MF Risk Measures: When Less Is More
The next time that you select a fund, remember that less risk not only means less pain but more gain also. The article explains the how and why of this theory
The next time that you select a fund, remember that less risk not only means less pain but more gain also. The article explains the how and why of this theory
A majority of investors choose their investment avenues based on return and its different cousins such as return compared to peers, benchmarks and of course historical returns.Investors are so busy with returns that assessing the risk of their investment mostly takes a backseat. But, of late, there is an increasing awareness among investors about using downside risk measures in selecting mutual funds. However, with interest comes confu-sion about the methods. There are umpteen number of ways in which an investor can analyse the risk of a mutual fund scheme. Here we will be talking only about the equity-oriented funds and the different ways of assessing their risk.
One of the best ways to understand a concept is to implement it and know if it can be used to select the right fund. Therefore we will take the large-cap fund category excluding funds with lower asset under management and calculate the risk param-eters of the funds to understand how to use them for fund selection. We have taken Nifty 100 as the benchmark for all the funds even though there are funds that have been benchmarked to Nifty 50, Sensex and BSE 100 TRI. Further, we have taken only those funds that have a history of at least eight years. All the calculation is done based on the weekly returns.
Beta
Beta is one of the most commonly used risk measure and it calculates the fund’s returns as against its benchmark. So, beta explains the relative riskiness of an asset compared to its benchmark and does not give the inherent risk of the asset itself. This means that if the benchmark of a fund is very volatile and if the fund is a little less volatile than its benchmark, it will have a beta of less than 1. A beta greater than 1 indicates that the fund is more volatile than the benchmark. If the beta is less than 1, the fund is less risky compared to the benchmark. So ideally a lower beta should be better for the fund as it will fell less compared to its benchmark and hence will require less appreciation to compensate for such a fall.
For example, consider Fund A with a beta of 0.95 and Fund B with a beta of 0.85, both of which have the same benchmark.
Thus, if initially the investment value is Rs 100 for both the funds and the benchmark rises by 10 per cent, the investment value of Fund A will be Rs 109.5 and the value of Fund B will be Rs 108.5. Now, if the benchmark declines by a similar percent-age, the value of Fund A will be Rs 99.09 and the value of Fund B will be Rs 99.27. Even if we reverse the sequence of returns, the fund with lower beta will have higher value at the end. The best scenario is when the beta is greater than 1 when the market is giving positive returns and lower than 1 when the market is giving negative returns. This we can name as ‘Bull Beta’ and ‘Bear Beta’, respectively. We will use the Capital Asset Pricing Model (CAPM) to get these values of the large-cap dedicated funds.
The table above shows the beta of the large-cap funds. We see that Axis Bluechip has the lowest beta while the ideal beta is of Canara Robeco Bluechip and Franklin India Bluechip that have higher Bull Beta and lower Bear Beta. Beta should not be looked at in isolation and must be used along with other risk metrics to understand riskiness of the fund. One of the most important factors is the R-squared value that shows how reliable the beta number is.
R-Squared
R-Squared aims to measure a fund’s performance explained by its benchmark performance. It varies between zero and one. So, if the R-Squared of a fund is 1 then it shows that the fund’s performance is perfectly correlated with the performance of the benchmark and explains the fund’s performance. Actively managed mutual funds can have a range of R-squared values. Mutual funds which have an R-squared of 80 or lower are less related to their benchmark. Generally, if an actively managed fund has a high R-squared value and higher beta, then it is probably closely following its index and hence performing like an index. For equity diversified funds, an R-squared value greater than 0.8 is generally accepted to mean that the underly-ing beta value is reliable and can be used for the fund. Beta and R-squared should thus be used together when examining a fund’s risk profile. They are as inseparable as risk and return. The following table shows the beta and R-squared values of large-cap dedicated funds.
The data presented above clearly shows that higher R-squared value of the fund makes the beta of the fund reliable. R-squared can be used intelligently to even select between actively and passively managed funds. For example, if an actively managed fund has a very high R-squared and beta close to 1, then it is probably better to replace it with an index fund, which can give you nearly the same performance but without paying a high expense ratio. This may help you to earn higher returns in the long run.
Standard Deviation
While beta measures the performance of the fund in compari-son to its benchmark, standard deviation of the fund shows the volatility of the fund’s returns. Higher standard deviation means higher variation in returns and vice versa. It shows the dispersion of returns from the average over a period of time. From a mutual fund perspective, it represents the volatility or riskiness of the fund. As a rule, the higher the standard deviation, the more volatile the mutual fund on a historical basis. Purely for the equity mutual fund category, large-cap funds will have lower standard deviation compared to small-cap and mid-cap funds. Therefore, if you want to have more predictable returns, you can always invest in large-cap funds with lower standard deviation.
The above table shows the annualised standard deviation of the large-cap funds. We see that Axis Bluechip has the lowest standard deviation and is one of the best in terms of annualised returns. Similarly, HDFC Top 100 with highest standard deviation has inferior returns compared to other funds with lower standard deviation.
Capture Ratio
To truly understand how your fund has been performing in different market cycles, you will have to categorise the perfor-mance according to the bull and bear periods. This approach can help you get a more in-depth reading of the fund’s perfor-mance. This comprehensive research can be achieved by looking at the ‘upside capture’ and ‘downside capture’ of these funds. An upside capture ratio of over 100 indicates that a fund has outperformed the benchmark during periods of positive returns for the benchmark. It is calculated by taking the fund’s upside capture return and dividing it by the benchmark’s upside capture return.
A downside capture ratio of less than 100 indicates that a fund has lost less than its benchmark in periods when the bench-mark has been in the red. The ratio is calculated by dividing the fund’s returns by the returns of the index during the down market and multiplying the result by 100. So, while an upside capture of over 100 per cent indicates that a fund has outper-formed the benchmark or category average during periods of positive returns, a downside capture below 100 per cent indicates that a fund has lost less than its benchmark or category average during periods that the market has been in the red. An ideal scenario is when funds have a high upside capture ratio and low downside capture ratio. The following table shows the upside and downside capture ratios along with the overall capture ratio.
The above table shows the upside, downside and overall capture ratio of the large-cap-dedicated funds. These capture ratios are calculated based on weekly returns of the funds and bench-mark. The best capture ratio is of Axis Bluechip. When the market goes up, the fund captures 90 per cent while when market goes down it only captures 82 per cent of that downfall. This is the reason the fund has remained one of the best performers in its category. This is followed by Mirae Asset Large-Cap that has a capture ratio of 1.083.
Drawdown
Drawdown is the amount by which your fund NAV declines from a peak reading to its lowest value before attaining a new peak. In more simple words, drawdown risk is the measure of how long it takes for a mutual fund or other investment to recoup its losses after it falls from a previous high. It is one of the best measures of risk you should know while assessing any investment securities, including mutual fund schemes. While what we have discussed above, such as standard deviation, beta and R-squared, serve as analytical tools that can be used to mathematically quantify and categorise certain characteris-tics of an investment risk, drawdown risk is a much more ‘real’ measure of the potential impact that a substantial loss may have on your portfolio.
The above graph shows the maximum drawdown of the large-cap dedicated funds. Clearly, Axis Bluechip has the lowest drawdown of 27 per cent compared to 34 per cent of Nifty 100.
When Less is More
When analysing funds from a risk perspective, remember that less is more. All the matrices that we discussed above are correlated. It has been witnessed that lower volatility mutual funds typically produce higher rates of return and less drawdown. According to a study, investment in the highest-ranked decile of low to average riskiness of mutual funds, reallocated quarterly, produced better returns compared to just buying and holding the funds. Moreover, more significantly, the maximum drawdown of this first decile portfolio was lower than the buy and hold portfolio. Therefore, the next time that you select a fund, remember that less risk not only means less pain but more gain also.
The above chart shows the cumulative returns of the large-cap funds. It clearly shows the best return is provided by Mirae Asset Large Cap Fund followed by Axis Bluechip fund. It should not come to your surprise is that these two funds also happen to be best in containing the risk.