Risk can be defined as the unfortunate possibility of losing a part of or all of the original investment. Risk can arise from several sources such as changes in the interest and currency rates, inflation, economy, industry, political situation and dozens of other internal and external factors.
Investors aim at maximising their returns and, with this mindset, tend to ignore the disclaimer which mutual funds highlight: “Mutual funds are subject to market risk”. This is a behavioural anomaly that indicates that investors do not understand the risk-return relationship.
Every investor has his/her own risk profile, and it is essential to have a clear idea about their personal risk profile as we all know that risk is measurable, and investors should make use of risk statistics while analysing and selecting mutual funds.
In this article, we will look at risk measures used in analysing equity and debt mutual funds portfolios.
Beta is the most commonly used risk measure that calculates the volatility or systematic risk of a security or Mutual Fund’s returns as against its benchmark. In other words, Beta shows the sensitivity of a mutual fund portfolio towards the market.
Beta is always benchmarked to 1. For instance, if the fund’s beta is 0.85, it is less sensitive to the benchmark compared to 1.10 which is more sensitive. In other words, in the former scenario, with every rise in the market by 1, the fund will rise by 0.85, and if there is a fall, the fund will fall by 0.85.
Investors can use this information to align the Mutual Fund portfolio according to their risk profile. For instance, a conservative investor might focus on portfolios with a low beta.
Beta is a relative measure that does not provide the inherent risk associated with an asset. Hence it should not be looked at in isolation while selecting a mutual fund. However, it is a useful statistical measure for diversification that can be used along with the other risk controls.
Alpha is not purely a risk measure. It is often used together with Beta.
Alpha indicates how better a mutual fund has performed against its set benchmark. For instance, let’s assume that the Nifty 50 index delivered 11% returns in the last year and the fund benchmarked against Nifty 50 delivered a return of 13%. In this case, the Alpha of the fund is +2%. And if the fund underperformed and achieved 8% returns, the Alpha is (2)%.
Therefore, funds can either have a positive or a negative Alpha, and this depends on how well the fund manager runs the fund.
On the other hand, Index funds do not produce Alpha. A zero Alpha is not necessarily bad, especially in the scenarios when Large Cap Equity Funds are facing a tough time to beat the Nifty 50 index.
A key point to remember with regards to both Beta and Alpha is, both of these measures rely on historical data and change from time to time.
This is a statistical measure that aims to measure a fund’s correlation to its benchmark performance on a scale of 100. Therefore, if the R-Squared of a fund is 100, it depicts that the fund’s performance is perfectly correlated with the performance of the fund’s benchmark.
The R-Squared of index funds is close to 100. In comparison, actively managed Mutual Funds may have a range of R-squared values. Funds having an R-Squared of 80 or below tend to not perform like a typical index.
If an actively managed mutual fund has a high R-squared value, it is probably structured like an index and is performing like one.
R-squared can be very useful while analysing and selecting funds. To explain with an example, if an actively managed fund has a very high R-squared it highlights that it is probably better to replace the same with an Index Fund, which gives nearly the same performance without having to pay a high expense ratio.
Sharpe Ratio measures the risk-adjusted performance of a fund. The measure is calculated by deducting the risk-free rate of return from the fund’s returns and dividing the outcome by the standard deviation of the fund.
The Sharpe Ratio indicates whether fund returns are because of the wise investment decisions taken and implemented by the fund manager or result of excess risk.
Sortino Ratio uses the Mutual fund’s downside standard deviation for calculations.
It is similar to the Sharpe Ratio and subtracts the risk-free returns from the returns of the fund. But instead of dividing the outcome by the standard deviation of the fund, it divides the difference with the downside deviation.
High alpha, Sharpe ratio and Sortino ratio depicts better potential performance for a mutual fund. Whereas, low beta and standard deviation reflect lower volatility of the fund. A higher R-Squared indicated a better correlation with the benchmark.
The above-mentioned risk assessment tool helps to evaluate all checks and balances before selecting funds instead of solely basing the decision on the historical performance.