Sortino Ratio
Explanation
The Sortino Ratio improves on the Sharpe Ratio by replacing total standard deviation with downside deviation—the volatility of returns that fall below a target rate (usually the risk-free rate or zero).
This distinction matters because investors generally welcome upside surprises. A stock that returns +2%, +15%, +3%, +20% has high standard deviation but only from positive outcomes. The Sharpe Ratio would penalize this volatility; the Sortino Ratio would not.
The Sortino Ratio was developed by Frank Sortino at the Pension Research Institute in the early 1980s. It gained wider adoption as behavioral finance research confirmed that investors experience roughly twice the pain from losses as the pleasure from equivalent gains (prospect theory).
Formula
| Variable | Meaning |
|---|---|
| Rp | Portfolio return |
| Rf | Risk-free rate or minimum acceptable return |
| σd | Downside deviation (standard deviation of negative returns only) |
Example
A portfolio returned 14% with a downside deviation of 8%. The risk-free rate is 4%.
For every 1% of downside risk, the portfolio earned 1.25% of excess return. A Sortino above 1.0 is generally considered good. This portfolio is delivering attractive returns without excessive drawdown risk.
How Stoquity Uses This
Stoquity calculates and displays the Sortino Ratio alongside the Sharpe Ratio on every portfolio's Analytics page. The AI engine references Sortino when evaluating asymmetric strategies—portfolios designed to capture upside while limiting drawdowns.
Common Mistakes
- Sortino and Sharpe often rank portfolios differently—a high-conviction growth portfolio may have a poor Sharpe but strong Sortino
- Downside deviation requires a clear definition of the target return threshold
- Like Sharpe, Sortino is unreliable over short measurement periods