Sharpe Ratio
Continuing on our portfolio metrics series, we’re looking at the Sharpe Ratio. The Sharpe ratio is very easily calculated. It’s simply the mean period return of your portfolio (typically monthly) minus the risk free rate for each period divided by the standard of deviation of the returns of your portfolio. The equation written out might look something like this:
Sharpe Ratio = (Rp – Rf)/StdDp
Sharpe ratio attempts to quantify performance in a similar way that alpha does. Basically, it answers the question, “How much excess return did you get for the volatility assumed?” In this case, instead of using the market as a basis via beta, we are using the risk free rate which is typically set to the return of the shortest dated Treasury bill available.
The Sharpe ratio is not without fault. Much like alpha and beta, most of the issues come with how the ratio attempts to quantify risk. In this case, risk is equated with the standard of deviation of returns. This causes a problem because standard of deviation relies on normal distribution of volatility. As a result, Sharpe ratio is most effective for analyzing highly diversified, strict investing strategies for example index linked funds, large diversified mutual funds, and general asset classes. For actively traded portfolios, the Sharpe ratio oversimplifies the risk/reward trade-off and, as a result, can become misleading especially when used in small sample sizes.
As with most statistical measures created to quantify abstract ideas, Sharpe ratio is best used in conjunction with other statistically independent measures of risk/reward when attempting to quantify the success or failure of an investing strategy.
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Comments
[...] been writing on and off over the last few weeks. If you remember, the last post was on the Sharpe Ratio. The Sharpe ratio is a slightly more exacting portfolio risk calculation in comparison to the beta [...]
Good post. I have to admit, I don’t know a huge amount about the ratio. The ratio appears to be a nice one to use, but as you mention all these metrics should not be used as a stand alone measure.