1. Look again at the companies listed in Table 8-2 (49.0K) . Monthly rates of return for most of these companies can be found on the Standard & Poor's Market Insight Web site (http://www.mhhe.com/edumarketinsight)—see the "Monthly Adjusted Prices" spreadsheet. This spreadsheet also shows monthly returns for the Standard & Poor's 500 market index. What percentage of the variance of each company's return is explained by the index? Use the Excel function RSQ, which calculates R².
   
   
2. Pick at least five of the companies identified in Practice Question 3 (http://www.mhhe.com/edumarketinsight). The "Monthly Adjusted Prices" spreadsheets should contain about four years of monthly rates of return for the companies' stocks and for the Standard & Poor's 500 index.
   1. Split the rates of return into two consecutive two-year periods. Calculate betas for each period using the Excel SLOPE function. How stable was each company's beta?
   2. Suppose you had used these betas to estimate expected rates of return from the CAPM. Would your estimates have changed significantly from period to period?
   3. You may find it interesting to repeat your analysis using weekly returns from the "Weekly Adjusted Prices" spreadsheets. This will give more than 100 weekly rates of return for each two-year period.
   
   
3. Identify a sample of food companies on the Standard & Poor's Market Insight Web site (http://www.mhhe.com/edumarketinsight). For example, you could try Campbell Soup (CPB), General Mills (GIS), Kellogg (K), Kraft Foods (KFT), and Sara Lee (SLE).
   1. Estimate beta and R² for each company from the returns given on the "Monthly Adjusted Prices" spreadsheet. The Excel functions are SLOPE and RSQ.
   2. Calculate an industry beta. Here is the best procedure: First calculate the monthly returns on an equally weighted portfolio of the stocks in your sample. Then calculate the industry beta using these portfolio returns. How does the R² of this portfolio compare to the average R² for the individual stocks?
   3. Use the CAPM to calculate an average cost of equity (r_equity) for the food industry. Use current interest rates—take a look at footnote 8 in this chapter—and a reasonable estimate of the market risk premium.
   
   
4. If you have access to "Data Analysis Tools" in Excel, use the "regression" functions to investigate the reliability of the betas estimated in Practice Questions 4 and 6 (http://www.mhhe.com/edumarketinsight).
   1. What are the standard errors of the betas from questions 4(a) and 4(c)? Given the standard errors, do you regard the different beta estimates obtained for each company as signficantly different? (Perhaps the differences are just "noise.") What would you propose as the most reliable forecast of beta for each company?
   2. How reliable are the beta estimates from question 6(a)?
   3. Compare the standard error of the industry beta from question 6(b) with the standard errors for individual company betas. Given these standard errors, would you rely on the industry beta or betas for individual companies?

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