Get To Know How to Use Statistical Analysis With Mutual Funds

Jan 10, 2024 By Triston Martin

To assess mutual funds like an expert, fortunately, you do not need to have a genius-level understanding of mathematics. It has already been determined how much time was spent on each of the quantitative and statistical aspects of the project.

Therefore, the most important information or skill you need to have to locate and purchase the finest mutual funds is understanding how to use these measurements and where to locate them. The term "statistical analysis of mutual funds" refers to exactly what it sounds like.

Digging into the numbers behind a fund requires learning more about its past performance and getting a feel for how it could perform in the future. Although there is no promise of future results, investment is not about guarantees; rather, it is about accepting well-considered risks.

Use of Statistical Tools for Mutual Fund Analysis

A significant number of investors make both short-term and long-term investments through mutual funds. It has been observed that, on average, the long-term return on investment provided by mutual funds is superior to that provided by various fixed-rate investments such as provident funds.

However, there is a greater degree of risk associated with mutual funds. Therefore, an investor must assess the dangers linked with mutual funds. Five statistical approaches may be used to examine the risk of investing in mutual funds. In this essay, we will go over these five different mutual fund analysis tools and discuss them.


Alpha is an essential instrument to quantify the return on investment risk-adjusted for mutual funds. It is a measurement of the performance of a mutual fund adjusted for the risk it takes. The alpha of an investment refers to the amount of additional return it generates compared to the return of a benchmark index.

A positive Alpha of 1.0, for instance, indicates that the fund has fared better than the benchmark index it was compared to by 1%. Similarly, an Alpha that is negative 2.0 suggests under-performance that is 2% worse. Therefore, the alpha is seen to be in a better position the more positive it is.


The volatility or systematic risk of a securities or portfolio relative to the overall market is measured by beta, often known as the beta coefficient. Beta is a statistic that may be determined by regression analysis relating an investment's return to changes in the market. The market's beta is 1.0 by definition.

Valuations of individual securities and portfolios are compared to the market by looking at how they differ from them. If an investment's beta equals the market, its price increases exponentially. An investment's market risk is predicted to be lower if its beta is smaller than 1.

Standard Deviation

The concept of standard deviation is widely used in the field of statistics. It is common knowledge among those studying mathematics and statistics. You may use this instrument to examine the volatility of a selected mutual fund.

It is a statistical measure of how far the data is from the center. The greater the dispersion of the data, the greater will be the deviation from the norm. Regarding mutual funds, the Standard Deviation informs investors of how much the actual return varies from the projected return based on the fund's past performance.

Sharpe Ratio

Economist William Sharpe, the Nobel Prize in Economics winner, created the Sharpe ratio. The ratio captures how well results have been achieved, considering the amount of risk involved. Investment risk premiums are determined by dividing the rate of return for the investment by its standard deviation minus the risk-free rate of return.

The Sharpe ratio shows the extent to which an investment's gains may be attributed to the manager's risk-taking or underlying performance. A higher Sharpe ratio indicates superior risk-adjusted performance for a certain fund.


The R-squared statistic determines how much variation in a fund's portfolio or securities can be attributed to changes in the corresponding benchmark index. The U.S. Treasury Bill is a standard against which other fixed-income instruments and bond funds are measured. All other stock indexes and equity mutual funds are measured against the S&P 500.

The R-squared scale covers the numbers 0–100. Morningstar states that a mutual fund's performance record with an R-squared score between 85 and 100 is highly associated with the index. In most cases, funds with a rating of 70 or lower underperform their respective indexes.

Maximum Return Monthly Performance Analysis Of Mutual Funds

As is usually the case, the performance of mutual funds is the primary focus. Several managers stand out when measured against a benchmark and their colleagues across rolling periods of one, three, and five years.

What is not typically learned from this type of study is whether the manager's performance was consistent throughout the time being evaluated or whether the performance was determined by a few outlier months. Additionally, you won't know if the manager's success was due to their exposure to a specific industry or geographical area.

The easiest approach to do such a study is to compile a monthly performance table for both the fund and the benchmark and compare their relative over/underperformance. It will allow you to spot outlier months and identify trends. Months with out-of-the-ordinary high or low performance, according to the benchmark, may also be examined.


It's common for investors to be too concerned with returns and to disregard the risks associated with their holdings. The risk-reward ratio can be tempered by the five risk metrics we've covered. The good news for investors is that these indicators are computed automatically and made available on various financial websites.

They are also integrated into many investment research reports. While these metrics are helpful, you should not let volatility risk be the only consideration you think about when picking stocks, bonds, or mutual funds to invest in.

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