Risk-Reward Ratio Calculator
Turn an entry, stop and target into a reward-to-risk ratio, the win rate it needs to break even, and the expected value at the win rate you actually achieve.
How to use this calculator
- 1Enter the price you would enter at, the stop-loss where you would exit if wrong, and the target where you would take profit.
- 2Add a share count if you want the outcome in money as well as a ratio.
- 3Enter your win rate from your own trading record — not what you hope it is. This is the input that decides whether the expectancy is real.
- 4Compare your win rate against the break-even figure: below it, the setup loses money over time however good any single trade looks.
How the calculation works
Ratio = |target − entry| ÷ |entry − stop|. Break-even win rate = 1 ÷ (1 + ratio). Expectancy (R) = win% × ratio − (1 − win%)- ratio
- Reward-to-risk: how many times the risk the target is worth
- break-even win rate
- The share of trades that must reach target for the strategy to break even
- expectancy (R)
- Average profit per trade expressed in multiples of the amount risked
Expressing expectancy in R — multiples of the risk taken — is what makes trades of different sizes comparable. A 0.2R edge is the same edge whether the risk was 50 or 5,000, which is exactly why professional risk frameworks talk in R rather than in currency.
The break-even win rate falls as the ratio rises, but not linearly: going from 1:1 to 2:1 drops the requirement from 50% to 33%, while 4:1 to 5:1 only moves it from 20% to 16.7%. Most of the benefit of a wider target arrives early.
None of this includes costs. Brokerage on both legs shrinks every win and enlarges every loss, so the genuine break-even win rate always sits above the figure this produces — materially so for small positions traded frequently.
Worked example
A 3:1 trade at a 40% win rate
- 1.Risk = 100 − 95 = 5 a share. Reward = 115 − 100 = 15 a share.
- 2.Ratio = 15 ÷ 5 = 3, so 3:1.
- 3.Break-even win rate = 1 ÷ (1 + 3) = 25%.
- 4.Expectancy = 0.40 × 3 − 0.60 = 0.60R. On 500 of risk that is about 300 expected per trade — a genuine edge despite losing 60% of the time.
Result: 3:1, profitable at 40% — expectancy 0.6R
A high win rate that still loses money
- 1.Risk = 5 a share, reward = 2 a share, so the ratio is 0.4:1.
- 2.Break-even win rate = 1 ÷ 1.4 = 71.4%.
- 3.At a 60% win rate: expectancy = 0.60 × 0.4 − 0.40 = −0.16R.
- 4.Winning six trades in ten still loses money, because the four losses are each two and a half times the size of a win.
Result: Negative expectancy at a 60% win rate
Win rate alone tells you nothing
The instinctive measure of trading skill is how often you are right, and it is close to useless on its own. A strategy winning 90% of its trades loses money if the occasional loss is twenty times a typical win. A strategy winning 30% is comfortably profitable if the wins are four times the losses. Neither the win rate nor the ratio means anything in isolation; only together do they determine whether an approach makes money.
The relationship between them is precise. At a reward-to-risk ratio of R, the break-even win rate is 1 ÷ (1 + R). A 1:1 trade needs to win more than half the time. A 2:1 trade needs a third. A 3:1 trade needs a quarter. This is why traders who lose most of their trades can still be consistently profitable, and why a high win rate is frequently a warning sign rather than a boast — it is most easily achieved by taking small profits quickly and letting losses run, which is the classic route to a losing record with a flattering hit rate.
Expectancy, and thinking in R
Expectancy combines the two figures into one number: the average profit per trade, expressed as a multiple of the amount risked. The convention of measuring in R — where 1R is the risk taken on the trade — is what makes results comparable across positions of different sizes.
A strategy with 0.3R expectancy makes, on average, three-tenths of the risked amount per trade. Risk 100 and it averages 30; risk 5,000 and it averages 1,500. The edge is identical; only the scale differs. This framing also clarifies what a good result looks like: sustainable edges are typically small. An expectancy of 0.1R to 0.3R is a real, workable advantage, and anything claiming to be far above that over a long series deserves scepticism about how the win rate was measured.
Why the planned ratio and the realised one diverge
The ratio computed here is the planned one, assuming the trade ends at either the stop or the target. Real trades frequently end somewhere else, and the differences almost always favour the market rather than the trader.
- Exiting early — closing a winner at half the target while still taking full losses converts a planned 3:1 into a realised 1.5:1 and can quietly turn a positive expectancy negative.
- Slippage and gaps — stops fill at the available price, not the intended one. The realised risk is often larger than planned, and never smaller.
- Costs on both legs — brokerage shrinks every win and deepens every loss, raising the true break-even win rate above the calculated figure — sharply so for small, frequent trades.
- Unreachable targets — a wide target improves the ratio on paper but is hit less often, lowering the win rate. Widening a target does not improve expectancy unless the win rate holds up, and it usually does not.
Where the numbers should come from
The ratio is arithmetic once three prices are chosen, so it is always correct. The win rate is the fragile input, and it is the one that decides whether the expectancy means anything at all.
A win rate estimated from impression rather than from records is essentially always too high — winners are remembered better than losers, and near-misses get recalled as successes. The only defensible source is a log of actual trades, and a meaningful one needs a reasonably large number of them: a 60% win rate measured over ten trades is entirely consistent with a strategy that truly wins 40% of the time. Until such a record exists, the useful output of this calculator is the break-even win rate, which is a fixed property of the setup, rather than an expectancy computed from a number that was hoped for rather than observed.
What this assumes, and where it stops
Assumptions
- Every trade ends at either the stop or the target, with nothing in between.
- The win rate entered is representative of a large number of trades of this shape.
- Stops and targets are filled at the stated prices.
- Expectancy excludes brokerage and charges, so the real break-even win rate is higher than shown.
Limitations
- Costs are not deducted from the expectancy, and they raise the true break-even win rate — substantially for small, frequently traded positions.
- A win rate drawn from a small sample is unreliable, and a small sample is the usual case.
- Real exits happen away from both the stop and the target, and the divergence typically works against the planned ratio.
- A positive expectancy describes an average over many trades. It says nothing about any individual trade, or about the losing streaks a positive-expectancy strategy still produces.
Common questions
What is a good risk-reward ratio?
There is no threshold that is good on its own, because the ratio only means something alongside a win rate. A 1:1 trade is fine at a 60% win rate and loses money at 45%. A 3:1 trade is profitable at 30% and loses at 20%. What matters is that your actual win rate exceeds the break-even figure of 1 ÷ (1 + ratio) by enough margin to cover costs. Chasing a high ratio by widening targets usually lowers the win rate enough to cancel the benefit.
Can I be profitable while losing most of my trades?
Yes, and many systematic approaches work exactly this way. At a 3:1 ratio the break-even win rate is 25%, so winning 40% of the time produces an expectancy of 0.6R — a substantial edge while being wrong six times out of ten. The requirement is that losses are genuinely cut at the stop and winners genuinely held to target. The approach fails the moment losses are allowed to run past the stop, because the ratio the whole edge depends on then no longer holds.
What does expectancy in R actually mean?
R is the amount risked on a trade, so expressing expectancy in R makes trades of different sizes directly comparable. An expectancy of 0.3R means that on average each trade returns three-tenths of what was risked — 30 if you risked 100, 1,500 if you risked 5,000. Real, sustainable edges are usually small: 0.1R to 0.3R is a workable advantage, and a claimed expectancy far above that over a long series usually indicates the win rate was measured optimistically.
Why is my real break-even win rate higher than the calculator shows?
Because this excludes costs. Brokerage and charges are paid on both entry and exit regardless of outcome, so every winner arrives smaller than planned and every loser lands deeper. On a 3:1 setup the theoretical break-even is 25%, but with costs consuming a meaningful share of a small position the real figure can be several points higher. The smaller the position and the more often you trade, the wider that gap becomes.
Sources
- Day Trading: Your Dollars at Risk — US Securities and Exchange Commission
- Trading Basics — US Securities and Exchange Commission (Investor.gov)
Formula and content last reviewed on .
Results are estimates for information only, not professional advice.
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