Risk-reward ratio
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Free Tool
Risk-Reward Ratio Calculator
Enter an entry, a stop-loss and a target, or a ratio directly, and this tool returns the risk-reward ratio, the rupee risk and reward, your position size, and the number most calculators leave out: the breakeven win rate, the fraction of trades a setup must win to make money. Overlay your assumed win rate to see the expectancy in R and whether the edge is positive or negative.
Risk-reward and win rate are a single equation. A 1 to 3 setup only needs to be right a quarter of the time; win rate, the number retail chases, is the wrong half to optimise alone.
Scenario preset
Quick pick
How to define the trade
Direction
Long: stop below the entry, target above. The tool checks the prices are on the correct sides.
The trade
The price at which you plan to enter.
Where the trade is wrong and you exit. This sets your risk.
A level the price genuinely trades to, not a hopeful round number.
Assumed win rate
40%
How often you expect a setup like this to reach the target. The tool marks it against the breakeven line.
Size and costs (optional)
The rupees you are willing to lose if the stop is hit. Quantity is derived from this and the stop distance.
A representative all-in round-trip cost as a percentage of position value. Edit for your segment, or model the exact stack in the brokerage calculator.
Breakeven win rate
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Clears itRisk-reward ratio
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Expectancy at your win rate
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Reward vs risk
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What the setup implies
Breakeven win rate
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Your assumed win rate
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Margin vs breakeven
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Effective R:R after costs
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Effective breakeven after costs
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Your point on the breakeven curve
The curve is the breakeven win rate, 1 divided by (1 plus R:R), as the ratio varies. Above the curve is positive expectancy, below it is negative. Your setup's ratio and your assumed win rate are plotted: green above the line, coral below.
Position sizing and cost detail
Position size is the risk budget divided by the per-share stop distance, rounded down. Rupee risk and reward follow from the quantity and the price distances. The cost line is a representative estimate on the value you enter; the exact stack depends on your segment and broker.
Flags to review before trusting this setup
The ratio is the easy part: two subtractions and a division. The hard part is upstream, setting a target the price genuinely reaches and a stop outside the noise, then taking enough of the same setup to know the win rate you actually get rather than the one you hope for. That discipline, building setups whose realised win rate clears the breakeven with room for costs, is what the method we teach is built around.
The one principle
The risk-reward ratio and the win rate are not two questions, they are one equation. The ratio you set with your entry, stop and target fixes the win rate the setup must clear to break even, and that breakeven is 1 divided by (1 plus the ratio). A 1 to 3 setup breaks even at a 25 percent win rate; a 1 to 1 needs more than 50 percent, and more still after costs. Win rate, the number retail traders chase because being right feels like skill, is only half of the pair. Optimise it alone, by cutting winners early and letting losers run, and you raise the hit rate while destroying the ratio, which is exactly how a trader can be right most of the time and still lose money.
This tool is the front door. It turns one trade's geometry into the win rate it needs, so you can vet a setup before you take it. The companion expectancy calculator is the deeper room: once you have taken many trades and can measure the win rate and the average win and loss you actually get, it tells you whether the edge is truly positive. The ratio vets the plan; expectancy judges the record.
The math, derived
Three numbers define a trade before you enter it: the entry, the stop and the target. The stop sets the risk and the target sets the reward, both measured as a distance in price from the entry. The ratio is the second divided by the first.
risk per unit = | entry − stop |
reward per unit = | target − entry |
R:R = reward per unit ÷ risk per unit
long: stop below entry, target above; short: stop above, target below
reward per unit = | target − entry |
R:R = reward per unit ÷ risk per unit
long: stop below entry, target above; short: stop above, target below
Worked on the defaults above: a long entry at 100, a stop at 95 and a target at 115 gives a risk of 5 and a reward of 15, so the ratio is 15 divided by 5, which is 3, a 1 to 3 setup. Size it with a risk-per-trade budget of 2,000 rupees and the position is 2,000 divided by the 5-rupee stop distance, which is 400 shares; the rupee risk is 2,000 and the rupee reward is 400 times 15, or 6,000. The ratio is a property of the geometry alone. What it does not yet tell you is whether the trade makes money, and for that you need the win rate the ratio demands.
The breakeven win rate identity
Take many trades of the same shape, a fraction p of them winning the reward and the rest losing the risk. Set the average result to zero and solve for p, and a clean identity falls out. Let the ratio be reward divided by risk, with the loss counted as one unit of risk.
0 = p × R:R − (1 − p) × 1
rearranged, the breakeven win rate is:
pbe = 1 ÷ (1 + R:R)
above pₖₑ the setup is positive; below it, negative
rearranged, the breakeven win rate is:
pbe = 1 ÷ (1 + R:R)
above pₖₑ the setup is positive; below it, negative
This is the most useful line in the subject. It tells you, for any ratio, the exact win rate you must clear, so you never judge a win rate in isolation again. At 1 to 1 the breakeven is 50 percent; at 1 to 2 it is 33.3 percent; at 1 to 3 it is 25 percent; at 1 to 4 it is 20 percent. On the defaults, a 1 to 3 setup breaks even at 25 percent, and an assumed win rate of 40 percent sits 15 points above that line. The expectancy at that win rate is 0.40 times 3 minus 0.60 times 1, which is 1.20 minus 0.60, or plus 0.60R per trade: the setup returns about 0.60 rupees for every rupee risked, before costs.
Read every output as arithmetic on your inputs, not a forecast. The ratio, the breakeven and the expectancy are computed entirely from the entry, stop, target and win rate you type in. The win rate in particular is an assumption you supply; the tool does not know how often your setups reach the target. Its job is to show you the bar a ratio sets and whether the win rate you claim clears it, not to predict what any account will do.
One equation, two ends
The clearest way to see the identity is to watch a single setup's geometry hand off to the win rate it demands. The stop and the target are the two ends of the risk-reward ratio; the ratio is the two ends of the breakeven win rate.
Reference: breakeven win rate by ratio
This is the identity p breakeven equals 1 divided by (1 plus R:R) tabulated. The first two columns are the ratio written as risk to reward and as the numeric reward per unit of risk; the third is the win rate at which the setup breaks even before costs; the last is a judgement, the cushion a retail system typically wants above breakeven so that costs and the ordinary error in a win-rate estimate do not tip a thin edge negative.
| Ratio (risk : reward) | Reward per 1 risk | Breakeven win rate | Comfortable target |
|---|---|---|---|
| 1 : 0.5 (reward-poor) | 0.5 | 66.7% | above 72% |
| 1 : 1 | 1.0 | 50.0% | above 56% |
| 1 : 1.5 | 1.5 | 40.0% | above 46% |
| 1 : 2 | 2.0 | 33.3% | above 40% |
| 1 : 3 | 3.0 | 25.0% | above 32% |
| 1 : 4 | 4.0 | 20.0% | above 27% |
| 1 : 5 | 5.0 | 16.7% | above 23% |
Read it and the reason professional desks widen the ratio before they chase the hit rate becomes obvious. Lifting a win rate is hard and runs quickly into a ceiling; moving the target out from a 1 to 2 to a 1 to 3, when the level still holds, drops the breakeven from 33.3 to 25 percent and turns a marginal setup robust. Asking the market to be right for you one time in four is a far easier thing to do consistently than winning three trades in four.
Reference: costs raise the bar, most on tight setups
The clean ratio is a gross number. Every round trip pays securities transaction tax, an exchange charge, stamp duty, the SEBI turnover fee and 18 percent GST on the fee lines, and that cost comes out of the reward and adds to the loss. As a fraction of the risk it is trivial on a wide setup and brutal on a tight one, because a fixed cost is a large share of a small stop. The table holds a representative all-in round-trip cost of 0.20 percent of position value fixed and varies the stop width, so you can see the effective ratio and the effective breakeven the setup actually trades at.
| Setup and stop width | Gross ratio | Cost as R | Effective ratio | Gross breakeven | Effective breakeven |
|---|---|---|---|---|---|
| Tight scalp, 0.5% stop | 1 : 1 | 0.40R | 1 : 0.43 | 50.0% | 70.0% |
| Intraday, 1% stop | 1 : 2 | 0.20R | 1 : 1.50 | 33.3% | 40.0% |
| Swing, 2% stop | 1 : 3 | 0.10R | 1 : 2.64 | 25.0% | 27.5% |
| Positional, 5% stop | 1 : 3 | 0.04R | 1 : 2.85 | 25.0% | 26.0% |
The tight scalp is the cautionary row. A 1 to 1 setup with a stop half a percent away loses 0.40R to a cost of only 0.20 percent, so its effective ratio collapses to 1 to 0.43 and the win rate it truly needs climbs from 50 to about 70 percent. The wide positional setup barely notices the same cost. This is the quiet reason high-frequency, tight-stop trading is so hard for retail: the edge has to survive a cost drag that scales with how tight you trade, and a 1 to 1 that looks fine on paper can need a near-impossible win rate once the round trip is counted.
Same win rate, opposite fates
Because the ratio sets the breakeven and the win rate has to clear it, two setups with the identical win rate can sit on opposite sides of the line. Hold the win rate at 45 percent and change only the ratio, and one setup loses money while the other is strongly positive.
Reference: the expectancy grid
The grid is expectancy per R, computed from p times R:R minus (1 minus p), for a range of win rates and ratios. Read down a column to see how much win rate a fixed ratio needs; read across a row to see how a wider ratio rescues a low win rate. Coral cells are negative, where the setup loses on average; green cells are positive; the boundary between them is the breakeven line the identity predicts.
| Win rate | 1 : 0.5 | 1 : 1 | 1 : 2 | 1 : 3 |
|---|---|---|---|---|
| 20% | −0.70 | −0.60 | −0.40 | −0.20 |
| 30% | −0.55 | −0.40 | −0.10 | +0.20 |
| 40% | −0.40 | −0.20 | +0.20 | +0.60 |
| 50% | −0.25 | 0.00 | +0.50 | +1.00 |
| 60% | −0.10 | +0.20 | +0.80 | +1.40 |
| 70% | +0.05 | +0.40 | +1.10 | +1.80 |
Two things jump out. Read the 70 percent row: at a 1 to 0.5 ratio, where winners are half the size of losers, it is barely positive at plus 0.05R, an edge costs erase, while the same 70 percent at 1 to 2 is a commanding plus 1.10R. And read the 40 percent row: negative until the ratio reaches 1 to 2, then a strong plus 0.60R at 1 to 3. The win rate you should want depends entirely on the ratio you can realistically achieve, which is why the two are meaningless apart. For the same grid read from the system side, with the average win and loss you have measured rather than the ratio you have planned, use the expectancy calculator.
Failure modes: where the clean ratio lies to you
A tidy ratio on a chart is a plan, not a result. Six things detach the printed number from what the trade actually earns, and each has turned a setup that looked excellent into one that was not.
1. Targets that never fill. The ratio is only as real as the target. Set the target at a level the price genuinely trades to and the reward is achievable; set it at a round number or just beyond a resistance the price reverses at, and you have inflated the ratio on paper while the market takes you out before you get there. A 1 to 4 that fills one time in ten is worse than a 1 to 2 that fills four times in ten. Measure the ratio against a target the price reaches, not the one that makes the arithmetic look good.
2. Stops that slip past the level. The ratio assumes the loss is exactly the distance to the stop. In a gap, a fast move or an illiquid name, the fill comes worse than the stop price, so the realised loss is larger than one R and the true ratio is smaller than the one you calculated. A stop is a request, not a guarantee. On instruments and sessions where slippage is common, budget for a loss larger than the stop distance, because a single slipped stop can undo several clean winners.
3. The ratio measured on the intended entry, not the fill. You calculate the ratio from the price you meant to enter, but you trade the price you actually got. Chasing an entry a little worse than planned shortens the reward and lengthens the risk at the same time, so a 1 to 3 planned can become a 1 to 2 realised before the trade even moves. Compute the ratio from the fill, not the alert, and if the entry has run away from the level, the setup you planned no longer exists.
4. Cherry-picked R on the winners you remember. It is easy to quote the ratio from the trades that worked and quietly forget the ones scratched early, the stops moved to avoid a loss, and the targets cut short out of fear. The average ratio your broker statement shows is lower than the one your memory reports, because memory keeps the clean winners and drops the messy exits. Reconcile the ratio you claim against the trades you actually closed, since the gap between them is where a good plan hides a mediocre record.
5. Cost drag lowering the effective R. Every round trip pays the full stack of securities transaction tax, exchange charges, GST on the fee lines, stamp duty and the SEBI fee, and that comes out of the reward and adds to the loss. On a wide setup it is a rounding error; on a tight one it can turn a 1 to 1 into an effective 1 to 0.4 and push the breakeven win rate from 50 toward 70 percent. Always read the effective ratio after costs, not the gross one, and treat tight-stop, high-frequency trading as the place costs do the most damage.
6. Moving the stop to avoid the loss. The most expensive habit in trading is widening the stop as the price approaches it, to turn a small loss into a hope. It raises the win rate, which feels like progress, and destroys the ratio, because the losses you do take are now far larger than the one R the plan assumed. A stop that moves is not a stop. The ratio only means anything if the stop is where you said it would be, and the discipline to let it get hit is the whole game.
The ratio lens on the SEBI base rate
Why does a segment where some participants clearly have an edge still show over 91 percent of individual traders net loss-making in FY25, with aggregate net losses of about 1,05,603 crore rupees, up roughly 41 percent on the year? The risk-reward frame answers a large part of it. A great many of those accounts optimise the wrong half of the equation. They chase the win rate, because being right feels like skill and booking a small profit feels safe, and they do it in the two ways that raise the hit rate while wrecking the ratio: cutting winners the moment they are green, and refusing to take the loss at the stop. The result is a high win rate sitting on a ruinous ratio, a 1 to 0.5 or worse, whose breakeven is far above the win rate the account actually runs.
The ratio is the front gate: it tells you the win rate a setup must clear before you take it. Once the trades are in, the expectancy calculator turns your realised win rate and average win and loss into the rupees an average trade returns, the position sizing calculator sets the rupee size of each trade from the stop, and the risk of ruin calculator shows how long a losing run has to be before it ends the account at that size. The ratio decides whether a trade is worth taking; the others decide whether you survive to collect the edge.
Common Questions
Frequently Asked Questions
What is the risk-reward ratio and how do you calculate it?
+The risk-reward ratio compares how much you stand to lose on a trade with how much you stand to gain, measured from the same entry. Risk is the distance from your entry price to your stop-loss; reward is the distance from your entry to your target. The ratio is reward divided by risk. If you buy at 100, place a stop at 95 and a target at 115, your risk is 5 and your reward is 15, so the ratio is 15 divided by 5, which is 3, usually written 1 to 3, meaning three units of reward for every one unit of risk. It is a property of the trade's geometry alone, set before you enter, and it says nothing on its own about whether the trade makes money, because that also depends on how often a setup like it reaches the target rather than the stop.
What is the breakeven win rate for a risk-reward ratio?
+The breakeven win rate is the fraction of trades you must win, at a given risk-reward ratio, for the wins and losses to cancel out. It is 1 divided by (1 plus the ratio), where the ratio is reward per unit of risk. At 1 to 1 you need to win 50 percent of the time; at 1 to 2 you need 33.3 percent; at 1 to 3 only 25 percent; at 1 to 4 just 20 percent. The wider the reward relative to the risk, the fewer of your trades need to work. This single identity is why the risk-reward ratio and the win rate can never be judged apart: the ratio sets the bar, and the win rate is what has to clear it. A win rate above the breakeven line is a positive-expectancy setup and one below it loses on average, no matter how good it feels.
What is a good risk-reward ratio?
+There is no universal number, because a ratio is only good relative to the win rate you can actually achieve at it. A 1 to 3 ratio has a breakeven win rate of 25 percent, so it is strongly positive if your setups reach the target more than a quarter of the time; a 1 to 1 ratio needs more than 50 percent after costs, which is a far harder bar to clear consistently. Higher ratios are not automatically better, because a distant target is reached less often, so pushing the target out to lift the ratio can lower the win rate faster than the ratio rises. A workable rule for retail is to look for setups where a realistic target gives a ratio of at least 1 to 2 while keeping the target at a level the price genuinely trades to, then confirm the win rate you actually achieve clears the breakeven with a cushion for costs. The right ratio is the one your realised win rate can beat.
Does a higher risk-reward ratio mean I need to win less often?
+Yes, and that is the whole point of the breakeven identity. Because the breakeven win rate is 1 divided by (1 plus the ratio), raising the ratio lowers the win rate you need: 1 to 1 needs 50 percent, 1 to 2 needs 33.3 percent, 1 to 3 needs 25 percent, 1 to 4 needs 20 percent. A trend-following method that wins only three or four times in ten can be highly profitable if its winners are three or four times the size of its losers, because it clears a low breakeven bar. The catch is that a higher ratio usually comes from a more distant target, and distant targets fill less often, so the win rate tends to fall as the ratio rises. The ratio only helps if the win rate at that target stays above the lower breakeven line, which is why you must measure the win rate you actually get, not assume it holds as you widen the target.
How do I calculate risk-reward for a short trade?
+The arithmetic is identical; only the direction of the prices flips. On a short you sell at the entry expecting the price to fall, so your stop-loss sits above the entry and your target sits below it. Risk is the distance from the entry up to the stop; reward is the distance from the entry down to the target; the ratio is still reward divided by risk. If you short at 100 with a stop at 104 and a target at 88, your risk is 4 and your reward is 12, a ratio of 1 to 3. This calculator has a long or short toggle that checks the prices are on the correct sides: for a short it requires the stop above the entry and the target below it, and it flags the setup if they are reversed, because a stop on the wrong side of the entry is the most common data-entry error and it silently inverts the whole calculation.
Is a 1 to 1 risk-reward ratio bad?
+It is not bad in itself, but it is demanding, and it is the ratio costs punish hardest. A 1 to 1 setup has a breakeven win rate of 50 percent before costs, so you have to be right more than half the time just to stay level, and after the round-trip stack of securities transaction tax, exchange charges, 18 percent GST on the fee lines, stamp duty and the SEBI turnover fee, the true breakeven rises above 50 percent. On a tight setup, where the stop is a small percentage move away, those fixed costs are a large share of the risk, so a 1 to 1 scalp can quietly need a win rate in the high fifties or low sixties to break even. High-win-rate methods do run at low ratios and can work, but the margin for error is thin and a single run of losses or a rise in costs erases the edge. The lower the ratio, the more the win rate and the cost control have to carry the system.
How do trading costs change my effective risk-reward ratio?
+Costs come out of the reward and add to the loss, so they lower the effective ratio and raise the breakeven win rate you actually face. Every round trip in the Indian market carries securities transaction tax, an exchange transaction charge, the SEBI turnover fee, stamp duty on the buy and 18 percent GST on the fee lines, and the 2026 Budget set STT on options at 0.15 percent of the sell-side premium and on futures at 0.05 percent of the sell-side turnover from 1 April 2026. As a fraction of the risk, that cost is small on a wide setup and large on a tight one: a stop that is 5 percent away barely notices a 0.2 percent round-trip cost, but a stop 0.5 percent away can lose a meaningful part of its reward to the same cost. This tool subtracts a representative round-trip cost, which you can edit, from the reward and adds it to the risk to show the effective ratio and the effective breakeven, and it is why a clean 1 to 3 on paper can trade like a 1 to 2.6, and a 1 to 1 scalp can need a win rate near 70 percent once costs are counted.
Why do traders with a high win rate still lose money?
+Because win rate is only half of the equation, and it is the half that flatters. A trader who wins 70 percent of the time feels skilful, but if the winning trades are small and the occasional losing trades are large, the risk-reward ratio can be well below 1 to 1, and at a 1 to 2 ratio, where losers are twice the size of winners, the breakeven win rate is 66.7 percent, so a 70 percent hit rate clears it by barely three points and costs erase what is left. The most expensive habit in retail trading is exactly this: cutting winners early to lock in the pleasant feeling of a win, and holding or widening the stop on losers to avoid booking a loss, which lifts the win rate while quietly destroying the ratio. Win rate is the number that is easy to chase and easy to fake, and it is the wrong half to optimise alone. The SEBI FY25 finding that over 91 percent of individual derivatives traders were net loss-making includes many accounts with a high hit rate and a ruinous ratio.
Risk-reward ratio or expectancy, which one matters more?
+They are two views of the same equation, and you need both. The risk-reward ratio is a property of a single planned trade, set by the entry, stop and target before you enter, and it tells you the breakeven win rate that setup must clear. Expectancy is a property of a whole system, measured across many completed trades, and it combines your realised win rate with your average win and loss into the rupees an average trade returns. The risk-reward ratio is the front door: it turns one setup's geometry into the win rate you need. Expectancy is the deeper room: once you have taken many trades and can measure how often you actually reach the target and how large the wins and losses turn out to be, expectancy tells you whether the edge is truly positive. Use the risk-reward ratio to vet a trade before you take it, and the expectancy calculator to judge the system after the trades are in. Neither number is meaningful without the win rate beside it.
Where the facts come from
Sources
- The risk-reward and breakeven identities. The risk-reward ratio is reward distance divided by risk distance, and the breakeven win rate follows from setting expectancy to zero, giving 1 divided by (1 plus the ratio). These are arithmetic identities, derived in full on this page, not empirical claims. The R-multiple convention, measuring outcomes per unit of risk, follows Van K. Tharp, Trade Your Way to Financial Freedom. vantharpinstitute.com
- The FY25 loss base rate. SEBI study on the profit and loss of individual traders in the equity derivatives segment: over 91 percent net loss-making in FY25, with aggregate net losses of about 1,05,603 crore rupees, up roughly 41 percent from about 74,812 crore in FY24, across the top brokers and around 96 lakh unique traders. business-standard.com
- The 2026 cost schedule. The round-trip cost lines, securities transaction tax with options at 0.15 percent of sell-side premium and futures at 0.05 percent of sell-side turnover effective 1 April 2026, plus the exchange transaction charge, the SEBI turnover fee, stamp duty and 18 percent GST on the fee lines, follow the NSE reference on levies. Verify current rates with your broker. nseindia.com
Educational note. This tool computes figures from your own inputs; every output is illustrative and depends entirely on the entry, stop, target, ratio and win rate you enter. The win rate is an assumption you supply, not a measurement the tool makes. The reference tables are mathematical models, not predictions of any account's results, and nothing here is a claim about the returns, win rate, or profit any strategy will achieve. Nothing on this page is a recommendation to trade, to use leverage, or to buy or sell any security, and it is not investment advice. Bharath Shiksha is an educational publisher, not a SEBI-registered investment adviser or research analyst.