Risk Classification Methodology Standard Deviation for Mutual Funds and ETFs

Firstly, standard deviation measures the dispersion of data points around the mean, indicating the degree of variability within a dataset. A smaller standard deviation suggests that the data points are clustered closely to the mean, indicating lower volatility, while a larger standard deviation indicates greater variability and risk. In portfolio construction, standard deviation aids in identifying the right balance between risk and return. For example, a portfolio heavily weighted in high-standard deviation assets may offer higher returns but also exposes investors to significant volatility.

When considering a fund’s volatility, an investor may find it difficult to decide which fund will provide the optimal risk-reward combination. Many websites provide various volatility measures for mutual funds free of charge; however, it can be hard to know not only what the figures mean but also how to analyze them. If the beta of a mutual fund is less than 1, then the fund is perceived as less risky compared to its benchmark.

Alternatively, you can estimate with 95% certainty that annual returns do not exceed the range created within two standard deviations of the mean. If the returns for a stock or portfolio follow a normal distribution, then approximately 68 percent of the time they will fall within one standard deviation of the mean return, and 95 percent of the time within two standard deviations. For example, if the mean annual return is 10 percent and the standard deviation is 2 percent, you would expect the return to be between 8 and 12 percent about 68 percent of the time, and between 6 and 14 percent about 95 percent of the time.

1. Past performance of any scheme of the Mutual fund do not indicate the future performance of the Schemes of the Mutual Fund.
2. In portfolio construction, standard deviation aids in identifying the right balance between risk and return.
3. You don’t have to interpret an additional unit of measurement resulting from the formula.
4. For Alpha vs. the Standard Index, Morningstar performs its calculations using the S&P 500 as the benchmark index for equity funds and the Barclays Aggregate as the benchmark index for bond funds.
5. The term may sound complex and perhaps beyond the comprehension of anyone other than a math or finance major, but using standard deviation with mutual funds can be simple and useful.
6. If the beta was 0.6 or 0.65, the fund is less risk or less volatile compared to its benchmark.

Calculating the Beta with the help of an example:-

A normal standard deviation for a portfolio varies based on the type of investments. There’s no exact number, so it’s important to compare it with similar portfolios to see if it’s normal. Up to this point, we have learned how to examine figures what is standard deviation in mutual fund measuring risk posed by volatility, but how do we measure the extra return rewarded to you for taking on the risk posed by factors other than market volatility? Enter alpha, which measures how much if any of this extra risk helped the fund outperform its corresponding benchmark. Using beta, alpha’s computation compares the fund’s performance to that of the benchmark’s risk-adjusted returns and establishes if the fund outperformed the market, given the same amount of risk.

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An assessment of the variations in a fund’s monthly returns, with an emphasis on downside variations, in comparison to similar funds. In each Morningstar Category, the 10% of funds with the lowest measured risk are described as Low Risk, the next 22.5% Below Average, the middle 35% Average, the next 22.5% Above Average, and the top 10% High. Morningstar Risk is measured for up to three time periods (three-, five-, and 10-years). These separate measures are then weighted and averaged to produce an overall measure for the fund. Funds with less than three years of performance history are not rated. While standard deviation determines the volatility of a fund according to the disparity of its returns over a period of time, beta, another useful statistical measure, compares the volatility (or risk) of a fund to its index or benchmark.

According to the modern portfolio theory, funds lying on the curve are yielding the maximum return possible, given the amount of volatility. Though the standard deviation is an important measurement for mutual fund-related investment decisions, still like every other metric, standard deviation also has certain limitations. To conclude, alpha is the excess return of the fund over above the benchmark returns. The fund is rewarded if the returns are generated by keeping a low-risk profile and penalized for being volatile. Alpha is defined as the excess return of the mutual fund over the benchmark return, on a risk-adjusted basis.

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If the standard deviation is high, the returns are more spread out and risky. This way, investors can know if they’re taking a lot of risk or playing it safe. This gives you the standard deviation, showing how much the returns vary from the average.

1. In this case, Stock A is considered less volatile than the market as its beta of 0.611 indicates that the stock experiences 39% less volatility than the Index ABC.
2. This is what I mean by ‘relative risk’; it gives us a perspective of how risky the fund is compared to its benchmark.
3. The difference in total return represents the fund’s excess return beyond that of the 90-day Treasury bill, a risk-free investment.
4. On the other hand, an R-squared value close to 0 indicates the beta is not particularly useful because the fund is being compared against an inappropriate benchmark.
5. Based on data over the past 10 years, the correlation between Stock A and Index ABC is 0.88.

First, we calculate the mean (average) annual return of the fund over these 5 years. In this case, Stock A is considered less volatile than the market as its beta of 0.611 indicates that the stock experiences 39% less volatility than the Index ABC. In this case, Stock X is considered more volatile than the market as its beta of 1.69 indicates that the stock experiences 69% more volatility than the Index XYZ.

The risk-free return is the maximum return you can generate without taking any risk. By risk I mean – market risk, credit risk, interest rate risk, and unsystematic risk. If the beta was 0.6 or 0.65, the fund is less risk or less volatile compared to its benchmark.

If the benchmark falls by 1%, the fund is expected to fall by 1.2%. Another potential drawback of relying on standard deviation is that it assumes a bell-shaped distribution of data values. This means the equation indicates that the same probability exists for achieving values above the mean or below the mean. Many portfolios do not display this tendency, and hedge funds especially tend to be skewed in one direction or another. At the center is the exponential moving average (EMA), which reflects the average price of the security over an established time frame. To either side of this line are bands set one to three standard deviations away from the mean.

First, the average monthly return of the 90-day Treasury bill (over a 36-month period) is subtracted from the fund’s average monthly return. The difference in total return represents the fund’s excess return beyond that of the 90-day Treasury bill, a risk-free investment. An arithmetic annualized excess return is then calculated by multiplying this monthly return by 12. To show a relationship between excess return and risk, this number is then divided by the standard deviation of the fund’s annualized excess returns.