Sharpe ratio practicality

There is a normality assumption in the applicability of sharpe ratio. But, practically most distributions are non-normal, how then is the sharpe ratio useful and why is it so popular? On that note, if the standard deviation is only effective when the distribution is normal, why is it so commonly used to describe the risk? I’m terribly confused with this. Please help me out.


It’s easy.

It isn’t.

It’s easy.

Okay, that was succinct. But got your point.
So, standard deviation doesn’t assume normal distribution then? Because, one of the limitations of the sharpe ratio was that it uses standard deviation as a measure of risk which might not be the best. To quote investopedia, " Kurtosis—fatter tails and higher peaks—or skewness can be problematic for the ratio as standard deviation is not as effective when these problems exist." And the CFA material, “The conceptual limitation of the Sharpe ratio is that it considers only one aspect
of risk, standard deviation of return. Standard deviation is most appropriate as a risk
measure for portfolio strategies with approximately symmetric return distributions.” Please help me out here.

Thanks !

If the return distribution has significant skewness or significant excess kurtosis, you will want to take those into account when assessing the riskiness of the portfolio.

There are many distributions that are approximately symmetric (e.g., Student’s t-distributions, and continuous uniform distributions). You can use standard deviation of returns as a first-order risk measure, but you should consider the excess kurtosis (for example,-\dfrac{5}{6} for a uniform distribution) as well.

Makes a lot of sense. Thankyouu!

My pleasure.

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