| name | risk-reward-ratio |
| description | Calculate long/short planned R-multiples and net expectancy. Use when evaluating executable entry, stop, target, win/loss distribution, costs, gaps, and uncertainty without treating R:R as trade quality by itself. |
| license | Apache-2.0 |
| metadata | {"author":"ske-labs","version":"4.0"} |
Risk-Reward Ratio (R:R)
R:R compares potential profit to potential loss, helping filter high-quality trades.
Calculation
For a long: R:R = (Target - Entry) / (Entry - Stop). For a short: R:R = (Entry - Target) / (Stop - Entry). Require positive denominators and use executable prices plus expected slippage/fees.
Example: Entry $100, Stop $95, Target $115 => R:R = $15 / $5 = 3:1.
The zero-cost binary breakeven R:R is (1 - Win Rate) / Win Rate. Actual breakeven is higher after costs, gaps, partial fills, and non-binary exits.
| Win Rate | Minimum R:R | Breakeven R:R |
|---|
| 40% | 1.5:1 | 1.5:1 |
| 50% | 1:1 | 1:1 |
| 60% | 0.7:1 | 0.67:1 |
| 70% | 0.5:1 | 0.43:1 |
Expectancy
Use realized net payoff distributions: E = p × average_win - (1-p) × average_loss - average_costs. Report uncertainty, tail loss, sample period, and regime stability. Planned R:R alone does not establish win probability or trade quality.
Optimizing R:R
Improve Entry: Enter at better levels (OTE, pullbacks), wait for confirmation at S/R, use limit orders at key levels.
Define Stop: use thesis invalidation plus a validated tick/volatility buffer, then size from the resulting risk.
Define Target: use observable structure, time exit, or a tested rule; moving a target farther away improves displayed R:R but can reduce hit probability.
Filter on conservative net expectancy, tail risk, liquidity, and mandate fit. Do not label a trade good or excellent from its planned R:R.
Workflow
- Identify entry from technical analysis
- Set stop loss based on structure or ATR (see stop-loss-strategies)
- Calculate R:R using the formula above
- Filter -- require positive conservative net expectancy and mandate compliance
- Set targets at R:R milestones (1R, 2R, 3R) for partial exits
Evidence and Validation
- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
- Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
- Research basis: R-multiples describe a planned payoff but do not establish expectancy. Include win probability, costs, gaps, and partial fills; FINRA notes that trading costs persist even with zero commissions.
Key Rules
- Evaluate win probability and payoff jointly; neither high R:R nor high win rate is sufficient.
- Use executable, predeclared targets and stops rather than decorative ratios.
- Avoid selection bias from waiting only for entries that make the displayed ratio attractive.
- Return
no trade when net expectancy, uncertainty, liquidity, or risk limits fail.
Related Skills
- position-sizing -- R:R determines trade quality; position sizing determines trade quantity
- stop-loss-strategies -- stop placement defines the risk side of the R:R equation
