A mutual fund is a diversified pool of investment in securities and debt instruments. There are various metrics to evaluate the performance of mutual funds. All these metrics have been discussed in detail below.
How do you evaluate a Mutual Fund?
One must consider the following factors while evaluating a fund –
- Investment strategy – i.e. where the money invested is getting channelised into and if this will help the investor meet his or her financial goal. For example, investment in funds that track debt markets is relatively safer and suitable for investors with low risk appetites.
- Fees charged – one must look into the expense ratio and the load of the mutual fund prior to investing.
- Holdings – one must look into the holdings that the fund manager is investing in – is it skewed towards one particular sector like technology or is it well balanced etc.
- Performance of the fund with respect to the benchmark usually for a period of 5-10 years will offer a fairly accurate picture of the past trends.
- Performance with respect to its competitors.
- Management of the fund – i.e. whether it is actively or passively managed.
Metrics Used to Evaluate Mutual Funds
It’s used to measure variation from an arithmetic mean. Generally, standard deviation in finance is a statistical measure that represents the volatility or risk in a market instrument such as stocks, mutual funds etc. It is an accurate measure of how much deviation occurs from the historical mean.
It is used to measure the dispersion of the actual return from the mutual fund’s expected return.
It is a widely used measure due to its consistency. It is important to note that the higher the standard deviation, the greater the fluctuation is. It is calculated as the square root of variance or –
Standard Deviation = [1/n * (xi – x)2]1/2
xi = each datapoint
x = mean
n = number of data points or time periods
However, it is not devoid of limitations. Some of them are as follows –
- It cannot be applied when a portfolio has multiple funds within it.
- It does not indicate the mutual fund performance against its benchmark.
- It does not show or proof or accurately predict the future consistency of the investment.
- The accuracy of the data rests in the size of the data set, i.e. the larger the data set, the more accurate the standard deviation is.
It’s used to gauge the performance of the asset manager who is tasked with guiding a fund, the Alpha ratio, indicating the probability of profits to the investors in a particular fund. The alpha is also called as the returns generated over and above the benchmark returns.
Alpha is used to estimate the future performance of the fund. Alpha helps overcome the limitations of the standard deviation metric.
It is a risk – adjusted metric to gauge the performance of the mutual fund and is calculated as
(End Price + Distribution Per Share – Start Price)
It can also be calculated with the help of the formula:
Alpha = (MF Return – risk free return) – (Benchmark return – risk free return) * Beta
In order to arrive at the Alpha, one must compare the return on a specific fund against a benchmark index. If the alpha ratio is zero, then it implies that the fund has performed in line with the benchmark.. Alpha in positive figures means that the mutual fund has performed better than its benchmark.
Investors generally choose mutual funds that have an alpha ratio of 1.5, which is considered to be an ideal score.
An instrument of the financial market used to quantify the performance of the mutual fund, Beta ratio, is a historical measure used to evaluate the investment portfolio’s returns over a period of time. It is usually used to quantify the mutual fund’s response to market volatility and is considered to be a representation of the relative risk of the fund.
It can help the investor decide whether a specific fund must be included in the investment portfolio or not as it will help the investor identify the cause for good or poor performance of the fund.
It is calculated as –
- Beta ratio = Covariance/Variance of market’s returns.
- Covariance = how two different stocks respond to each other in varying market conditions. A positive covariance indicates that they move in compliance with each other and a negative covariance indicates that they move in opposite directions.
- Variance = is the price deviation of the fund from its average or mean.
Beta ratio starts with a baseline of 1. If the value is one, then the fund’s response is equivalent to the markets or the shift in the price of the mutual fund is the same as the benchmark movements. A beta value that exceeds one shows that the fund is more responsive than the benchmark movement.
Suppose the Beta is 1.2, then it indicates that if the market/benchmark moves by 10%, the fund could move up by 12%. Same with the downside movement as well, if the benchmark moves down 10% then the fund value could go down by 12%. The converse is the case when the ratio is less than 1.
The sharpe ratio refers to the average return that you can expect based on the risk free rate per unit of the total risk. You can use the sharpe ratio to understand the mutual fund’s past or future performance, which can help you decide whether or not to invest in it.
Needless to point out, the higher the sharpe ratio, the better the mutual fund is.
The sharpe ratio is mathematically calculated as follows –
- Sharpe Ratio= Rp – Rf /σp
- Rp =return of portfolio
- Rf =risk-free rate
- σp =standard deviation of the portfolio’s excess return
It is used to compare changes in the overall risk return when new assets or an asset class itself is added to the portfolio.
Sharpe Ratios above one are generally considered good and a ratio of one might be considered inadequate. It can be used to evaluate past performance as well as future performance too.
There are certain limitations of sharpe ratio. They are as follows –
- A negative sharpe ratio fails to convey any useful meaning because it indicates that the risk-free rate is more than what the portfolio can return as a yield. For instance, if Fund A has a negative sharpe ratio (ie, the ratio depicted is less than zero), it means that it has underperformed the benchmark during that period. However, it does not indicate whether its performance in the future will also be underwhelming for investors.
- Though a higher sharpe ratio implies better returns, these are only worth it if the higher returns are not a product of excess additional risk to the investor.
- It comes with an assumption that risk equals volatility which is a very narrow way of looking at all investments.
- It uses standard deviation as its denominator with an assumption that the returns are distributed normally, which need not necessarily be the case.
- It can be manipulated by portfolio managers easily as they can increase the measurement period to show a more favourable ratio.
A statistical measurement used to indicate the proportion of the variance for a dependent variable from the independent variable in a regression model, R Squared, is an important metric for mutual funds as it can show you a range of expected performance. Based on the range it shows you, you can then decide whether or not to invest in the fund you’re evaluating.
Popularly known as a coefficient of determination, the R Squared is calculated like this –
R2 =1− (Unexplained Variation/ Total Variation)
Using these mutual fund metrics can help you understand where you should allocate your funds, thereby lowering the risk of losing your hard earned money. After all, investments are all about growing your wealth, not decreasing it!
- What are mutual fund metrics used for?
Mutual fund metrics help you evaluate how a mutual fund is performing. This can help you make an informed decision regarding your investments.
- What does 100% in R Squared mean?
It means that the securities are performing in tandem with the benchmark they track. This hints at the fact that the fund is performing well.
- Are mutual fund metrics reliable?
Yes, however, you should not solely base your investment on these metrics. You must also analyse your risk appetite before choosing a fund.