Risk-Reward Ratio
Category
Performance-Analyse & Journaling
Sub-category
Journal-Pflichtfelder
Curated by
Last reviewed
The risk-reward ratio (RRR) relates a trade's possible profit to the amount risked: target distance divided by stop distance. An RRR of 3:1 means the planned profit is three times the planned loss (3R). It is only half the truth: only together with the hit rate does expectancy emerge – a high RRR with too low a hit rate loses just like the reverse.
Context & Mechanics
Definition and calculation
The RRR is calculated before the trade from three prices: entry, stop and target. RRR = (target − entry) ÷ (entry − stop) for longs. A trade with entry $100, stop $98 and target $106 has an RRR of 6 ÷ 2 = 3:1 – it promises 3R. Important: the RRR describes the plan, not the outcome – real trades rarely end exactly at the planned point due to partial sales, trailing or slippage. For strategy evaluation the realised R-multiples count.
RRR and hit rate belong together
The RRR alone says nothing about profitability: what matters is the combination with the hit rate – the expectancy. The break-even formula is: required hit rate = 1 ÷ (1 + RRR). At 1:1 you need over 50%, at 2:1 over 33%, at 3:1 over 25% – plus costs in each case. From this follows the structural advantage of higher RRRs: they forgive low hit rates and estimation errors. But there is no free lunch – more distant targets are reached less often; anyone artificially inflating the RRR (tighter stop, distant target) usually lowers the hit rate in return.
Typical distortions
Three errors ruin the RRR calculation in practice: wish targets instead of market structure (the target sits beyond the next resistance just so 3R comes out), unrealistically tight stops (triggered in noise before the idea can work) and moving stop or target during the running trade. Robust process: stop at the invalidation, target at the next relevant structure – and if the RRR then sits below ~2:1, skip the trade instead of bending the numbers.
Why it matters for traders
The RRR is the filter that sorts out weak setups before entry, and the bridge between the individual trade and strategy statistics. In the GlanWick simulator, RRR scenarios with different hit rates can be calculated by way of example without real capital – GlanWick is a training and simulation tool and not a prop firm itself.
Execution Example
Two traders evaluate the same long setup: entry $30.00, stop $29.00 ($1.00 risk). Trader A sets the target at the next resistance at $32.50; trader B wants “at least 5R” and sets the target at $35.00 – beyond two resistance zones.
- Trader A: RRR = 2.50 ÷ 1.00 = 2.5:1. Break-even hit rate: 1 ÷ 3.5 ≈ 29%. Historically the setup reaches the first target in ≈45% of cases → expectancy: 0.45 × 2.5 − 0.55 × 1 = +0.575R per trade.
- Trader B: RRR = 5 ÷ 1 = 5:1, break-even rate ≈17%. But the target beyond two resistances is historically reached only in ≈12% → expectancy: 0.12 × 5 − 0.88 × 1 = −0.28R – a losing system despite an impressive RRR.
- Lesson: not the higher RRR wins, but the better combination of RRR and realistic hit rate.
- Practice check: estimate both figures before every trade – if the expected hit rate sits below the break-even rate of the planned RRR, the trade is a bet against your own statistics.
Execution Risk & Errors
Optimising the RRR in isolation without pricing in the falling hit rate of distant targets
Placing targets beyond obvious resistances just to show a pretty RRR
Setting stops unrealistically tight so the ratio works on paper
Confusing planned and realised RRR and keeping statistics with planned values
Entering trades with an RRR below ~2:1 because the setup “feels safe”
Frequently Asked
What risk-reward ratio should I aim for?
A minimum of 2:1 is common for swing setups – as a rule of thumb, not a law of nature. What matters is your own statistics: the RRR must fit the strategy's real hit rate so expectancy is positive.
How are RRR and hit rate connected?
Via the break-even formula: required hit rate = 1 ÷ (1 + RRR). At 2:1, 33.3% suffices, at 3:1, 25% – plus costs. Higher RRRs lower the hurdle but are reached less often: both figures move in opposite directions.
Is a 1:1 RRR trade always bad?
No – with a very high hit rate (e.g. mean-reversion systems at ≥60%) 1:1 can be profitable. It just leaves little safety margin: even small deteriorations of the rate or higher costs tip expectancy negative.
What is the difference between RRR and R-multiple?
The RRR is the planned ratio before the trade; the R-multiple the realised result afterwards (e.g. +1.7R after a trailing exit). Strategy statistics build on realised R-multiples, not planned values.