How to decode key MF ratios

The benefits of investing in mutual funds are quite well known to the public. Fund factsheets and other sources such as bl.portfolio MF Star Track MF ratings, Value Research, and Morningstar provide you with certain statistical ratios which can give you more insights into the performance of the mutual fund.

In our earlier editions, we have attempted to explain ratios such as rolling returns, portfolio turnover, tracking error, and tracking difference. Here, we will try to decode a few ratios and explain how one can use them for making investing decisions in actively managed equity mutual funds.

Risk indicators

The return of every mutual fund varies across different time periods due to various factors. However, the degree of risk may not be similar for all mutual funds and this can be measured using statistical ratios.

Beta is a commonly used risk metric which calculates a mutual fund’s volatility relative to its benchmark. For instance, considering last three years, Nippon India Large Cap Fund has a beta of 1.01 which means that if its benchmark moves up/down by one per cent, the fund’s NAV goes up/down by 1.01 per cent. An index fund generally has a beta of 1. However, do note that as said earlier, beta just measures fund’s sensitivity to its benchmark while it doesn’t capture the inherent volatility of a fund.

Standard deviation (SD) is another ratio to measure risk of any mutual fund. It measures the degree of how much the returns of a mutual fund vary from its historical average return over a period of time on an annualised basis. For instance, as per ACE MF, considering last three years data, Canara Robecco Blue Chip has a SD of about 14 per cent which means that in the last three years the returns have varied about 14 per cent from the fund’s average annual return. Standard deviation of small-cap funds is typically higher than that of large cap equity funds. Typically, standard deviation shows volatility of returns. However, a higher SD should not be always be viewed in a bad light as it also shows that the fund may have also generated higher returns.   

Risk adjusted measures

The risk measures such as beta and standard deviation have certain drawbacks and hence shouldn’t be seen in isolation. In this backdrop, risk adjusted measures can prove to be helpful.

Sharpe ratio is used to measure the excess return on every additional unit of risk taken. Hence, the higher the Sharpe ratio, the better it is for the fund. This can be calculated by dividing the excess return a fund has generated over risk-free rate of return by the fund’s SD. Assuming risk free rate of 7.79 per cent i.e. overnight MIBOR (as considered by multiple mutual funds), if we compare two flexi-cap funds i.e. HDFC Flexi Cap and Parag Parikh Flexi, we can see that both have generated 3-year CAGR returns of around 34 per cent and 31 per cent respectively while their Sharpe ratios are 0.52 and 0.57 respectively. This shows that despite having generated lower returns than HDFC Flexi Cap, the Parag Parikh fund has done a better job when it comes to risk-adjusted returns.

However, as we discussed earlier, volatility is not always bad. Investors are concerned about downside but don’t mind exposure to upside volatility. Sortino ratio would come here to the rescue as instead of SD, it adjust the fund’s excess returns over risk free rate with downside deviation. Hence, Sortinio ratio punishes the fund only for downside volatility rather than overall volatility. Considering Sortino ratio for the two funds we get a contrary view as HDFC Flexicap has a higher number which indicates that despite having lower Sharpe ratio, the HDFC Fund generates higher downside risk adjusted returns.

Do note that these ratios too shouldn’t be seen in isolation as there can be instances when, we can get high Sharpe and Sortino ratios for certain funds which generate very low returns.

R-squared is a measure of the percentage of a mutual fund’s performance as a result of the benchmark. Hence, index funds typically have R-squared close to 100. For instance, an actively managed large cap MF scheme ABSL Frontline Equity has an R-squared of about 98 per cent which means that 98 per cent of the variation in fund’s NAV ican be explained by the benchmark index S&P BSE 100-TRI due to which the fund’s performance may be simply replicating that of the benchmark.

Typically, actively-managed funds shouldn’t have such a high R-squared as one pays higher expense ratio for an actively-managed fund so that a fund can generate alpha. Instead of actively-managed funds with consistently higher R-squared, you can consider low-cost index funds.

The above doesn’t mean that you should straightaway invest in funds with lesser R-squared of, say less than 80, if you want to invest in actively-managed schemes. Along with R-squared, you should check other risk measures to arrive at a fair investing decision.