DATA : C17-02a >> https://1drv.ms/x/s!AH-ZI1II9WjugTU DATA : C17-02b >> https://

Question

DATA : C17-02a >> https://1drv.ms/x/s!AH-ZI1II9WjugTU

DATA : C17-02b >> https://1drv.ms/x/s!AH-ZI1II9WjugTc

Case 17.2 An Analysis of Mutual Fund Managers, Part 2 DATA C17-02a c17zb addition to analyzing the relationship between the managers' characteristic and the performance of the fund, researchers wanted to determine whether the same characteristics are related to the behavior of the fund. In particular, they wanted to know whether the risk of the fund and its management expense ratio (MER) were related to the manager's age, tenure, university SAT score, and whether he or she had an MBA © RTimages/ Shutterstock.com In Section 4-6, we introduced the market model wherein we measure the systematic risk of stocks by the stock's beta. The beta of a portfolio is the average of the betas of the stocks that make up the portfolio. File C17-02a stores the same managers' characteristics as those in file C17-01. However, the first column contains the betas of the mutual funds. To analyze the management expense ratios, it was decided to include a measure of the size of the fund. The logarithm of the funds' assets (in Smillions) was recorded with the MER. These data are stored in file C17-02b. Analyze both sets of data and write a brief report of your findings

Explanation / Answer

Answer to the question)

Since the data is not being retrieved in excel , else I would have shared the calculations

I can guide you through the steps

For both the data sets , we can make use of the regression analysis tool in excel and analyse what factors affect the risk of the funds and the management expense ratios

.

For that in excel :

click on the data tab

In the options under data tab , select data analysis

A new window opens up

In this window select "regression"

Click ok

Now the regression window opens up on screen

In this window: select Y as the Beta data or MER data

Then select rest of the variables data as X range (because X denotes the predictors)

Then Click ok

We get the output for each of the data set

Now compare the values of r and r square that we get in the first table of the output

.

r is the correlation coefficient value. if this value is close to 0 it indicates a weak relation of the response variable with the entire set of predictor variables

and it the value of r is close to 1 , then this indicates a strong relation between the response and the predictor variables

Likewise : r square value is called coefficient of determination. It tells us what percent of the variation is explained by the model.

Again if R square value is close to 1, this indicates that the model is able to explain good proportion of variation iin the response variable , and thus the model is a good fit.

Related Questions

Navigate

• Browse (All)
• Browse D
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.