Sortino Ratio

What is a Good Sortino Ratio?

The higher the Sortino ratio, the greater the expected risk-adjusted returns — all else being equal.

A higher Sortino ratio signifies a higher return per unit of downside risk, while a lower ratio indicates lower returns per unit of negative risk.

In accordance with the trade-off theory, the minimum rate of return (or “hurdle rate”) required by investors should increase the greater the level of risk.

Therefore, a higher Sortino ratio must result in more returns to compensate investors for the incremental risk (and vice versa).

However, since the ratio is calculated using past data, it is still a flawed indicator of future performance.

Sortino Ratio vs. Sharpe Ratio: What is the Difference?

One common critique of the Sharpe ratio is how the standard deviation of a portfolio’s returns represents the portfolio risk.

In short, the notion that all equity returns follow a normal distribution is an oversimplified assumption — which is the reason for numerous variations of the Sharpe ratio such as the Sortino ratio.

In the case of the Sortino ratio, the downside deviation replaces the standard deviation of the total portfolio’s returns.

On that note, the Sharpe ratio tends to be more applicable for portfolios exhibiting low volatility, while the Sortino ratio is more practical for portfolios with high volatility.

With that said, the Sortino ratio is used frequently by returns-oriented investors in the financial markets that pursue higher returns in excess of the broader market (and thereby use riskier strategies).

Sortino Ratio Calculator

We’ll now move to a modeling exercise, which you can access by filling out the form below.

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Sortino Ratio Calculation Example

Suppose the portfolio of a hedge fund had the following performance in returns for 2021.

2021 Hedge Fund Portfolio Performance

• January = (1.0%)
• February = (4.0%)
• March = (8.0%)
• April = 10.0%
• May = 20.0%
• June = 25.0%
• July = 16.0%
• August = 12.0%
• September = 5.0%
• October = 3.0%
• November = (2.0%)
• December = (4.0%)

Given the monthly returns data, we can compare the portfolio returns to the risk-free rate, which we’ll assume to be 2.5%.

• Risk-Free Rate (rf) = 2.5%

If we subtract the risk-free rate from the portfolio return for each month, we are left with the excess return in each month.

But the Sortino ratio focuses solely on the downside deviation, so in the formula for the next column, we will insert an “IF” function where only the negative monthly returns appear (i.e. positive excess returns will result in an output of 0).

The five months in which the returns were negative are 1) January, 2) February, 3) March, 4) November, and 5) December – reflecting how losses were concentrated on the beginning and end of the year.

In the next column, we’ll calculate the square of the negative returns, which will be used in the downside standard deviation formula.

To calculate the downside deviation, we’ll add up the column we just completed and use the “SQRT” function on the sum, which is subsequently divided by the total number of months.

• Downside Deviation (σd) = 4.4%

The next step is calculating the average excess return across the entire period.

• Excess Returns, Average = 3.5%

Upon dividing the average excess returns of 3.5% by the downside deviation of 4.4%, we arrive at a Sortino ratio of 0.80.

• Sortino Ratio = 3.5% ÷ 4.4% = 0.80