Reviewed by the Quantzee team.
TL;DR
The risk-reward ratio expresses how much potential profit you earn for every dollar you risk on a trade — a 1:2 ratio means you need to win only one trade in three to break even.
What Is Risk-Reward Ratio?
The risk-reward ratio (R:R) is the mathematical relationship between the maximum loss on a trade (defined by your stop loss) and the maximum target profit (defined by your take profit or target level). It is expressed as the amount risked relative to the amount targeted: a 1:2 risk-reward ratio means you risk 1 unit to potentially earn 2 units.
The power of risk-reward ratio lies in what it does to the math of long-run profitability. If your strategy has a 1:2 R:R, you only need a win rate above 34% to be profitable over time — you can be wrong on two out of every three trades and still make money. This is counterintuitive but mathematically certain: a high R:R ratio compensates for a low win rate, allowing profitable trading strategies to have accuracy well below 50%.
R:R ratio is most useful when calculated before entering a trade — it tells you whether the trade is worth taking relative to your stop level and realistic target. A trade with a 1:0.5 R:R means you risk $2 to make $1, requiring a win rate above 67% just to break even. Unless your strategy has genuinely proven win rates at that level, such trades should be skipped regardless of how compelling the setup looks.
Key Formula / Numbers
Risk = Entry Price - Stop Loss Price
Reward = Target Price - Entry Price
R:R Ratio = Risk : Reward
Break-Even Win Rate = 1 / (1 + R:R multiple)Break-even win rates by R:R:
| R:R Ratio | Minimum Win Rate to Break Even |
|---|---|
| 1:1 | 50% |
| 1:1.5 | 40% |
| 1:2 | 33% |
| 1:3 | 25% |
| 1:0.5 | 67% |
Try the calculator: run your own entry, stop loss, and target through the Risk-Reward Ratio Calculator to get your R:R and break-even win rate instantly.
Worked Example
(Illustrative example — figures below are a hypothetical scenario for teaching the calculation, not real market data.)
Say a trader is evaluating a long entry on a global equity index CFD trading at 5,000. The stop loss sits at 4,970 (30-point risk) and the target sits at 5,090 (90-point reward).
Risk = 5,000 − 4,970 = 30 points Reward = 5,090 − 5,000 = 90 points R:R Ratio = 30 : 90 = 1 : 3
Using the break-even formula: Break-Even Win Rate = 1 / (1 + 3) = 25%. This trade only needs to win one time in four to be profitable over a large enough sample — even though a 25% win rate sounds low in isolation, it is fully compensated for by the 1:3 ratio.
Compare that to a trade with the same setup but a tighter target of 5,030 (30 points): R:R becomes 1:1, and the break-even win rate jumps to 50%. The stop distance didn’t change — only the target did — but the strategy now needs to win twice as often to break even. This is the practical lesson behind the formula: R:R and win rate are not independent variables, and a small change in target distance can double the win rate a strategy needs just to survive.
How Quantzee Uses This
Quantzee indicators provide defined entry zones and price levels that directly enable pre-trade R:R calculation. When the AI Adaptive Quant Toolkit signals an entry, it identifies both the invalidation level (stop) and the signal’s projected target zone — giving you the two numbers needed to calculate R:R before committing capital. Non-repainting signals are essential here: if stop and target levels are going to shift retroactively on historical bars, you cannot trust the R:R you calculated at entry to reflect what was genuinely available.
Practical Application
Applying R:R as a pre-trade filter, not a post-trade label, changes how a trading plan is built:
- Set the stop first, based on structure — not on how much you’re “willing to lose.” A stop placed at a meaningful invalidation level (below a recent swing low, outside an ATR band) defines the risk side of the ratio honestly.
- Identify the realistic target next — the next resistance zone, a measured move, or a volatility-based projection. Resist the temptation to stretch the target to make the ratio look better; an unrealistic target produces a flattering R:R that never gets hit.
- Calculate R:R before sizing the position, not after. If the ratio falls below your minimum threshold (most systematic traders use 1:1.5 as a floor), the correct action is to skip the trade — not to move the stop closer to force a better ratio artificially.
- Track realized R:R against planned R:R over a sample of trades. A persistent gap (planned 1:2, realized 1:1.3 on average) usually means targets are being exited early out of impatience, or stops are being moved wider mid-trade — both erode the mathematical edge R:R is supposed to provide.
Common Mistakes
- Calculating R:R after entry, not before: The ratio has no use as a filter if you calculate it after deciding to trade. The discipline is to reject any trade where the R:R doesn’t meet your minimum threshold before entry.
- Moving stop losses to “give the trade more room”: This retroactively changes the R:R ratio and destroys the mathematical advantage of maintaining it. If your stop is in the right place at entry, it should stay there.
- Ignoring win rate in the R:R calculation: A 1:5 R:R sounds impressive until you realize that if your win rate on those setups is 5%, the strategy is a net loser. R:R and win rate must be evaluated together — the relevant metric is expected value per trade.
Further Reading
The break-even win-rate math above follows the same expectancy framework Van Tharp formalized in Trade Your Way to Financial Freedom — one of the standard references systematic traders use to reason about R-multiples and position sizing together, rather than treating risk-reward ratio as a standalone number.
Related Terms
FAQ
What is a good risk-reward ratio for trading?
A minimum of 1:1.5 is generally required for a strategy to have positive expected value at realistic win rates; most professional systematic traders target 1:2 or better, which allows profitability at win rates as low as 33%.
Can a strategy be profitable with a low win rate?
Yes — if the R:R ratio is high enough. A strategy that wins 30% of the time but achieves 1:3 R:R on each winner has a positive expected value of 0.2R per trade and will be profitable over enough trades.
Should I use a fixed risk-reward ratio or adjust per trade?
Most systematic traders use a fixed minimum R:R as a filter (only take trades meeting or exceeding the threshold) while allowing the actual ratio to vary — rejecting any trade that falls below the minimum regardless of how good the setup looks.
How do I calculate risk-reward ratio on options trades?
For options, use the premium paid (or margin at risk for a defined-risk spread) as the risk side, and the realistic profit target — either a technical price target translated into option value, or a fixed profit-taking rule — as the reward side. Because option value doesn’t move linearly with the underlying, R:R on options is more sensitive to time decay and implied volatility changes than on a simple stock or futures position, so it should be recalculated as expiry approaches rather than treated as fixed at entry.
Does a good risk-reward ratio guarantee profitability?
No. R:R only tells you the reward-to-risk relationship on a single trade type — it says nothing about the probability of winning. A strategy with excellent R:R (1:5) but a near-zero realistic win rate is still a net loser. R:R must always be evaluated alongside a strategy’s actual historical win rate, not in isolation.
What is the difference between risk-reward ratio and expectancy?
Risk-reward ratio describes a single trade’s potential payoff structure. Expectancy combines R:R with win rate into a single number representing average profit per trade: Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss). Two strategies can have identical R:R but very different expectancy if their win rates differ — expectancy is the more complete profitability metric, but R:R remains the faster pre-trade filter.