R-multiple Framework

What is the R-multiple Framework?

The R-multiple framework expresses every trade outcome as a multiple of its initial risk. R is the amount put at risk at entry: the distance from entry to stop, times position size. A trade stopped for its full risk is -1R; a trade that returns twice what it risked is +2R. Popularized by Van Tharp, the convention turns a ledger of dollar results across different instruments, sizes, and account balances into a single comparable distribution of R-multiples.

That normalization is the point. Expectancy becomes the average R per trade, a function of win rate and the relative size of winners and losers in R terms. Paired with fixed fractional sizing, where every trade risks the same fraction of equity, 1R maps to a known slice of the account, so losing streaks can be reasoned about in trade counts instead of dollars. The framework stays honest only if R is recorded from the original stop: widening a stop mid-trade quietly redefines what -1R was supposed to mean.

How traders use it

• For journaling: every closed trade is logged as an R-multiple, so expectancy and the shape of the outcome distribution can be tracked without the noise of varying position sizes and instruments.
• For pre-trade geometry: targets are quoted in R against a 1R stop, making reward-to-risk explicit before entry; see the profit target taxonomy for how those objectives get placed.
• For comparing systems: strategies on different markets or account sizes can be ranked on average R, R distribution, and worst R streaks, because the unit already accounts for what was risked.