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Sharpe Ratio vs. Sortino Ratio

Since its creation in 1966 to measure the performance of mutual funds’, the Sharpe Ratio has been the most popular calculation for determining a risk-adjusted evaluation of return on investment (ROI) performance. Although it is widely used, it does have limitations and issues. A few of those shortcomings can be overcome by using the Sortino Ratio, an alternative measurement that was first developed in the early 1980s. In this article, we will briefly introduce these two Ratios and explain their differences, similarities and individual use cases.  

Sharpe Ratio overview

The Sharpe Ratio measures how desirable a risky investment instrument or strategy performs compared to a risk-free investment, such as government-issued bonds, by taking into consideration the additional risk level involved when holding the asset. This is calculated by taking the average period’s return in excess of the risk-free rate and dividing this by the standard deviation of the return generating process.  

Though it’s a great measure of quality, the Sharpe Ratio’s limitations have been known for over 25 years. The creator, William F. Sharpe, highlighted such in his own 1994 review, which you can find in The Journal for Portfolio Management.

The first problem with the Sharpe Ratio is it does not distinguish between upside and downside volatility. Naturally, upside volatility is good. This phenomenon is exacerbated because the more significant outliers increase the standard deviation used in the calculation. The standard deviation is the denominator, meanwhile, the numerator is not affected. Therefore, the result is lowering the ratio’s value. The greater the volatility, the less accurate the Ratio will be. As a trader or investor, strong upside is a positive characteristic; however, the Sharpe Ratio will disguise this. When using the Sharpe Ratio, this should be taken into account. 

When there is a non normal distribution (positively or negatively skewed), the Ratio does not perform well. To its detriment for positively skewed return distributions, performance is achieved with less risk than the Sharpe Ratio would suggest.

If you’re unfamiliar with some of the terms noted above, we’ve covered the process of calculating Sharpe Ratio in forex in an earlier post.

The Sharpe Ratio is the most commonly used metric for assessing the viability of a strategy or portfolio. You’ve probably come across it on popular strategy analysis tools like Myfxbook. However, the Sharpe Ratio punishes strategies with large and aggressive returns because of these limitations noted above. As a trader or investor, large profits are the name of the game.

Sortino Ratio overview

The Sortino Ratio shares many similarities with the Sharpe Ratio, except the Sortino Ratio offers much more insight into the risk associated with a given strategy or asset. The Sharpe Ratio assesses profit, volatility (risk), and how much you could have otherwise profited from a risk-free investment, such as treasury-bills, gilt or the German bund.

The Sortino Ratio sets out to counter the Sharpe Ratio’s inherent flaws. To understand precisely how the Sortino Ratio achieves this, you can read our calculating Sortino Ratio in forex article.

Sharpe Ratio vs. Sortino Ratio

Here are the fundamental differences between Sharpe Ratio and Sortino Ratio, to help you understand which one to use and when.

Upside volatility is a plus; therefore, it should not be included in the risk calculation, as is the case with the Sortino Ratio.

Standard deviation in the Sharpe Ratio measures the dispersion of data around its mean, both above and below. However, the Sortino Ratio uses downside deviation; meaning upside volatility is not part of the ratio’s calculation whatsoever.

Generally, it is preferred to use the Sharpe Ratio when evaluating low-volatility investment portfolios or those fitting a normal distribution. If the investment or trading strategy being analysed consists of mostly bullish volatility. In that case, it’s more appropriate to use the Sortino Ratio when evaluating high-volatility portfolios.