01 strategy card, a demo execution report, your risk charter and a calculator. All numerical examples below are imaginary.

1. Understand the evidence problem

Win rate is only one number. A strategy that wins often but loses much more on its rare losing trades can still lose money. Expectancy is the average net result per trade. Drawdown measures the decline from a prior equity peak. Both must be calculated from a complete, chronologically ordered sample with realistic costs.

Win percentage alone cannot tell whether a strategy pays. Calculate average winning R, average losing R, total sample expectancy and maximum observed drawdown in a fixed, cost-aware ledger. Estimate uncertainty rather than extrapolating a small run of winners.

A backtest or small sample describes observed outcomes. It cannot establish future profitability unless the method survives out-of-sample testing and realistic trading costs.

2. Worked example: what can go wrong?

Imagine 20 synthetic trades: 12 wins average +1.2R and 8 losses average −1R. Gross total is 12×1.2−8 = +6.4R. Costs average 0.10R per trade, so twenty trades cost 2R. Net total is +4.4R, and mean net expectancy is +0.22R per trade. A negative future sample remains possible. A win rate of 60% does not validate future returns.

The earlier preserved source also illustrated: A synthetic 20-trade sample has 12 wins averaging +1.2R and eight losses averaging -1R. Gross total is +6.4R. If costs average 0.10R per trade, net total is +4.4R and mean net expectancy +0.22R per trade. This does not establish future profitability.

Original Black Box Journey educational diagram. Fictional results are not a verified market edge.

3. Follow a reproducible review

1. Count all completed eligible wins, losses and flat results.
2. Compute average positive and negative net R separately.
3. Calculate net expectancy as sum of trade net R divided by count.
4. Plot the cumulative net R in chronological order and measure peak-to-trough decline.
5. Record sample size, cost assumptions and holdout limitations.

A complete record is more valuable than a flattering summary. A reviewer should be able to reproduce the decision using the same information.

4. Identify the failure mode

Ten consecutive winners can occur by chance, and market regimes change. Small samples carry substantial uncertainty. A positive average from data used to tune the strategy is not enough for a profitability claim. Require separate out-of-sample evidence and realistic execution.

Unsafe alternative: A student advertises 90% win rate after nine wins and one small loss while hiding occasional -10R gaps. They must show risk distribution and full loss sizes.

5. Produce the independent research deliverable

The original lab requires: Calculate a 20-trade ledger, plot cumulative net R, identify peak-to-trough drawdown and write limits of inference.

Record the original input, full trade set, execution costs, skipped events and the exact comparison. If a result changes after a correction, keep both versions.

6. Calculate win rate, expectancy and drawdown separately

Synthetic four-trade ledger: Results after assumed trading costs are +1R, −1R, −1R and +1.5R. Two trades won, so win rate is 2 / 4 = 50%. Total net result is +1 − 1 − 1 + 1.5 = +0.5R. Average result, or expectancy in this tiny sample, is +0.5R / 4 = +0.125R per trade. This is arithmetic, not a credible forecast from four observations.

Starting at zero R, the cumulative path becomes +1, 0, −1 and +0.5R. The largest peak-to-trough decline is from +1R down to −1R, a 2R drawdown. That is different from the single largest loss of −1R. Real cash drawdown depends on how position risk changes over time.

Journal drill: Build a second ledger with costs, skipped cases and a fixed initial risk amount. Compute wins, losses, net R, peak equity, deepest decline and number of trades. Explain why a profitable-looking average and a 50% win rate do not prove the next month will be profitable.

Common mistake

Reporting a favourable final P/L as if it proves every earlier decision was valid. Keep process compliance and statistical outcome in separate columns.

Plain-English glossary

• Win rate: Winning trades divided by all measured trades.
• Expectancy: Average result per trade.
• Drawdown: Decline from a previous peak.
• R: Result scaled by initial risk.
• Holdout: Sample not used to design the rules.

Try it yourself

Calculate a 20-trade ledger, plot cumulative net R, identify peak-to-trough drawdown and write limits of inference. Include at least one losing and one rejected observation. Write the denominator and units beside every statistic.

What you can now do

• Calculate a cost-aware trade sample's expectancy and drawdown without equating a high win rate to profit.
• Show an adverse case using exact currency or R units.
• Explain the limits of the evidence without promising profit.

Next lesson

CP05.4 · Good Decisions Versus Lucky Outcomes.