Risk-Reward Ratio (R/R)
ES: Risk-Reward Ratio (R/R) PT: Razão Risco/Retorno
The most elementary metric in professional trading: the proportion between what you can lose and what you can gain. A ratio of 1 to 3 means risking one unit to make three, and it defines whether the trade has a favourable asymmetry before you even consider probability.
What Is the Risk-Reward Ratio?
The risk-reward ratio is the mathematical proportion between a trade’s maximum acceptable loss and its target gain. It is expressed as 1 to X, where X indicates how much reward you get for each unit of risk.
A ratio of 1 to 3 means that for every unit you can lose — the distance between entry and stop — you expect to make three, that is, the distance between entry and target.
It is the most fundamental metric in professional trading because it defines the asymmetric structure of the payoff: it tells you whether the trade has a mathematical edge before you even consider the probability of success. Warren Buffett, Paul Tudor Jones and other elite traders repeat the same principle: look for asymmetric bets, cap the loss and maximise the gain. This ratio quantifies it precisely.
The most widespread practical rule is to reject any trade below 1 to 2. The reason is arithmetic: with a 50% hit rate — the equivalent of a coin flip — a 1 to 2 ratio already produces positive expectancy. At 1 to 1 you need to be right more than half the time, dangerously close to chance. And at 1 to 3 you can make money being right only 40% of the time.
That slack in the hit rate is precisely the strength of a favourable ratio.
Calculation and Application
The calculation requires identifying three levels before entering: the entry price, the stop at which the position closes if the market goes against you — whose distance from entry defines the risk — and the target at which profits are taken, whose distance defines the reward.
The formula is (entry − stop) / (target − entry) for long positions, and the inverse for shorts.
A stock example: entry at 180, stop at 175 and target at 195. The risk is 5 and the reward 15, giving a ratio of 1 to 3, professional and perfectly acceptable.
An options example: a call bought at 5 in premium with thirty days to expiration. The maximum loss is the premium, 5, and the target is to sell at 15, giving a profit of 10 and a ratio of 1 to 2, also acceptable.
Some traders use a multiple-target approach: closing half the position at 1 to 2, a quarter at 1 to 4 and the rest at 1 to 10. The combined ratio comes out better than a single target.
It is critical that both stop and target rest on objective analysis rather than arbitrary figures. Stops should sit at technical levels — support, resistance, moving averages or volatility-based levels — and targets likewise: resistance, Fibonacci extensions, historical price behaviour. An arbitrary stop of the "5% below entry" kind, or a target of the "200 sounds good" kind, produce poor ratios systematically.
Calculate it before entering: if it comes out below 1 to 2, the right move is to pass on the trade or adjust the three levels. Never argue with the arithmetic out of conviction: this discipline is what preserves capital through losing streaks.
Combined With the Hit Rate: Expectancy
The ratio alone is not enough: it must be combined with the probability of success to calculate expectancy, the average gain per trade.
The formula is (hit rate × average gain) − (miss rate × average loss), where both rates sum to one hundred per cent. Positive expectancy indicates a strategy profitable over the long run; negative expectancy leads to losses however much discipline you apply.
The classic matrix is revealing. A ratio of 1 to 1 requires being right more than 50% of the time to be profitable. 1 to 2, more than 33%. 1 to 3, more than 25%. And 1 to 5, more than 17%.
That table explains why high ratios compensate for low hit rates. Paul Tudor Jones has stated hit rates of 40% to 50% with average ratios of 1 to 3 or 1 to 5, producing exceptional returns. The method consists of cutting losers fast, keeping losses small, and letting winners run.
There is a natural inverse relationship between the two figures: the higher the risk-reward ratio, the lower the hit rate tends to be. The reason is obvious: a ratio of 1 to 10 implies a very distant target, and the statistical probability of reaching it is low by definition. A ratio of 1 to 1 with a nearby target is hit far more often but requires more trades to compensate.
Professionals optimise total expectancy, not the ratio in isolation. Two numerical examples make it clear. System A hits 70% with a ratio of 1 to 1.2, giving 0.70 × 1.2 − 0.30 × 1 = 0.54. System B hits 35% with a ratio of 1 to 4, giving 0.35 × 4 − 0.65 × 1 = 0.75. System B is mathematically superior despite being right half as often.
The key is finding the optimal point between the two figures for each specific strategy.
In Options Strategies
In options the ratio is usually more transparent than in shares, because maximum loss and maximum gain are defined.
In long calls and puts, maximum loss is the premium and the target is flexible. A call bought at 5 with a target sale at 15 gives a ratio of 1 to 2.
In credit spreads — bull put, bear call — the ratio is usually unfavourable. A 5-wide spread with 1.50 of credit has a maximum gain of 1.50 and a maximum loss of 3.50, a ratio of 1 to 0.43. It is compensated by a high hit rate, 70% to 85%, and demands disciplined management.
In debit spreads the ratio is favourable. A 5-wide bull spread paid at 2 has a maximum gain of 3 and a maximum loss of 2, or 1 to 1.5.
In iron condors, the ratio runs from 1 to 0.3 up to 1 to 0.5: extremely unfavourable, compensated by a very high probability of 70% to 80%.
In straddles and strangles, the ratio varies with volatility: maximum loss is the total premium and the gain is technically very large, but it requires a volatility expansion or a significant move.
Naked short options have a potentially catastrophic ratio: unlimited risk against a reward capped at the premium. For very experienced traders only.
The general rule is that debit strategies have a favourable ratio, paying up front in exchange for potentially larger gains, while credit strategies have an unfavourable one compensated by high probability. The choice depends on risk appetite, market view and horizon.
The advantage of options is that the defined maximum loss makes the ratio always precisely calculable. In shares, an opening gap can exceed the distance to the stop; options offer genuinely bounded exposure.
Practical Trading and Psychology
Applying this requires considerable mental discipline, built on five habits.
Discipline before entry: calculate the ratio before executing, and pass on or adjust the trade if it comes out below 1 to 2. A written plan: documenting entry, stop and target before trading, which prevents emotion from taking over. Consistency in sizing: applying sizing rules of 1% to 2% of the portfolio, which is what lets the discipline compound across many trades. Not adjusting on the fly: moving the stop further out to avoid being swept is a betrayal of the original thesis, and accepting the loss at the defined level preserves long-run expectancy. And record keeping: noting the ratio actually achieved on each trade and comparing it with the one planned, because the deviations reveal execution problems.
The psychological errors are five. Moving the stop to avoid the loss, which substitutes hope for discipline. Taking profits too early, which cuts winners and destroys the arithmetic. Revenge trading, entering poor-ratio trades after a loss to win it back. Cherry-picking metrics, reporting only the winning trades. And conviction bias, accepting a suboptimal ratio because "this time is different".
A typical professional plan specifies five things: the minimum ratio threshold, usually 1 to 2 or 1 to 3; the sizing rules, 1% to 2% per trade; the expectancy objective, positive across more than a hundred trades; the expected hit rate, 40% to 50% for a 1 to 3 strategy; and the maximum tolerance for consecutive losses, five to ten before reviewing the strategy.
Paul Tudor Jones’s formulation sums up the concept: a five to one ratio lets you be right only 20% of the time and break even. That is the fundamental insight: a favourable ratio tolerates many losing trades without the capital collapsing.
Psychology is what decides it: you have to accept that more than 60% of trades will lose, and that this is fine when the winners are five times bigger. Most retail traders fail precisely here, because they would rather be right — a high hit rate with a poor ratio — than be profitable.
Common Ratios and What They Demand
Each ratio demands a different minimum hit rate to produce positive expectancy.
| Ratio | Minimum hit rate to break even | Example strategies | Typical expectancy |
|---|---|---|---|
| Over 50% | Very short term, mean reversion | Marginal; demands great discipline | |
| Over 33% | Swing and short term | Positive at a 40% hit rate | |
| Over 25% | Intermediate swing | Clearly positive; the professional standard | |
| Over 17% | Position trading | Accepts a low hit rate in exchange for large winners | |
| Over 9% | Breakouts and events | Tudor Jones style; demands great patience |
Frequently Asked Questions
What counts as a good ratio?
The reason is arithmetic: at 1 to 2, a 40% hit rate already produces positive expectancy; at 1 to 3, 30% is enough. That margin is the cushion against the inevitable losing streaks.
Some strategies — breakouts, trend following — naturally produce high ratios, from 1 to 4 up to 1 to 10. Others — mean reversion, very short-term trading — have lower ratios but higher hit rates.
What matters is that the target ratio fits the characteristics of the strategy.
How does it differ between shares and options?
Credit spreads have an unfavourable ratio, below 1 to 1, compensated by a high probability of profit. Debit spreads and long options have a favourable ratio but lower probability.
Balancing those two things is the trader’s central decision.
Should I always demand a minimum of 1 to 3?
The universal rule is that any strategy with a sustained ratio below 1 to 1.5 requires an exceptional hit rate, above 70%, to be profitable. If that rate is not guaranteed, the strategy is doomed across many trades.
What exactly is expectancy?
An example: a 50% hit rate, an average gain of 100 and an average loss of 50 give 0.50 × 100 − 0.50 × 50 = 25 per trade. A hundred trades at that expectancy produce about 2,500 in profit, and multiplied by frequency that gives the annual return.
Professional systems aim for expectancy between 50 and 500 per trade after commissions. Low-expectancy systems, below 20, require enormous volume to compensate.
How does it prevent large losses?
With a limit of 500 per trade, ten consecutive losses come to 5,000 rather than the 50,000 or more that could accumulate without stops. No single trade can destroy the account.
Combined with sizing of 1% to 2% of the portfolio per trade, the impact of any trade is bounded to that percentage of capital. Surviving the losing streaks is what lets you keep trading when the strategy starts working again.
Without this discipline, a single large loss can take the whole account, something seen regularly among retail traders.