In the world of trading and investing, two crucial metrics that determine the effectiveness and profitability of a trading strategy are its Reward: Risk ratio (often expressed as R-multiple) and the Win Rate (sometimes referred to as accuracy). These metrics are interrelated and play a pivotal role in shaping a strategy’s potential success. Understanding their relationship helps traders design and refine strategies to achieve sustainable profitability.
What is Reward: Risk Ratio (R-Multiple)?
Reward: Risk Ratio, also known as R-multiple, measures the potential return of a trade relative to its risk. It provides a quantifiable way to assess how much a trader stands to gain compared to the amount they are willing to lose on a trade.
R-Multiple: It is the ratio of the profit (or loss) achieved on a trade relative to the initial risk. For example, if a trader risks $100 on a trade and earns $300, the R multiple is 3 (i.e., $300 profit / $100 risk).
The formula to calculate a strategy’s Reward: Risk Ratio is:
Reward: Risk = Average Win / Average Loss
What is Win Rate (Accuracy)?
Win Rate refers to the percentage of trades that result in a profit out of the total number of trades. It is a measure of how often a trader’s strategy is successful in achieving its profit targets.
The formula to calculate a strategy’s Win Rate is:
Win Rate = (Number of Winning Trades / Total Number of Trades) × 100
The Relationship Between Reward: Risk Ratio and Win Rate
The interaction between Reward: Risk and Win Rate is crucial in determining the profitability of a trading strategy. Here’s how these two metrics influence each other:
Chart: %-Win rate required to break even (Generated with QF Alphawolf software)
Example: High Reward: Risk with Low Win Rate (Positive Skew PnL Distribution)
Suppose a strategy has an R multiple of 4 (risking $100 to gain $400) but a win rate of 30%. Even though the strategy only wins 30% of the time, the high R multiple ensures that the profits from the winning trades significantly outweigh the losses from the losing trades. This can result in overall profitability despite a low win rate.
Example: Low Reward: Risk with High Win Rate (Negative Skew PnL Distribution)
A strategy might have a Reward: Risk ratio of only 0.75 (risking $100 to gain $75) with a win rate of 75%. The high win rate ensures that a significant portion of trades are profitable. However, the low Reward: Risk ratio means that each win does not contribute significantly to the overall profit compared to the risk taken. The overall profitability is still achievable but may be less robust compared to strategies with higher R multiples.
Combining high win-rate and low win-rate trading strategies in a portfolio can be highly effective for optimizing overall results. A high win-rate strategy, with a greater percentage of profitable trades, often compensates for lower risk-reward ratios and provides consistent gains. Conversely, a low win-rate strategy, typically characterized by higher risk-reward ratios, can yield substantial profits despite fewer winning trades. By diversifying these strategies within a portfolio, traders can balance stability and potential returns. The high win-rate strategies offer steady performance, while the low win-rate strategies can generate significant profits during winning streaks. This blend helps mitigate the volatility and risk associated with relying on a single strategy, creating a more robust and resilient trading approach.
Calculating Profitability with Reward: Risk and Win Rate
The overall profitability of a trading strategy can be calculated by considering both Reward: Risk and win rate. The following formula helps to assess the expected profitability:
Expected Return = (Win Rate × Average Win) − ((1 − Win Rate) × Average Loss)
Conclusion
The interplay between Reward: Risk ratio and Win Rate is fundamental in designing a successful trading strategy. While a high R-multiple can compensate for a low win rate, a high win rate with a low R-multiple requires careful management to ensure overall profitability. Understanding this balance helps traders make informed decisions and optimize their strategies for better financial outcomes. Traders should continuously evaluate and adjust their strategies to maintain an optimal balance between these metrics, ensuring long-term success in their trading endeavors.