Risk/Reward

R:R defines payoff structure. Combine with win rate to compute expectancy and ensure long‑term viability.

Formulas

• R:R = Reward / Risk (both expressed in R).
• Expectancy = WinRate × AvgWin − (1 − WinRate) × AvgLoss.

Application

1. Choose targets from structure (swing, ADR, liquidity) not from hope.
2. Record average R per setup; discontinue setups with negative expectancy.

Detailed Calculation Example

Scenario: You risk $200 per trade (1R = $200).

• Trade 1: Win +$400 (2R)
• Trade 2: Loss −$200 (1R)
• Trade 3: Win +$600 (3R)
• Trade 4: Loss −$200 (1R)
• Trade 5: Win +$400 (2R)

Step-by-step expectancy:

1. Win rate = 3 wins / 5 trades = 60%
2. Avg win = (400 + 600 + 400) / 3 = $466.67 (2.33R)
3. Avg loss = (200 + 200) / 2 = $200 (1R)
4. Expectancy = 0.60 × 2.33R − 0.40 × 1R = 1.398R − 0.4R = +0.998R per trade
5. Over 100 trades: +99.8R = +$19,960 (with $200 risk per trade)

Case Study: Strategy A vs Strategy B

Strategy A (High Win Rate, Low R:R):

• Win rate: 70%, Avg win: 0.8R, Avg loss: 1R
• Expectancy = 0.70 × 0.8R − 0.30 × 1R = 0.56R − 0.30R = +0.26R per trade

Strategy B (Lower Win Rate, Higher R:R):

• Win rate: 45%, Avg win: 2.5R, Avg loss: 1R
• Expectancy = 0.45 × 2.5R − 0.55 × 1R = 1.125R − 0.55R = +0.575R per trade

Conclusion: Strategy B generates 2.2× more expectancy per trade despite lower win rate, because R:R compensates.

Real Trade Example: GBPUSD Swing

• Entry: 1.2650
• Stop: 1.2580 (70 pips = 1R = $700 on 1 lot)
• Target 1: 1.2790 (140 pips = 2R) — close 50%
• Target 2: 1.2930 (280 pips = 4R) — close remainder
• Actual result: Hit T1 (+$700), T2 stopped at +3.5R (+$2,450)
• Total: +$3,150 (4.5R average)

Break-Even Analysis

Minimum win rate needed for positive expectancy:

• If R:R = 1:2, need win rate > 33.3%
• If R:R = 1:3, need win rate > 25%
• If R:R = 1:1.5, need win rate > 40%

Formula: Min WinRate = 1 ÷ (1 + R:R)