(c) Make a table showing the estimated values of ;, its estimated standard error, estimate of i, and the R values from the four regression equations. Asset B SE (3) Ei R the (1) 2 = GIM, R iM and the correlation M iM (d) Characterize the relation among Bi coefficient PiM. Can || > 1 or | R| > 1? ; = ( ) (Ri) PiM = ( ) (Ri) |B|> 1? possible ( ) not possible ( ) |Ri| > 1? possible ( ) not possible ( ) From (1), which asset appears to be most correlated to "Market"? What does it mean in terms of risk diversification? (f) Can ; be negative? Why or why not? If ; for an asset is negative, would you like to hold the asset in your portfolio? Briefly explain why. We may use the S&P 500 index as the "market return" for our SI model. The following represents R linear regression output from estimating the SI model for the four North- west stocks (Boeing, Microsoft, Nordstrom and Starbucks) using monthly continuously com- pounded return data over the the period November 1998 October 2003. > summary(boeing.fit) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.00216 sp500 0.01366 0.16 0.875 0.63862 0.27354 2.33 0.023 * Residual standard error: 0.106 on 58 degrees of freedom Multiple R-squared: 0.0859, Adjusted R-squared: 0.0701 F-statistic: 5.45 on 1 and 58 DF, p-value: 0.023 > summary(nord.fit) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.00432 0.01414 sp500 0.31 0.76 1.50799 0.28312 5.33 1.70E-06 *** Residual standard error: 0.11 on 58 degrees of freedom Multiple R-squared: 0.328, Adjusted R-squared: 0.317 F-statistic: 28.4 on 1 and 58 DF, p-value: 1.7e-06 > summary(msft.fit) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.0012 sp500 0.014 0.09 0.93 1.6971 0.2808 6.04 1.20E-07 *** Residual standard error: 0.109 on 58 degrees of freedom Multiple R-squared: 0.386, Adjusted R-squared: 0.376 F-statistic: 36.5 on 1 and 58 DF, p-value: 1.16e-07 > summary(sbux.fit) Coefficients: Estimate Std. Error t value Pr(>|t!) (Intercept) 0.0183 0.0171 sp500 1.07 0.288 0.6666 0.3418 1.95 0.056. Residual standard error: 0.132 on 58 degrees of freedom Multiple R-squared: 0.0615, Adjusted R-squared: 0.0454 F-statistic: 3.8 on 1 and 58 DF, p-value: 0.056 (*1 Signif. codes: 0 '**** 0.001 **** 0.01 0.05 0.1'1 The followings are estimated regression lines for each SI model. Boeing returns SI model for MSFT 0 SI model for SBUX 88 8 1:|: 1:|: 8 -0.10 -0.05 0.0 0.05 0.10 -0.10 -0.05 0.0 0.05 0.10 -0.4 -0.2 0.0 0.2 SP 500 returns SI model for Boeing 00 & % o 80000 D 8 8 0 0 8 -0.10 -0.05 0.0 0.05 0.10 SP 500 returns NORD returns -0.1 0.1 0.3 -0.3 -0.10 8 -0.05 SP 500 returns SI model for NORD 80 0.0 0.05 0.10 SP 500 returns (g) For MSFT stock, write down the test statistics for the hypotheses Hoi H B 1. 2 = = 1 vs. (h) Which asset has a (statistically) non-zero intercept (with 5% significance level)?