What Is an R-Multiple?
An R-multiple expresses your profit or loss as a multiple of your initial risk. "R" stands for the dollar amount you risked on the trade -- the distance between your entry price and stop loss, multiplied by your position size.
If you risked $200 on a trade and made $600, that is a +3R trade. You made three times what you risked.
If you risked $200 and lost $150 (you got out before your full stop was hit), that is a -0.75R trade. You lost three-quarters of your risk.
If you risked $200 and lost $200 (your stop was hit exactly), that is a -1R trade.
The formula:
R-Multiple = (Exit Price - Entry Price) / (Entry Price - Stop Loss Price)
For short trades: R-Multiple = (Entry Price - Exit Price) / (Stop Loss Price - Entry Price)
Why R-Multiples Matter More Than Dollar P&L
Dollar profit and loss numbers are misleading when compared across trades of different sizes.
Consider two trades:
- Trade A: Made $500 profit on a $50,000 position with a $2,000 risk. That is +0.25R.
- Trade B: Made $300 profit on a $5,000 position with a $150 risk. That is +2.0R.
Trade A made more dollars. Trade B was the far better trade. Trade B captured 2x the risk; Trade A captured only a quarter of the risk on a position ten times larger.
R-multiples normalise across different position sizes, stock prices, and account sizes. They answer the question: "For every dollar I risked, how many dollars did I make (or lose)?" This makes it possible to compare trades on an equal footing.
A trade that makes +2R on a $200 risk and a trade that makes +2R on a $2,000 risk are equally good trades in terms of execution quality. The dollar amounts are different because the positions were sized differently, but the quality of the trade -- how well you captured the available move relative to your risk -- is the same.
How to Calculate R-Multiples: Worked Examples
Example 1: Winning Long Trade
- Entry price: $42.00
- Stop loss: $40.00
- Exit price: $48.00
R per unit = Entry - Stop = $42.00 - $40.00 = $2.00
Profit per unit = Exit - Entry = $48.00 - $42.00 = $6.00
R-Multiple = $6.00 / $2.00 = +3.0R
You made three times what you risked. If you bought 500 shares, you risked $1,000 (500 x $2.00) and made $3,000 (500 x $6.00).
Example 2: Losing Long Trade (Stop Hit)
- Entry price: $25.50
- Stop loss: $24.00
- Exit price: $24.00 (stop hit)
R per unit = $25.50 - $24.00 = $1.50
Loss per unit = $24.00 - $25.50 = -$1.50
R-Multiple = -$1.50 / $1.50 = -1.0R
A -1R loss means you lost exactly what you planned to risk. This is a well-managed loss. The stop did its job.
Example 3: Partial Loss (Exit Before Stop)
- Entry price: $8.20
- Stop loss: $7.60
- Exit price: $7.85 (exited early based on deteriorating price action)
R per unit = $8.20 - $7.60 = $0.60
Loss per unit = $7.85 - $8.20 = -$0.35
R-Multiple = -$0.35 / $0.60 = -0.58R
You lost less than 1R because you exited before the stop was hit. Whether this was a good decision depends on context -- if you saved yourself a further -0.42R of loss, it was the right call. If the stock bounced at $7.70 and ran to your target, you cut yourself out of a winner prematurely.
This is exactly why recording R-multiples over time matters. You can measure whether your discretionary exits (before stop or target) improve or worsen your results compared to letting the mechanical rules play out.
Example 4: Short Trade
- Entry price: $55.00 (shorted)
- Stop loss: $57.50
- Exit price: $49.00 (covered)
R per unit = Stop - Entry = $57.50 - $55.00 = $2.50
Profit per unit = Entry - Exit = $55.00 - $49.00 = $6.00
R-Multiple = $6.00 / $2.50 = +2.4R
Building an R-Distribution
A single R-multiple tells you about one trade. The real power comes from collecting R-multiples across 50 or more trades and looking at the distribution.
Your R-distribution is the pattern of R-multiples across all your closed trades. It might look something like this:
| R-Multiple Range | Count | Percentage |
|---|---|---|
| Below -1.5R | 3 | 6% |
| -1.5R to -1.0R | 8 | 16% |
| -1.0R to -0.5R | 7 | 14% |
| -0.5R to 0R | 4 | 8% |
| 0R to +0.5R | 6 | 12% |
| +0.5R to +1.0R | 8 | 16% |
| +1.0R to +2.0R | 9 | 18% |
| +2.0R to +3.0R | 3 | 6% |
| Above +3.0R | 2 | 4% |
This distribution tells you several things:
Your loss containment -- Most losses are clustered between -1.5R and -0.5R. The 3 trades below -1.5R are worth investigating -- what went wrong? Did you move your stop? Did the stock gap through your stop overnight?
Your win capture -- The bulk of your wins are between +0.5R and +2.0R, with a few outliers above +3R. Those +3R wins are likely the trades where you let winners run. The cluster of small wins (+0 to +0.5R) might represent trades where you took profit too early.
Your edge -- If the average of all these R-multiples is positive, you have a statistical edge. If it is negative, you are losing money on a risk-adjusted basis regardless of what the raw dollar P&L says.
What Good Looks Like
There is no single "correct" R-distribution, because it depends on your strategy. But here are general benchmarks:
Average R above +0.3 -- You have a measurable edge. Each trade, on average, returns 30% of what you risked.
Average R above +0.5 -- Strong edge. Your wins are meaningfully larger than your losses on a risk-adjusted basis.
Average R above +1.0 -- Exceptional. You are, on average, doubling your risk on each trade. This usually indicates either a high win rate with decent winners, or a moderate win rate with occasional large R wins.
Few trades below -1.5R -- Your stop discipline is solid. Trades that lose more than 1.5R suggest stop management issues (moving stops, ignoring them, or gaps through stops).
Occasional trades above +3R -- This indicates you have the discipline to let winners run. Many traders struggle with this because the urge to take profit is strong when a position is up +1R or +2R.
Expectancy: The Single Number That Summarises Your Edge
Expectancy combines your win rate with your R-multiples into one number:
Expectancy = (Win Rate x Average Win R) - (Loss Rate x Average Loss R)
Where:
- Win Rate = Percentage of trades that are profitable
- Average Win R = Average R-multiple of winning trades
- Loss Rate = 1 - Win Rate
- Average Loss R = Average R-multiple of losing trades (as a positive number)
Example:
- Win rate: 45%
- Average winning R: +2.1R
- Average losing R: -0.8R (you cut losses before the full -1R stop)
Expectancy = (0.45 x 2.1) - (0.55 x 0.8) = 0.945 - 0.44 = +0.505R
This means that, on average, every trade you take is expected to return +0.505R. With a 1% risk per trade, that is 0.505% account growth per trade.
Over 100 trades: 100 x 0.505% = approximately 50% account growth (before compounding).
A positive expectancy with a 45% win rate. This is how traders with sub-50% win rates still grow their accounts -- their winners are large enough in R-terms to more than compensate for the losers.
A negative expectancy means you are losing money regardless of how it feels. Some traders have a 60% win rate but negative expectancy because their losses are much larger in R-terms than their wins (e.g., they cut winners at +0.5R but let losers run to -2R).
Free R-Multiple Calculator
Use SwingFolio's free R-Multiple Calculator to calculate the R-multiple for any trade. Enter your entry price, stop loss price, and exit price, and it returns the R-multiple, risk per unit, and profit per unit.
The calculator works for both long and short trades and is free to use without an account.
How SwingFolio Tracks R-Multiples Automatically
When you log a trade in SwingFolio with a stop loss, the R-multiple is calculated automatically when the trade closes. No manual formula work needed.
Here is what SwingFolio does with your R-multiples:
Per-trade R-multiple -- Shown on every closed trade that has a stop loss recorded. This appears on the trade detail page and in the trades list.
Average R-multiple on the dashboard -- The dashboard KPI bar shows your average R across all closed trades. This updates as you close trades. The dashboard shows separate averages for closed trades and open positions (open R is calculated using current market prices).
R-multiple by strategy -- The analytics page breaks down average R by strategy. This tells you which strategies produce the best risk-adjusted returns -- and which ones you should consider dropping or modifying.
R-distribution chart -- The analytics section includes an R-distribution chart showing the spread of your R-multiples. This is the visual version of the table shown earlier in this article.
Expectancy calculation -- SwingFolio calculates expectancy across your entire trade history and per strategy. A strategy with positive expectancy is worth keeping; one with negative expectancy is costing you money.
The key requirement is that you record a stop loss for each trade. Without a stop loss, there is no "R" to measure against, and SwingFolio cannot calculate the R-multiple. This is one reason SwingFolio emphasises stop losses in the trade form -- they are not just risk management tools, they are measurement tools.
Putting It Together
R-multiples, position sizing, and expectancy form a complete framework for measuring your trading edge:
- Position sizing ensures you risk the same percentage on every trade.
- R-multiples measure each trade's outcome relative to that risk.
- Expectancy tells you whether your system has a positive edge over time.
If your expectancy is positive and you size positions consistently, your account will grow over a sufficient number of trades. If your expectancy is negative, no amount of stock-picking skill or market timing will save you in the long run.
The practical step is to start recording stop losses on every trade. After 50 closed trades, you will have an R-distribution that tells you more about your trading than any single metric ever could.