Case Study: Mutual Funds Essay Example
- Category:Business
- Document type:Assignment
- Level:Undergraduate
- Page:5
- Words:3210
Table of Content
Statistics for Decision Making
Case Study: Mutual Funds
Table of Contents
3Statistics for Decision-Making: Analysis report of case study-mutual funds
31.0 Introduction
31.1 Objectives
32.0 Business problem
53.0 Methodology
64.0 Analysis and Discussion
6Data analysis and interpretation
64.1 Shares categories Analysis
64.2 Count of shares category
74.3 Performance of Assets based on growth Objective
84.4 Best quarter performance and year-interval performance
94.5 Expense ratio for shares
104.6 Assets recorded by the shares categories
124.7 Shares categories performance in the year 2013
134.8 Mutual funds and fees payment
144.9 Performance during the worst quarter
154.10 Statistical tests
165.0 Ratio Analysis
165.1 Sharpe Ratio
175.2 Jensen Ratio
176.0 General Conclusion
18Implications
197.0 Bibliography
Statistics for Decision-Making: Analysis report of case study-mutual funds
1.0 Introduction
Mutual fund is defined as the a type of trust by a sponsor where trustees raise money using the sale of units to the public, using various schemes, in order to invest in securities according to the regulations (Gadhi & Perumal, 2016). Basically, a mutual fund is a type of collective investment that is professionally-managed to pool money from several investors and have the money invested in stocks, bonds, and other securities. The portfolio manager has the role of trading the funds’ fundamental securities, realizing capital profits/losses, as well as collecting the divided or interest income (Joshi, 2013). The individual investors are then given investment earnings. The Net Asset Value (NAV), which is the value of the mutual fund share, is computed every day basing on the total value of the fund, divided by the shares number (Gadhi & Perumal, 2016). This report presents a case study where the investment analyst for clients is required to make an analysis for clients who decide to buy mutual funds for their retirement account. After the analysis, the investment analyst is required to provide guidelines for the clients to make reasonable decisions among the available mutual funds for their retirement account.
1.1 Objectives
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To provide general guidelines for clients to select a fund based on different characteristics
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To guide client to make a reasonable choice among the many funds available
2.0 Business problem
In the current business world, there are numerous investment choices and mutual fund is booming sector that provides an opportunity for investors to generate income and returns (Joshi, 2013). Mutual funds provide a portfolio of securities and therefore it is a common choice especially, for investors thinking of retirement. The business problem in the case study involves making a decision to buy mutual funds for investors’ retirement account. Accordingly, the investment analyst is required to make analysis and reach the most suitable decision for clients purchasing mutual funds for their retirement account. There are many available funds and hence the investment analyst ought to make a reasonable choice among the many funds available. There is a sample of 121 mutual funds and therefore the investment analyst is required to use various variables to perform analysis in order to be able to make the best investment decision for the client. The variables include:
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Category – type of shares comprising the mutual fund – small cap, mid cap, large cap
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Objective – objective of shares comprising the mutual fund–growth or value
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Assets – in millions of dollars
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Fees – sales charges (no or yes)
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Expense ratio – ratio of expenses to net assets in percentage 2013
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Return – twelve-month return in 2013
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4-year return – annualized return 2009 – 2013
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3-year return – annualized return 2011 – 2013
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Risk– risk-of-loss factor of the mutual fund classified as low, average or high
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Best Quarter
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Worst Quarter
The performance variables (Expense ratio, Three year return, Five year Return and return 2013) will be analyzed basing on funds characteristics (Category, Objectives, Risk and Fees).
3.0 Methodology
SPSS (Statistical Package for Social Scientists) software was used for data entry and statistical analysis. Descriptive statistics were used to provide an overview of data that and infer guidelines for clients to select a fund based on different characteristics and make a reasonable choice among the many available funds. Pearson’s correlation test was used to measure the strength of the association and relationship between the variables. Regression analysis was used to determine overall fit and relative contribution of variables and all predictors. Performance variables (Expense ratio, Three year return, Five year Return and return 2013) are analyzed based on funds characteristics (Category, Objectives, Risk and Fees).Data is presented using tables and graphs.
4.0 Analysis and Discussion
Data analysis and interpretation
4.1 Shares categories Analysis
Data was collected to understand share categories and their respective performance. Analyses are conducted based on frequencies and other descriptive statistics.
4.2 Count of shares category
From the category analysis of descriptive statistics, small cap category recorded the highest number of shares (60 in total) followed closely by the large cap shares category whichtotaled to 42. The mid cap category comprised of the least shares which was 19 in total. This shows that more mutual funds preferred small cap than other shares types. The chart below shows the three categories of shares:
Figure 1: Count of shares Categories
4.3 Performance of Assets based on growth Objective
The table below illustrates data about Performance of Assets based on their growth Objective
Table 1: Performance of Assets based on their growth Objective
Category |
Objective Value |
Grand Total |
|
large cap |
127684.9 |
199481.3 |
|
small cap |
|||
Grand Total |
153384.9 |
132905.9 |
286290.8 |
As shown in the table above, the total sum of assets of large cap share category whose objective was growth (127684.9) was higher than that of the large share category whose objective was value (71796.4). In contrast, the total sum of assets of large cap share category whose objective was growth (8026.3) was lower than that of small cap share category whose objective was value (53086.5).
The mid cap shares category on the other hand recorded similar results as the large cap share category with those whose objective was growth recording a sum of assets of 17673.7 which was higher than 8023 that was recorded by sum of assets of the mid cap shares category whose objective was value. This shows that for the small cap mutual fund type value is the best objective to drive the business as compared to growth. On the other hand, large cap mutual fund category’s and mid cap mutual funds category’s driving objective for improved performance is growth.
4.4 Best quarter performance and year-interval performance
The survey wanted to find out the best quarter performance as well as year interval performance and its results were recorded. The results were as displayed in the table below.
Category |
||
large cap |
Sum of Best Quarter |
|
Sum of 3-Year-Return |
||
Sum of 5-Year-Return |
||
Sum of Best Quarter |
||
Sum of 3-Year-Return |
||
Sum of 5-Year-Return |
||
small cap |
Sum of Best Quarter |
|
Sum of 3-Year-Return |
||
Sum of 5-Year-Return |
||
Total Sum of Best Quarter |
||
Total Sum of 3-Year-Return |
||
Total Sum of 5-Year-Return |
The small cap shares category recorded the highest sum of best quarter return whose value was 1915.5 followed closely by large cap shares category (1001.9). Mid cap shares category recorded the least return during its best quarter (580.6) compared to the large cap shares category and the small cap shares category. All the three categories recorded lowest returns after 5 years with small cap shares category recording 763, mid cap shares category 118 while large cap recording slightly lower than mid cap (56.4).
Moreover, the small cap shares category recorded more returns in their 3rd year (941.5) than the one they recorded during the 5th year (763). The same results were displayed by the large cap shares category that recorded 298.1 in their 3rd year and 56.4 in their 5th year. Similarly, mid cap share category displayed the same trend of results recording 285.3 in their 3rd year and 118 in their 5th year. The total sum of best quarters by all shares categories was 3498 while the total sum of the third year return by all the three shares categories was 1524.9 and that of the total sum of 5- year return was 937.4.
The results in this section imply that returns on shares invested reduced as time increased whose implication was a reduction the capital investments.
4.5 Expense ratio for shares
The expense ratio for shares is shown in the table below:
Table 2: Expense ratio summation
Total expense ratio for shares categories |
|
Grand Total |
The sum of expense ratio for shares categories at low risk was higher (79.92) followed by the sum of expense ratios for average risk shares categories (58.9) while those at high risk recorded the least sum of expense ratio (24.3).This indicates that mutual fund types associated with high risks incur expenditure less than mutual funds with low risks.
An analysis of Expense ratio at various types of mutual funds was also conducted as summarized below.
Table 3: Expense ratio at various types of mutual funds
Category |
Total Expense ratio |
Large Cap |
|
Small Cap |
|
Grand Total |
The total of expense ratio also varies with the type of mutual funds type.
Figure 2: Expense ratio at various types of mutual funds
As indicated in the figure above, the small cap mutual funds category recorded the highest sum of expense ratio (85.53) than the large cap and the mid cap mutual funds categories. The large cap mutual funds category followed closely with 51.73. On the other hand, the mid cap mutual funds category recorded the lowest sum of expense ratio which was 25.69. The grand total of expense ratio was 162.95. This shows that the small cap share category spends more than the other types of mutual funds.
4.6 Assets recorded by the shares categories
The table below shows the sum of assets recorded by the shares categories against the risk level.
Table 4: Sum of Assets
111952.5 |
|
142743.9 |
|
Grand Total |
286290.8 |
The shares category with low risk had the highest sum of assets (142743.9) followed by the shares category with average risk (111952.5) and shares category with high risk recorded the least sum of assets (31594.4). The grand total of all the assets was 286290.8. This indicates that the mutual fund types with low risks performed better than those with high risks thus the difference in total sum of assets. This has been displayed in the chart below.
Figure 3: Total assets of shares categories against risk level
It is clearly evident from the bar chart that the shares categories at low risk recorded the highest total sum of asset while the shares categories at high risk recorded the lowest return on investment. The shares category at average risk recorded an average return on investment as indicated in the bar graph below. This can be attributed to the fact that the higher the risk the higher the probability of encountering unexpected losses (Joshi, 2013).
4.7 Shares categories performance in the year 2013
The pie chart above shows the way the shares categories performed in the year 2013.
Figure 4: A Pie Chart Showing Shares Categories And Their 2013 Return
Small cap shares category recorded the highest percentage of returns in 2013 followed by large cap shares category. Mid cap shares category recorded the least returns in the year 2013. Small cap shares are therefore the best option to consider in share investment plans of the company and individuals.
4.8 Mutual funds and fees payment
The study wanted also to find out the number of mutual funds types who pay fees and those who do not pay fees. 97 of the mutual funds categories do not pay fees while the remaining 24 pay fees. This data is shown in the line graph below.
Figure 5: Line graph of mutual funds types against fees payment
4.9 Performance during the worst quarter
Another aspect of the study was finding out the performance of the mutual funds types during their worst quarter. The data is summarized in the table below which indicates the performance of the mutual funds types during their worst quarter.
Table 5: The performance of the mutual funds types during their worst quarter
Category |
|
large cap |
|
small cap |
|
Grand Total |
The performance of the small cap mutual funds type was the worst recording a deficit of 1131.5. The performance of the large cap mutual funds type followed with a deficit of 736.8 while the mid cap mutual funds type recorded an average deficit of 366.6 during their worst quarter. This shows that during recession it is difficult for small businesses to make good returns as compared to large businesses. The easier option is thus venturing into mid cap for such periods.
4.10 Statistical tests
Statistical tests were carried out to test how expense ratio and returns vary with assets. The The R square value of 0.1044 indicated that the regression model was 10.44% perfect under a standard error value of 6263.89 for assets. ANOVA tests are shown below
Significance F |
|||||
Regression |
705829814.4 |
176457453.6 |
4.497295216 |
0.002052859 |
|
Residual |
4551416716 |
39236351 |
|||
5257246530 |
The variance values demonstrate statistically significant relationship between assets (dependent variable) and expense ratio and returns at 99% confidence interval (p=0.00205). This means that expense and returns are closely determined by asset values. The table below shows detailed regression relationships.
Coefficients |
Standard Error |
|||
Intercept |
9958.496585 |
2337.576766 |
4.260179486 |
4.17454E-05 |
Expense ratio |
-4599.487432 |
1381.37125 |
-3.329653365 |
0.00116622 |
Return 2013 |
19.33756388 |
55.82363893 |
0.346404574 |
0.729666234 |
5Yr-Return |
-2.121666838 |
86.24469157 |
-0.02460055 |
0.98041585 |
3-Yr-Return |
-175.0538682 |
144.2212401 |
-1.213787013 |
0.227294596 |
From the table, there is no statistical significance between assets and 5 or 3-year returns at 95% confidence interval. However, assets demonstrate statistically significant relationship with expense ratio at 99% confidence interval with p=0.0012. The results demonstrate that while assets are not important determiners of long term returns but short term returns. Within the first few years of investment, profitability is low leading to the strong relationship with expenses. However, the beta coefficients show an improvement as time i.e.175.0538682 in 3-year period and -2.121666838 for 5-year period, implying that assets would have a statistically significant result in the long term.
5.0 Ratio Analysis
5.1 Sharpe Ratio
In Sharpe ratio, performance of a fund is assessed basing on the Sharpe Ratio; this is the ration of returns that the fund generates over and above risk free rate of return as well as the total risk allied to it. Whereas a high and positive Sharpe Ratio is an indication of a superior risk-adjusted performance of a fund, a low and negative Sharpe Ratio demonstrated an unfavorable performance. Therefore, where Sharpe Ratio of the mutual fund scheme is higher than the Sharpe Ratio of the market portfolio, this implies that the fund has outperformed the market (Gadhi & Perumal, 2016). Assumptions include that small investors makes full investments within the mutual fund and does not have any portfolio for eliminating unsystematic risk and therefore demands a premium for the total risk. Generally, a mutual fund that has a low Sharpe Ratio is deemed as having a comparatively high unique risk. The mutual funds with a higher Sharpe’s ratio are expected to perform well among other mutual fund schemes (Mohit & Navdeep, 2009).
5.2 Jensen Ratio
This ratio examines the variation between market risk and actual performance of the fund. Positive Jensen ration is an indication of a superior mutual fund. According to Jagongo & Mutswenje (2014) there are three dimensions for examining the ability of an investment analyst to provide higher returns to investors. Jensen ratio evaluates performance of mutual funds as the excess return that portfolio provides over the anticipated returns. A positive value of Jensen ratio demonstrates that the mutual fund has higher return than the market portfolio and is above the security market line. On the other hand, a negative value of Jensen ratio is an indication that the mutual fund has a lower return than the anticipated returns and is below the security market line (Krishnan & Booker, 2002). The mutual funds with a higher Jensen ratio are expected to perform well among other mutual fund schemes.
6.0 General Conclusion
The best types of shares to invest in are the mutual funds in the small cap category. This is because the analysis indicates that the small cap category had the highest number of shares. The next recommended type of share is the large cap shares because this category closely followed the small cap category. The least recommendable type of share is the mid cap category because the analysis indicates that this type had the least shares. In regard to the performance of assets based on their growth, the small cam mutual fund type is the best objective in driving the business. In addition, in regard to the best quarter performance and year-interval performance, the small cap shares category recorded the highest sum of best quarter return whose value was 1915.5 followed closely by large cap shares category (1001.9). Mid cap shares category recorded the least return during its best quarter (580.6) compared to the large cap shares category and the small cap shares category.
However, in regard to expenditure for shares, mutual fund types associated with high risks incur expenditure less than mutual funds with low risks. According to the statistical analysis, the small cap mutual funds category recorded the highest sum of expense ratio (85.53) when compared to the large cap and the mid cap mutual funds categories. This shows that the small cap share category spends more than the other types of mutual funds. Lastly, in regard to performance of shares, mall cap shares category recorded the highest percentage of returns in 2013 followed by large cap shares category. Mid cap shares category recorded the least returns in the year 2013. From the analysis, small cap shares are therefore the best option to consider in share investment plans of the company and individuals.
Implications
The statistical analysis provides a comparative analysis of proportion of investments of funds invested in various kinds of stocks, namely large cap, mid cap and small cap stocks. This has provided a general outlook of the risks and returns of the chosen funds when compared to previous year. In addition, statistical analysis of the portfolio is important in understanding the variability of returns from the mutual funds when compared to previous year. Provided that the statistical analysis indicates that small cap shares are therefore the best option to consider in share investment plans of the company and individuals, followed by the large cap shares, basing on different characteristics; this information will be availed to the client for them to select among large cap, mid cap and small cap stocks. The report recommends that the most reasonable investment choice for clients is small cap shares as per the statistical analysis.
7.0 Bibliography
Gadhi K & Perumal R, 2016, Performance Of Selected Bank Mutual Fund Schemes Impact In Investors’ Decision Making, International Journal of Advanced Research in Management and Social Sciences, 5(3), pp:361-370.
Jagongo A & Mutswenje V, 2014, A Survey of the Factors Influencing Investment Decisions: The Case of Individual Investors at the NSE, International Journal of Humanities and Social Science, 4(4), pp: 92-102.
Joshi J, 2013, Mutual Funds: An investment option from investors’ point of view, IBMRD’s Journal of Management and Research, 2(1), pp: 124-134.
Krishnan R & Booker D, 2002, Investors’ use of Analysts’ recommendations, Behavioral Research in Accounting, 14(1).
Mohit G & Navdeep A, 2009, Mutual Fund Portfolio Creation Using Industry Concentration, Tura: ICFAI University.