R Multiple Calculator
An R multiple expresses a trade's result as a multiple of the amount risked, where one R is the distance from the entry to the stop. Because the unit is the risk rather than the money, results across different position sizes and different markets become directly comparable.
The trade in units of risk
Defaults buy 200 units at 100 with a stop at 95, exiting at 112.
The R multiple deliberately ignores position size — it cancels out of the ratio. That is the point: a 2.4R trade is a 2.4R trade whether it made 240 or 24,000, which is what makes a record of them comparable.
Runs entirely in your browser. Nothing you type is sent anywhere or stored.
How the number is built
One subtraction defines the unit and one division applies it. The unit is decided before the trade starts and never changes.
R = (exit − entry) ÷ (entry − stop)
One R is a distance, and in money it is that distance times the size. Both forms are useful: the distance makes trades comparable, and the money makes the risk real.
A worked example
Take the defaults: 200 units bought at 100 with a stop at 95, exited at 112.
One R is 100 − 95 = 5 per unit, which is 1,000 across the position.
The result is 112 − 100 = 12 per unit, which is 2,400.
So 2,400 ÷ 1,000 = 2.40R.
Change the size to 2,000 units and nothing about the R multiple moves. The money becomes 24,000 against 10,000 risked, and the answer is still 2.40R — which is exactly why a record kept in R can be compared across accounts, markets and years.
What a record in R tells you
Average every trade’s R, losers included, and you have expectancy — the amount a strategy earns per attempt, in units of risk. A positive average means the approach pays; a negative one means it does not, regardless of how the individual trades felt.
Which immediately shows why the hit rate on its own is useless. Winning three times in ten at 4R and losing seven at −1R gives 12R − 7R = 5R across ten trades, or 0.5R each. Winning seven times at 0.5R and losing three at −1R gives 3.5R − 3R = 0.5R, or 0.05R each.
The first record wins far less often and earns ten times as much per attempt. In money those two would be hard to compare; in R the comparison is immediate.
R is fixed when you enter
The denominator is the stop you actually placed, and it is not revisable. Widening a stop mid-trade enlarges R after the fact, so a loss that should have been −1.8R gets recorded as −1R and the journal quietly stops describing what happened.
Moving a stop in your favour is a different case and it is fine. Tightening to lock in a gain does not change the R the trade was entered with, and the honest convention is to keep the original denominator throughout.
What the number does not include
Commission and spread are paid on every trade and belong in the result. On this site’s shared
series a round trip measures about 2% of the median bar range of 0.493 — small against a 2.4R winner
and decisive on a strategy averaging 0.05R. The figures are in research/series-measurements.json.
Slippage attacks the denominator specifically. A stop filled below its price makes the loss larger than one R, so a record of clean −1R losses is usually a record that has not been checked against the fills.
Turning R back into a position
The same three numbers run in the other direction give you the size. Decide the money that one R is allowed to be, divide it by the distance from entry to stop, and the position falls out.
On the defaults, if one R is capped at 1,000 and the stop sits 5 away, the position is 200 units. Move the stop to 95.5 and the distance becomes 4.5, so the same 1,000 of risk buys 222 units.
Which is why R and position sizing are the same idea approached from opposite ends. One asks what a finished trade returned per unit of risk; the other asks how many units a fixed unit of risk allows. Keeping the money value of one R constant across every trade is what makes a record in R comparable — vary it, and a 3R winner from a large-risk trade is being averaged against a 3R winner from a small one as though they were the same event.
The original data
Of the 24,971 unique videos in research/search-study-corpus.jsonl, 11 have an instruction-shaped
title about R multiples, at a median of 2,728 views across 11 channels — and 0% are
calculator-shaped. Position sizing appears in 195 at 1,738 and win-rate targets in 161 at 13,711.
The counts come from site/rank_tools2.py, which deduplicates by video id.
Eleven videos at 2,728 against 161 on win rates at 13,711. The measure that makes a trading record readable has almost no audience, and the measure that makes it misleading has fifteen times as much.
The answer to the question on that chart is that the R record you already have should decide it, not the position in front of you. If your winners historically average 3R, closing at 2R is systematically leaving the tail behind; if they average 1.5R, taking 2R is above your own norm. The point of measuring in R is that the question stops being a judgement call and becomes a comparison against a distribution you have written down.
When it fails
R inherits every weakness of the stop it is measured from. A stop placed at a round number rather than where the idea is wrong produces a denominator with no meaning, and every R calculated from it inherits that — so a journal full of tidy 2R winners can be describing trades whose risk was never actually defined. The arithmetic is correct and the unit is arbitrary, which is the worst combination.
The second failure is excluding losers from the average. Expectancy is the mean of everything.
A third is comparing R across strategies with different holding periods. 0.5R a week is not 0.5R a quarter.
A fourth is ignoring costs. They come out of every realised R.
A fifth is recording planned R rather than realised R. Slippage separates them.
And a sixth is using R without recording how many trades produced it. A 3R average over eight trades is a story, not a measurement.
Related
Expectancy is the average R across a full record. Position sizing turns one R into a number of units. And stop-loss is what defines the denominator in the first place.
Switching my journal to R was the change that stopped me lying to myself. In money, a good trade in a large position and a mediocre trade in a small one look the same, and I remembered the ones that made the most rather than the ones that were best. In R, the size is gone and only the decision is left.
— Michael Whitman
This page is educational, not financial advice. Test every idea on your own charts before risking money.