To measure risk as the standard deviation of returns is fraught with issues. But if we understand its limitations, this measure has the advantage of simplicity.


Risk is easier to forecast than return. For example, based on a very large sample of daily US stock returns data from 1927 to 2018, the correlation in volatility from one month to the next is +69%.1 This number is much higher than any of the one-month forward correlations we’ve discussed so far on the return side. That’s without even trying: I just used the equal-weighted 21-day volatility as a predictor of volatility over the next 21 days. A caveat is that volatility is not always a good proxy for risk, especially if we define risk as exposure to loss. ...

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