Risk & Position Sizing
Risk & Position SizingBeginner9 min read

Risk-Reward Ratios

Why this matters

Win rate alone is a vanity metric. A strategy that wins 70% but risks $300 to make $50 can still lose money. Risk-reward is the other half of expectancy.

Thinking in R — multiples of what you risked — lets you compare trades fairly and design setups that do not need perfection.

What Risk-Reward Means

Risk-reward compares potential profit to potential loss on a planned trade. If you risk $100 to target $200, that is 1:2 (risk one to make two).

Measure from entry to stop (risk) and entry to target (reward). Hope is not a target.

  • Risk = entry to stop (dollars or R)
  • Reward = entry to take-profit
  • R:R = reward ÷ risk

1:2 Risk-Reward

Stop one unit below entry, target two units above — asymmetric payoff sketch.

Win Rate Math

At 1:1, you need to win more than about half the time after costs to profit. At 1:2, you can win less often and still come out ahead if losses stay controlled.

Example: risk $100, target $200. Two losses (−$200) and one win (+$200) scratch before fees. A bit better than 33% wins starts printing — as long as you actually take the full losers and winners as planned.

  • Higher R:R → lower required win rate
  • Lower R:R → you need to be right more often
  • Fees and slippage raise the bar either way

Link to Expectancy

Expectancy ≈ (win% × average win) − (loss% × average loss). Risk-reward shapes average win vs average loss.

You can improve expectancy by cutting losers short, letting winners reach planned R, or selecting setups with better asymmetric structure — not by wishing for higher win rate alone.

  • Asymmetric payoffs reduce pressure to be right constantly
  • Moving targets to scratch winners kills R:R
  • Track results in R, not only dollars

Realistic Targets

A fantasy 1:10 target past three resistance shelves is not a plan. Map reward to structure you can actually sell into.

Sometimes the honest R:R is 1:1.2. Then you need selectivity and execution quality — or you pass on the trade.

  • Targets need liquidity and structure
  • Pass when reward does not justify risk
  • Partial profits can still preserve overall R if planned

Practical Habits

Before entry, write risk in R and planned reward in R. After exit, record realized R. Over time you will see whether your playbook actually delivers the asymmetry you assumed.

  • Plan R:R before clicking
  • Journal realized R every trade
  • Cull setups that never reach targets

Key Takeaways

Remember these points

  • Risk-reward compares planned reward to planned risk.
  • Higher R:R lowers the win rate you need.
  • Expectancy depends on both win rate and payoff asymmetry.
  • Targets must be realistic structural levels.
  • Track performance in R-multiples.

Common Mistakes

Chasing win rate only

High win rate with terrible payoff still loses. Measure both sides.

Imaginary targets

Marking 1:5 on the chart without a place to exit is fiction.

Cutting winners and letting losers run

That inverts R:R and destroys expectancy even with "good" entries.

Quiz

0/4 answered

1.Risking $100 to make $200 is an R:R of:

2.All else equal, improving R:R generally:

3.Expectancy depends on:

4.A useful habit is to:

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