5 Ways To Measure Mutual Fund Risk

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There are flashy numbers of dividend pay outs in percentages declared by fund houses on a regular basis in newspapers, periodicals, websites, etc. These numbers attract investor eyeballs towards their schemes. Now, SEBI has stepped in and has asked fund houses to disclose their pay outs in rupee terms. This shows that investors are trying to get a clearer picture on their investment returns through dividends. However, investing by considering only historical returns and dividends in a mutual fund scheme is risky. Investors need to evaluate the risk involved in mutual fund schemes before investing and review their investments, say, at least once a year.

Investors may perform a small 5-step exercise to evaluate riskiness of particular mutual fund scheme, as described below

We will take a hypothetical example of ABC-Equity (G) scheme to compute its riskiness in our Paanch Ka Dum (Power of 5) concept

1) Alpha

Alpha basically is the difference between the returns an investor expects from a fund, given its beta, and the return it actually produces.

Computation- Alpha equals (Fund return-Risk free return) – (Funds beta) (Benchmark return- risk free return).

Example-1

Fund return (Fund performance in last one year) 75%

Risk free return 8%

Benchmark return (Sensex performance in last one year) 41%

Beta 0.69

By computing with above formula we will get alpha as 0.44 for this fund.

A positive alpha means the fund has outperformed its benchmark index. Whereas, a negative alpha indicates an underperformance of the fund. The more positive an alpha the healthier for investors.

Here, the fund has underperformed since an alpha we computed is less than beta. It means the fund has produced less returns considering the risks fund is taking while comparing it with actual return to the one predicted by beta.

Note- The ideal time period for analysing alpha and beta value is one year returns from their funds.

2) Beta

Beta is a measure of the volatility of a particular fund in comparison to the market as a whole, that is, the extent to which the funds return is impacted by market factors. Beta is calculated using a statistical tool called regression analysis.

By definition, the market benchmark index of Sensex and Nifty has a beta of 1.0.

It may be challenging for investors to compute it for each mutual fund scheme. However, one need not worry. Important statistical measures for various mutual fund schemes are easily available on financial websites like InvestmentYogi where mutual funds performance is tracked and analysed regularly.

Let us consider 3 possible scenarios in interpreting beta numbers

Sensex is assumed as benchmark index.

1.A beta of 1.0 indicates that the fund NAV will move in same direction as that of benchmark index. The fund will move up and down in tandem with the movement of the markets (as indicated by the benchmark)

2.A beta of less than 1.0 indicates that the fund NAV will be less volatile than the benchmark index.

3.A beta of more than 1.0 indicates that the investment will be more volatile than the benchmark index. It is an aggressive fund that will move up more than the benchmark, but the fall will also be steeper.

For example, if the beta of ABC-Equity (G) is 1.4 then it is considered as 40 percent more volatile than the benchmark index (beta of benchmark index being 1).

Similarly, in example-1, as we have considered beta of ABC-Equity (G) fund as 0.69 this means the mutual fund scheme will be less volatile than its benchmark index.

Note- Conservative investors should focus on mutual funds schemes with low beta. Aggressive investors can opt to invest in mutual fund schemes which have higher beta value for higher returns taking more risk.

3) R-Squared

As discussed above, beta is dependent on correlation of a mutual fund scheme to its benchmark index. So, while considering the beta of any fund, an investor also needs to consider another statistic concept called R-squared that measures the correlation between beta and its benchmark index. The beta of a fund has to be seen in conjunction with the R-squared for better understanding the risk of the fund.

R-squared values range between 0 and 1, where 0 represents no correlation and 1 represents full correlation. If a funds beta has an R-squared value that is between 0.75 and 1, the beta of that fund should be trusted. On the other hand, an R-squared value that is less than 0.75 than it indicates the beta is not particularly useful because the fund is being compared against an inappropriate benchmark index. This fund will not give returns similar to their benchmark index. The lower the R-squared the less reliable is the beta, and vice versa.

The R-squared of an index fund, investing in same securities and in the same weightage as the index, will be one.

Note- Beta and R-squared are calculated based on the historical data. They give an adequate estimate of risks to be evaluated by investors before investing.

4) Standard Deviation (SD)

The total risk (market risk, security-specific risk and portfolio risk) of a mutual fund is measured by Standard Deviation (SD). In mutual funds, the standard deviation tells us how much the return on a fund is deviating from the expected returns based on its historical performance. In other words can be said it evaluates the volatility of the fund.

The standard deviation of a fund measures this risk by measuring the degree to which the fund fluctuates in relation to its average return of a fund over a period of time.

In other words, it is a measure of the consistency of a mutual funds returns. A higher SD number indicates that the net asset value (NAV) of the mutual fund is more volatile and, it is riskier than a fund with a lower SD.

Note- For SD to be an effective tool, investors will need to use it in comparison with peer group mutual funds. For example, a large-cap mutual fund is to be compared with a large-cap mutual fund with the same investment objective(s).

5) Sharpe Ratio

Sharpe ratio (SR) is another important measure that evaluates the return that a fund has generated relative to the risk taken. Risk here is measured by SD. It is used for funds that have low correlation with benchmark index. This ratio helps an investor to know whether it is a safe bet to invest in this fund by taking the quantum of risk.

The higher the Sharpe ratio (SR), the better a funds return relative to the amount of risk taken. In other words, a mutual fund with a higher SR is better because it implies that it has generated higher returns for every unit of risk that was taken. On the contrary, a negative Sharpe ratio indicates that a risk-free asset would perform better than the fund being analyzed.

It tries to find out the excess return generated by a mutual fund over and above a risk-free rate of return such as an RBI bond or a post-office savings scheme, etc.

Lets say the Sharpe ratio equals 0.957 for a fund. As discussed above, the higher this ratio, the better a funds return relative to the amount of risk taken. Here, this fund could be a risky investment option for their investors since ratio is just near to 1 (approx.).

Quick View

Mutual Fund Evaluation Criteria–

Consistent Performer- Low SD- High SR- Higher ranked fund

Volatile Performer- High SD- Low SR– Lower ranked fund

Mutual Fund Evaluation Criteria-

Consistent Performer- Low SD- High SR- Higher ranked fund

Volatile Performer- High SD- Low SR- Lower ranked fund

Note- Comparison should be made with peer group for accurate evaluation.

Conclusion

This Paanch Ka Dum concept we just discussed to evaluate a mutual funds risk will enable an investor to take a wise decision on his mutual fund investments. An investor should not blindly invest by considering only past returns mentioned, but needs to do some research of the fund schemes and reviewing their performance at regular intervals.

Source: Sify.com

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