Does Higher Volatility Translate into a Higher Return? Australian Fund Monitors 30 June 2021 There is a long held ideal that when investing in equities, the level of volatility is correlated to the return; the more risk you put on the table the greater the return you expect to get back. Of course, the amount of time invested also needs to be considered, but for investments over 3 years (and beyond) this ideal is generally accepted, as evidenced by the number of scatter graphs used in fund marketing material. Volatility is managed by fund managers in several different ways, but generally it comes down to portfolio construction. The number of stocks in the portfolio, the size of the position held in each stock (and sector), and the buy and sell triggers, all affect the volatility of the portfolio. Typically, the funds management industry uses Standard Deviation as a measure of volatility. Standard Deviation measures the dispersion of monthly returns both above, and below the average monthly return. The smaller the funds standard deviation, the less volatile it is. The larger the standard deviation, the more dispersed the returns are and the more volatile it is. But does this show through in data, and is past volatility any sort of indicator of how a manager should have performed? We have looked at the returns and standard deviation over the past 3 and 5 years of all Long Only Australian Equity Funds (107 funds) on the www.fundmonitors.com database and broken these into quintile rankings. The funds with the best performance fall into the 5th quintile (best) and funds with the lowest standard deviation fall into the 5th quintile (best). Looking at the data over 3 years as at the end of May 2021:
Running the data over 5 years shows that standard deviation and return become slightly more correlated:
Clearly, while there is some minor correlation in this data, the ideal of using standard deviation as a measure of manager skill, especially in isolation, is not a prudent investment conclusion. Investors and advisors should be looking at multiple risk data points such as Sharpe Ratio, Sortino Ratio, Up and Down Capture and Downside Deviation, to help them make the most effective investment decisions.
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