R-multiples and your trade log

A single trade tells you nothing. A distribution of R-multiples tells you almost everything. This lesson builds a small trade log and reads it the way a professional reads a strategy report.

What the log records

The minimum useful trade log has one row per trade with these columns:

Put this in a spreadsheet. Fill it in the day the trade closes. A log filled in "at the weekend" gets edited by memory.

A twelve-trade sample

Here is a plausible run of twelve trades from a swing trader risking $100 per trade.

Now compute what matters:

• Winners: trades 2, 5, 8, 9, 10. Total = 2.0 + 3.0 + 1.5 + 1.0 + 2.5 = +10.0R.
• Losers: trades 1, 3, 4, 6, 7, 11, 12. Total = −(1.0 + 1.0 + 1.2 + 1.0 + 1.0 + 1.0 + 1.0) = −7.2R.
• Net = 10.0 − 7.2 = +2.8R over 12 trades.
• Win rate = 5 ÷ 12 = 41.7%.
• Average winner = 10.0 ÷ 5 = 2.0R.
• Average loser = 7.2 ÷ 7 = 1.03R.
• Net per trade = 2.8 ÷ 12 = +0.23R.

In dollars: +2.8R × $100 = +$280. On a $10,000 account that is 2.8% over twelve trades. Not spectacular, and that is exactly the point: a system that loses more often than it wins, with modest average winners, is comfortably profitable because the losers are held to about 1R.

Key idea: The sum of your R-multiples is your result. The shape of the distribution (how many small losses, how many large wins) is your strategy.

Reading the distribution

Line the results up from worst to best:

−1.2, −1.0, −1.0, −1.0, −1.0, −1.0, −1.0, +1.0, +1.5, +2.0, +2.5, +3.0

Three things to check on any distribution:

1. Is the left edge contained? The worst trade is −1.2R. Healthy. If you see −3R or −5R in a log, the stop is not being honoured and the whole system's numbers are fiction until that is fixed. One −5R loss would have turned this +2.8R sample into −2.2R.
2. Is the right tail present? The best trades are 2.5R and 3R. A log where nothing exceeds 1R needs either wider targets or a different setup, because it is asking the win rate to do all the work.
3. Are the losses clustered? Trades 6 and 7, then 11 and 12, were back-to-back losses. Streaks of two are normal. Streaks of five or six in a 41% win-rate system will also be normal (Module 1). Knowing that in advance is the difference between sitting through it and abandoning the system at trade 14.

Sample size

Twelve trades is a sketch. The 41.7% win rate could easily be 30% or 55% over the next hundred. As a rough guide:

This is another reason to start at 0.5% risk: you need to buy 100+ trades of data, and you want that data to be cheap.

Try it: Build the twelve-column log in a spreadsheet and enter the twelve trades above. Add formulas for total R, win rate, average winner and average loser. Then change trade 4 to −5R and watch what happens to the total.

Recap

• Log every trade with entry, initial stop, 1R in dollars, exit and result in R.
• Sum of R is your result; the distribution of R is your strategy.
• Check the left edge (worst loss should be near −1R), the right tail (some 2R+ winners) and the clustering of losses.
• A 42% win rate with 2R average winners and 1R average losers is comfortably profitable.
• Under 30 trades tells you little; 100+ per setup before you trust the numbers.