Sharpe Ratio
Explanation
The Sharpe Ratio, developed by Nobel laureate William Sharpe in 1966, divides a portfolio's excess return (above the risk-free rate) by its standard deviation. The result tells you how much return you earned for each unit of risk you accepted.
A Sharpe Ratio of 1.0 is generally considered acceptable. Above 1.5 is strong. Above 2.0 is excellent and rare over multi-year periods. The S&P 500 has historically delivered a Sharpe Ratio of approximately 0.4–0.6 over rolling 10-year windows.
The Sharpe Ratio is the most widely used performance metric in institutional finance. It appears in virtually every fund factsheet, endowment report, and portfolio analytics dashboard. Its popularity stems from simplicity: one number that captures the return-risk trade-off.
Formula
| Variable | Meaning |
|---|---|
| S | Sharpe Ratio |
| Rp | Portfolio return (annualized) |
| Rf | Risk-free rate |
| σp | Standard deviation of portfolio returns (annualized) |
Example
A portfolio returned 12% annualized over 3 years with a standard deviation of 15%. The risk-free rate averaged 4%.
For every 1% of volatility, the portfolio earned 0.53% of excess return. This is roughly in line with long-term equity market averages—acceptable but not exceptional.
How Stoquity Uses This
Stoquity displays the Sharpe Ratio prominently on each portfolio's Analytics tab. The AI engine uses Sharpe as one input when evaluating whether a proposed trade improves the portfolio's risk-adjusted profile. Charter compliance checks flag any portfolio whose rolling Sharpe drops below its defined floor.
Common Mistakes
- The Sharpe Ratio penalizes upside volatility the same as downside—the Sortino Ratio addresses this
- Sharpe Ratios below 1 year are unreliable due to insufficient data
- Comparing Sharpe Ratios across different time periods is misleading