R-multiple explained: measuring trade outcomes in risk units
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By Ken Chigbo, Founder, KenMacro. Published 2026-05-12.
Quick answer
R-multiple is a normalised measure of trade outcome where 1R equals the initial risk (dollar amount risked from entry to stop). A trade that wins 3 times the initial risk is a plus 3R trade; a trade that loses the full risk is a minus 1R. R-multiple makes trades comparable across assets, position sizes, and account sizes. The metric was popularised by Van K Tharp in the late 1990s.
Quick answer
R-multiple is a normalised measure of trade outcome where 1R equals the initial risk (dollar amount risked from entry to stop). A trade that wins 3 times the initial risk is a plus 3R trade; a trade that loses the full risk is a minus 1R. R-multiple makes trades comparable across assets, position sizes, and account sizes. The metric was popularised by Van K Tharp in the late 1990s.
What is R-multiple?
R-multiple is a measure of trade outcome expressed in units of initial risk. The system, popularised by Van K Tharp, defines R as the dollar amount risked from entry to stop on a given trade. A trade where the trader risks 100 US dollars and exits with a 300 US dollar profit is a plus 3R trade. A trade where the trader risks 100 US dollars and gets stopped out is a minus 1R trade. R-multiple normalises outcomes across different position sizes, different assets, and different account sizes. A 50-pip gain on EUR/USD with one mini lot and a 250-pip gain on USD/JPY with one micro lot can both be 2R trades if the original risk was matched.
How traders use R-multiple
Professional traders track every trade in R-multiples rather than in dollars or pips. The advantages are three. First, R-multiple distributions reveal whether a strategy has positive expectancy (average R per trade greater than zero) without confusing the picture with position-sizing variations. Second, R-multiple distributions reveal the win rate and average win versus average loss in a single chart. Third, R-multiples make trader benchmarking honest: a trader posting plus 50R over 100 trades is genuinely outperforming, regardless of absolute dollar P&L or account size. The desk publishes weekly scorecards in R-multiples (current week 18 sits at 6 wins, 3 losses, plus 13.79R) and tracks all deployed frameworks in R-multiples for clean comparability across the multi-asset universe.
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Worked example with R-multiples
Consider a trader running a swing strategy across 20 trades over a quarter. The trades break down as 12 wins and 8 losses. The winners average plus 2.5R per trade (so 30R total). The losers average minus 1R per trade (so minus 8R total). Net expectancy: plus 22R over 20 trades, or plus 1.1R per trade. At 100 US dollars risk per trade (1 per cent of a 10,000 dollar account), the strategy returns 2,200 US dollars over the quarter, a 22 per cent return. The same strategy at 200 US dollars per trade returns 4,400 dollars; at 50 US dollars per trade, 1,100 dollars. R-multiples capture the structural expectancy independent of position-sizing choice, which is the metric that matters for strategy validation.
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Frequently asked
How do I calculate R-multiple on a trade?
R-multiple equals trade profit or loss in dollars divided by initial risk in dollars. Initial risk equals the dollar distance from entry to stop multiplied by position size. A trade entered at 1.0850 with a stop at 1.0800 on one mini lot of EUR/USD risks 50 pips at 1 US dollar per pip, equal to 50 dollars. Exiting at 1.0950 captures 100 pips at 1 dollar per pip equals 100 dollars profit. The R-multiple is 100 divided by 50 equals plus 2R.
What is a good R-multiple expectancy?
A trading strategy with positive expectancy (average R per trade greater than zero) is structurally profitable. Above 0.3R per trade average, with a sample size of 100 trades or more, is a strong strategy. Above 0.5R per trade is excellent. The desk's deployed frameworks target plus 0.5 to 1.0R per trade average on validated multi-year backtests with realistic costs applied.
Why do prop firms care about R-multiple?
Prop firms care about R-multiple because it strips out position-sizing variation and reveals true strategy expectancy. A funded trader posting plus 30R over 50 trades is structurally outperforming, independent of the absolute dollar P&L or the size of the funded account. R-multiple is the metric that travels cleanly across evaluation accounts, funded accounts, and scaled accounts.
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