Risk-Reward Ratio Explained — and Why 1:3 Isn't a Magic Number
"Always trade with at least a 1:3 risk-reward." You've heard it a hundred times. The math actually doesn't support that as a universal rule. Here's what does.
What R:R actually measures
Risk-reward ratio is the distance from entry to target divided by the distance from entry to stop. It's a planning number, set before you take a trade.
Example:
Entry $100 · Stop $98 · Target $106
Risk = $2 · Reward = $6 · R:R = 1:3
One unit of risk = "1R." A 1:3 trade pays you 3R if it works, costs you 1R if it doesn't.
The myth: "1:3 is the minimum"
This advice is everywhere because it's simple, not because it's correct. R:R only tells half the story. The other half is your win rate. The two are mathematically yoked through the breakeven equation.
1:1 R:R → 50% breakeven
1:2 R:R → 33% breakeven
1:3 R:R → 25% breakeven
1:5 R:R → 17% breakeven
So a 1:3 strategy needs 26%+ win rate to be profitable (before fees). Sounds great — until you realize most setups don't actually achieve 1:3 with a 26% win rate. Higher R:R targets fail more often. Lower R:R targets hit more often. There's a real tradeoff curve.
The tradeoff curve
The expectancy formula (the only one that matters)
Profitable when E > 0
This is the only formula you need to evaluate a strategy. Plug in your real win rate, real average win in R, real average loss in R. If E is positive, you have edge. If negative, you're paying to play.
Three profitable profiles, three different R:Rs
Profile A — Trend follower
Profile B — Swing trader
Profile C — Mean-reversion scalper
All three have positive expectancy. None of them are 1:3. The trend-follower has the highest R:R but the lowest hit rate — those long stretches of losses are why most retail abandons trend systems before they pay off. The scalper barely beats 1:1 but wins so often the math still works.
Why "always 1:3" fails as advice
If you force every trade to a 1:3 target, you'll do one of three things:
- Tighten your stop unnaturally to make the math work — gets you stopped out by noise, win rate drops below the 25% breakeven.
- Set unrealistically far targets — they don't get hit before price reverses; you watch +1.5R turn into a loss.
- Skip valid setups that only project a 1:1.5 reward — even though many of those have positive expectancy at 60%+ win rate.
R:R should match your strategy's nature
| Strategy type | Realistic WR | Realistic R:R |
|---|---|---|
| Breakout / trend following | 30–40% | 1:2.5 to 1:5 |
| Swing / pullback | 45–55% | 1:1.5 to 1:2.5 |
| Mean reversion | 60–75% | 1:0.7 to 1:1.5 |
| Scalping | 65–80% | 1:0.5 to 1:1 |
Pick the R:R from your strategy, not from a YouTube rule. A trader who naturally cuts losses fast and rides winners can target 1:5. A trader who's good at reading reversals at support might do best at 1:1.
The hidden killer: variance
Even with positive expectancy, low-WR / high-R:R strategies have brutal drawdowns. A 35% WR system has a real chance of 8 losses in a row in any 50-trade sample. Can you tolerate −8R drawdown before the system pays off? Most retail can't.
At WR=35%, in 100 trades, ~80% chance of at least 6 losses in a row
The professional approach: track expectancy in R
- For every closed trade, log the R outcome (+2.4R, −1.0R, +0.6R, etc.)
- After 30+ trades, compute average R per trade
- If positive over a sample of 50+ trades across regimes — your strategy has edge
- If negative or zero — fix the strategy or stop trading it
This tracking is timeframe-and-instrument-agnostic. A trader doing 5 trades/month and one doing 50/month can compare apples to apples in R-units.