One trade made $500 and another made $300. Neither number says which trade went better, because neither says what was at stake. If the first risked $500 and the second risked $100, the first returned one times its risk and the second returned three times its risk. That ratio is the R-multiple, and it is the unit this article uses for everything that follows.
What an R-multiple is
R is the risk you accepted when you opened the trade: the distance from your entry to your stop, times the units you bought. An R-multiple divides the result by that number.
R-multiple = profit or loss / initial risk
A worked example
Buy at $50 with the stop at $48. The initial risk is $2 a share, so 1R is $2 a share.
- Exit at $54. The profit is $4 a share, and $4 / $2 is 2R.
- The stop is reached at $48. The loss is $2 a share, and -$2 / $2 is -1R.
The same arithmetic works on the whole position. Buy 250 shares and the initial risk is $500. A 2R result is $1,000 and a -1R result is $500. R is a ratio, so the share count cancels out of it.
For a short, 1R is the stop price minus the entry price, and the result is the entry price minus the exit price, divided by 1R. The signs reverse; nothing else does.
Why R-multiples make trades comparable
Two results in dollars, and the same two in R:
| Trade A | Trade B | |
|---|---|---|
| Profit | $500 | $300 |
| Risk accepted | $500 | $100 |
| R-multiple | 1R | 3R |
Trade B put up a fifth of the capital at risk and returned three times it. In dollars, Trade A looks larger. In R, the comparison runs the other way.
That property is what lets one column hold a $12 stock and a $300 one. It holds a two-day trade beside a three-week one, and a position built in a $10,000 account beside one built in a $200,000 account. Every row is a multiple of what that particular trade had at stake.
Calculating an R-multiple
Step 1: define 1R before you enter
1R is the entry price minus the stop price, per share. Entry at $75 with the stop at $72 gives 1R of $3.
Fix the stop before the order goes in. A stop chosen after the price has moved is chosen by the price, and an R-multiple measured against it measures nothing.
Step 2: divide the result by 1R
Once the trade closes, the R-multiple is the exit price minus the entry price, divided by 1R.
| Exit | Arithmetic | Result |
|---|---|---|
| $81 | ($81 - $75) / $3 | 2R |
| $87 | ($87 - $75) / $3 | 4R |
| $72 | ($72 - $75) / $3 | -1R |
| $73.50 | ($73.50 - $75) / $3 | -0.5R |
Step 3: record the four numbers that produce it
Entry price, initial stop, exit price and the R-multiple that follows. Without the initial stop, the R-multiple cannot be reconstructed later, so it is the field worth guarding.
Reading an R-multiple distribution
A single R-multiple describes one trade. The spread of them describes the method.
Take a hypothetical record of 100 closed trades:
| R-multiple | Trades | Contribution |
|---|---|---|
| -1R | 45 | -45R |
| -0.5R | 5 | -2.5R |
| 0R | 5 | 0R |
| +1R | 20 | +20R |
| +2R | 15 | +30R |
| +3R | 7 | +21R |
| +4R | 3 | +12R |
Add the contributions: -45 - 2.5 + 0 + 20 + 30 + 21 + 12 = +35.5R across 100 trades.
From the same table:
- Win rate: 45 of the 100 trades finished above zero, so 45%.
- Average winner: 83R over 45 winners, or 1.84R.
- Average of everything else: -47.5R over 55 trades, or -0.86R.
- Expectancy: 35.5R over 100 trades, or +0.355R per trade.
Note where the five break-even trades sit. They are neither winners nor losers, but they are still trades, so they belong in the denominator. Counting them in the loss rate while leaving them out of the average loss produces a figure that is wrong in both directions.
The long way round gives the same answer: (0.45 x 1.844) - (0.55 x 0.864) = 0.830 - 0.475 = 0.355R. Total R divided by trade count is faster and harder to get wrong.
Using R-multiples to set targets
The breakeven win rate at each target
Give every loser a cost of 1R and every winner the same fixed multiple. The win rate that returns nothing is then 1 divided by 1 plus that multiple.
| Target | Breakeven win rate |
|---|---|
| 1R | 50.0% |
| 1.5R | 40.0% |
| 2R | 33.3% |
| 3R | 25.0% |
| 4R | 20.0% |
A 2R target needs 33.3% of trades to work before it returns anything. At a 40% win rate, a 2R target gives (0.4 x 2) - (0.6 x 1) = +0.2R per trade before costs. Brokerage and slippage come out of that 0.2R, and on a small position they can take most of it.
Read the table in the other direction too. A method that wins 55% of the time clears breakeven at 1R, so a 2R target is not the only workable choice. The target and the win rate are one decision, not two.
Scaling out, priced in R
One approach exits a third of the position at 1R, a third at 2R, and trails a stop on the last third. What the trade averages depends entirely on the last third.
- The runner exits at 3R: (1 + 2 + 3) / 3 = 2R.
- The runner comes back and exits at breakeven: (1 + 2 + 0) / 3 = 1R.
- The runner exits at 6R: (1 + 2 + 6) / 3 = 3R.
Scaling out narrows the range of outcomes. It does not raise the average on its own, and describing the plan as "about 2R" hides which of those three rows you are counting on.
R-multiples and position sizing
Risk a fixed 1% of your account on each trade and 1R becomes 1% of the account. A -1R trade costs about 1%, a 2R trade returns about 2%, a 3R trade about 3%.
Two conditions sit under that "about". The loss has to stop where the stop was, which a gap through it does not. And the 1% has to be measured on the same balance each time.
Over a month of 20 trades totalling +12R, the account arithmetic follows the same rule. With risk fixed at 1% of the balance you started the month with, +12R is exactly +12% of that balance. With risk recalculated on the running balance after every trade, the total depends on the order the wins and losses arrived in, so +12% becomes an approximation rather than the answer.
Expectancy, the number the distribution is for
Expectancy is the average R per trade across the record. Two ways to reach it:
- Total R divided by the number of trades.
- (Win rate x average winner in R) minus (loss rate x average loser in R, written as a positive number).
Two hypothetical systems:
| System A | System B | |
|---|---|---|
| Win rate | 40% | 50% |
| Average winner | 2.5R | 1.0R |
| Average loser | -1.0R | -1.2R |
| Expectancy | (0.4 x 2.5) - (0.6 x 1.0) = +0.4R | (0.5 x 1.0) - (0.5 x 1.2) = -0.1R |
System B wins more often and returns less than nothing. That is the case for reading win rate and R together rather than either alone.
Expectancy scales with trade count, which is the only projection the number supports:
| Expectancy per trade | Total across 100 trades |
|---|---|
| -0.1R | -10R |
| +0.1R | +10R |
| +0.2R | +20R |
| +0.4R | +40R |
| +0.6R | +60R |
Those totals are in R, not dollars. They say nothing about how long 100 trades takes, or how large your R is. A +40R record on a 0.25% risk figure and a +10R record on a 2% one are the same money.
Five ways an R-multiple goes wrong
1R defined after the fact. A stop chosen once the trade is open produces an R-multiple for the trade you ended up in, not the one you planned. Set the stop before the order.
The stop moved, and R moved with it. Trailing a stop up is a decision about the trade. Recalculating 1R from the new stop rewrites the risk you took and inflates every R-multiple after it. 1R is the initial risk, fixed at entry.
Partial exits averaged carelessly. Weight each exit by the units it closed. Two thirds at 1R and one third at 4R is (2 x 1 + 1 x 4) / 3 = 2R, not the 2.5R you get by averaging the two prices.
Win rate read on its own. System B above wins half its trades and loses money. A win rate with no R beside it cannot be interpreted in either direction.
A largest loser far past -1R. Check the worst R in each month against -1R. If the stop was placed before entry and reached as placed, the worst result is about -1R, and a gap through the stop is the ordinary exception. A largest loser of -2.4R with no gap behind it usually means a stop was widened, never sent, or not filled, and that is a record-keeping fault before it is a trading one.
R-multiple quick reference
| Result | What it means |
|---|---|
| -1R | The stop was reached; the full planned risk was lost |
| -0.5R | Closed early, at half the planned risk |
| 0R | Closed at the entry price |
| 1R | Profit equal to the risk |
| 2R | Profit twice the risk |
| 3R or more | Profit at least three times the risk |
R-multiples in Swingfolio
The analytics page carries three separate readings.
Average R-Multiple sits above the filters. The headline figure is a winsorised mean, labelled "winsorised (5% trimmed each end)", with the median printed beside it so one freak trade cannot carry the average alone. A bar underneath marks the "Middle 90% of trades" across the full range of your results. Below 20 closed trades the card switches to the raw mean and shows a warning badge reading "Low sample" with the count against the threshold, such as "12 / 20".
Each trade's R comes from its stop when a stop was recorded. When none was, the app derives one from the worst adverse excursion the trade reached. A trade drops out of the card only when neither is available.
R-Multiple Distribution, in the section headed "Trade Quality", is the bar chart of the spread. Its buckets are "< -2R", "-2R to -1R", "-1R to 0R", "0R to 1R", "1R to 2R", "2R to 3R" and "> 3R", and a hovered bar reads "Trades: 12 (14.3%)". A reference line marks the average. This chart reads the R-multiple stored on each trade, so a trade saved without a stop is absent from it. The empty state says so directly: "Add stop-loss to trades to calculate R-multiples".
Expect, in the metrics strip at the top of the page, is expectancy in your portfolio currency rather than in R. It is the win rate times the average winning trade, minus the loss rate times the average losing trade, with break-even trades counted in the denominator and in neither average. To convert it back to R, divide by your usual 1R in dollars.
Before a trade closes, the R-multiple calculator does the same arithmetic from a direction, an entry price, a stop loss, and an exit or target price. It returns the initial risk (1R), the P&L per share and the risk-reward ratio. Add a share count and an account size and it also returns the dollar risk and the position risk as a percentage of the account.
Record the initial stop on your next trade, then read the R column when it closes. Start the 30-day trial.