The Sortino ratio measures return per unit of downside risk. It is the Sharpe ratio's cousin, with one twist: it divides return only by the volatility of the LOSING returns, so it stops penalising a stock for jumping the good way.
Take the average return above a minimum acceptable level (often the risk-free rate or zero), then divide by the downside deviation — the standard deviation of only the returns that fell below that level. Upside moves are ignored in the denominator. Example (illustrative): two stocks both average +10% excess return. One with symmetric swings has a Sortino near its Sharpe (say 1.2); one that jumps up but rarely falls hard has a small downside deviation and a much higher Sortino (say 2.5).
The Sharpe ratio treats a violent rally and a violent crash as equally "risky," which can unfairly penalise a stock whose big moves are mostly upward. Sortino corrects that asymmetry: when a stock's Sortino is much higher than its Sharpe, its bumps have been mostly upward; when the two are close, its risk is roughly symmetric.
The Sortino ratio is standard public statistics, not a Quantustik edge. It is one honest lens on the same question our risk metrics and calibrated forecast bands address: is a return worth the downside risk taken to earn it? None of this is investment advice.
Sharpe divides return by the volatility of all returns; Sortino divides only by the volatility of the losing ones. Sortino is higher when a stock's big moves are mostly to the upside.
As a rough guide, above 2 is often strong and above 1 acceptable — but like Sharpe it is only meaningful relative to a benchmark or the same asset over time, not as an absolute cutoff.
Because it uses only losing periods, Sortino rests on fewer data points and is noisier, especially over short windows. Read the two together.
Browse all S&P 500 tickers to see this metric applied to individual companies.
Educational research only — not investment advice.