By now, you should guess that since the beta is high, the fund gets penalised for its erratic behaviour. To put this in context, think about it this way, Ferrari is faster compared to a BMW, this comparison is like the beta. It gives you a sense of how volatile a fund’s performance has been in the past so that you can use it as an indicator of how volatile it might be going forward. When a fund has a high SD, it indicates that the past performance has been fairly volatile, and basically indicates a bumpier or more volatile ride compared to another fund with a lower SD.
All along with this module, I’ve stressed the importance of giving your MF investments time, and this is the reason why I’ve stressed on it. The standard variation of less than one indicates a low variation from the mean, whereas greater than one is indicative of a high degree of variation. However, it is to be remembered that it is not good or bad, but an indicator of the data spread.
The number tells us that the fund generates 0.29 units of return (over and above the risk-free return) for every unit of risk undertaken. Naturally, by this measure, the higher the Sharpe ratio, the better it is as we all want higher returns for every unit of risk undertaken. The funds under consideration are the Axis Small-cap fund and Axis long term equity. Lastly, if the beta of the fund is higher than 1, it implies that the fund is risker compared to its benchmark.
I’ve captured this from Value research; these attributes belong to Tata Multicap fund. Furthermore, while you will solely arrive at a number using this specific deviation definition for risk calculation, there is always a problem as to whether it is low or high. Sannihitha Ponaka is an MBA graduate from Symbiosis and has more than 5 years of experience in the financial sector. Following her dreams in the field of finance, she leverages writing to communicate the importance of investing.
A critical ratio frequently used by fund managers the standard deviation can greatly help investors. Let us understand the standard deviation meaning to help you assess risk better. By now, you must have realized that volatility plays an important role in what is standard deviation in mutual fund measuring mutual funds performance. Beta is a measure of volatility; it tells us how risky the fund is when compared to its benchmark.
Standard deviation from the mean represents the same thing whether you are looking at gross domestic product (GDP), crop yields, or the height of various breeds of dogs. Moreover, it is always calculated in the same units as the data set. You don’t have to interpret an additional unit of measurement resulting from the formula. Well, think about it, the fund has managed to generate a 10% return compared to the Index’s 7% while managing to stay significantly less volatile (remember beta is is just 0.75). Hence we are rewarding the fund for its good behaviour or less volatile behaviour. The standard deviation of 9.40 indicates that the fund’s returns would go up or down by this value from its mean.
The right mutual funds for your long-term goals with inflation-beating growth plus risk management. The importance of standard deviation as an accepted risk assessment parameter has now been established. It is vital to bear in mind that despite all the advantages of standard deviation using it alone as a risk assessment tool can have its limitations. There may be a fund with a low standard deviation that may lose money due to poor portfolio composition although such cases are rare.
It is important to note that standard deviation can only show the dispersion of annual returns for a mutual fund, which does not necessarily imply future consistency with this measurement. Economic factors such as interest rate changes can always affect the performance of a mutual fund. The Sharpe Ratio evaluates risk-adjusted performance, or how well a fund performs relative to its volatility.
Additionally, a fund’s high standard deviation does not necessarily indicate that it is extremely volatile, even if it belongs to a sector or category with a high standard deviation. The fund’s volatility is comparable to other investments in its category. Therefore, comparing funds that fall under the same category is crucial. While investing in a mutual fund we often look at returns as a parameter for assessment. Along with returns a fair assessment of risk can help you in making a prudent choice. One such way of assessing risks and volatility can be using a statistical tool called standard deviation.
It is a representation of the relative risk of the fund and not the inherent risk of investing in that particular fund. Standard deviation is a good measure of market volatility and the response of the mutual fund to this volatility. While there is no such thing as a good or bad standard deviation, funds with a low standard deviation in the range of 1- 10, may be considered less prone to volatility.
In finance, standard deviation refers to a statistical measure representing the volatility or risk in a market instrument such as stocks, mutual funds etc. If the beta of a mutual fund is less than 1, then the fund is perceived as less risky compared to its benchmark. For example, the Tata Multicap fund has a beta of 0.95, hence the fund is slightly less risky compared to its benchmark.
Standard deviation is a measure that can measure the riskiness of a mutual fund but not the only one that you should rely on before making an investment decision. You should use standard deviation along with other quantitative and qualitative measures for evaluating a mutual fund. An equity category – mid cap fund or a sectoral fund or a multi cap fund usually has a higher standard deviation in comparison with large-cap or balanced funds. While mean and standard deviation measures the extent of variation, standard variation is considered more effective when the data points are normally distributed. Mean deviation can be a better measure when the level of dispersion is higher. Mean deviation tells us how far, on average, all values are from the middle.
World-class wealth management using science, data and technology, leveraged by our experience, and human touch. Thus, SD indicates how far the returns are dispersed on either side of the mean.
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