This table contains monthly return data on two stocks of Delta (airline industry) and IBM (computer industry), Market Index (the S&P 500), and risk-free rate (3 month T-bills) over the period January 1983 to December 1987.

OBS	DELTA	IBM	MARKET	RKFREE
1983:01	0.04	0.027	0.065	0.00646
1983:02	0.027	0.01	0.028	0.00599
1983:03	-0.016	0.028	0.043	0.00686
1983:04	-0.043	0.15	0.097	0.00652
1983:05	-0.045	-0.041	0.08	0.00649
1983:06	0.012	0.081	0.048	0.00673
1983:07	-0.259	0.001	-0.017	0.00714
1983:08	0.08	0.001	-0.034	0.00668
1983:09	0.041	0.062	0	0.00702
1983:10	0.039	-0.001	-0.082	0.00678
1983:11	0.12	-0.066	0.066	0.00683
1983:12	-0.028	0.039	-0.012	0.00693
1984:01	-0.013	-0.065	-0.029	0.00712
1984:02	-0.117	-0.026	-0.03	0.00672
1984:03	0.065	0.034	0.003	0.00763
1984:04	-0.085	-0.002	-0.003	0.00741
1984:05	-0.07	-0.044	-0.058	0.00627
1984:06	-0.012	-0.019	0.005	0.00748
1984:07	0.045	0.047	-0.058	0.00771
1984:08	0.04	0.127	0.146	0.00852
1984:09	0.008	0.004	0	0.0083
1984:10	0.161	0.012	-0.035	0.00688
1984:11	-0.026	-0.023	-0.019	0.00602
1984:12	0.156	0.011	-0.001	0.00612
1985:01	-0.01	0.108	0.097	0.00606
1985:02	0.087	-0.009	0.012	0.00586
1985:03	-0.003	-0.052	0.008	0.0065
1985:04	-0.123	-0.004	-0.01	0.00601
1985:05	0.179	0.025	0.019	0.00512
1985:06	0.021	-0.038	-0.003	0.00536
1985:07	0.008	0.062	0.012	0.00562
1985:08	-0.066	-0.028	0.005	0.00545
1985:09	-0.112	-0.022	-0.055	0.00571
1985:10	-0.083	0.048	0.026	0.00577
1985:11	0.02	0.085	0.059	0.0054
1985:12	0.03	0.113	0.013	0.00479
1986:01	0.122	-0.026	-0.009	0.00548
1986:02	-0.055	0.003	0.049	0.00523
1986:03	0.076	0.004	0.048	0.00508
1986:04	0.059	0.031	-0.009	0.00444
1986:05	-0.043	-0.018	0.049	0.00469
1986:06	-0.07	-0.039	0.004	0.00478
1986:07	0.018	-0.096	-0.076	0.00458
1986:08	0.018	0.055	0.049	0.00343
1986:09	0.026	-0.031	-0.047	0.00416
1986:10	0.134	-0.081	0.018	0.00418
1986:11	-0.018	0.037	0	0.0042
1986:12	-0.01	-0.056	-0.005	0.00382
1987:01	0.161	0.073	0.148	0.00454
1987:02	0.133	0.092	0.065	0.00437
1987:03	-0.129	0.076	0.037	0.00423
1987:04	-0.121	0.067	-0.025	0.00207
1987:05	0.151	0.006	0.004	0.00438
1987:06	0.014	0.016	0.038	0.00402
1987:07	0.043	-0.009	0.055	0.00455
1987:08	-0.037	0.053	0.015	0.0046
1987:09	-0.067	-0.105	-0.015	0.0052
1987:10	-0.26	-0.187	-0.26	0.00358
1987:11	-0.137	-0.087	-0.07	0.00288
1987:12	0.121	0.043	0.073	0.00277

1. Using the 60 observations from January 1983 to December 1987, estimate by OLS (ordinary least squares) the parameters di and B; in the single index model regression: rit rft = di + Bi (rmt - rft) + Eit, i = Delta, IBM (1) for each of the two stocks. Report the estimated regression line with the estimated standard error underneath the estimated coefficients and the R-squared statistic. e.g., Ri,t= 0.003 +0.673Rm,t , R2 = 0.432 (0.008) (0.059) (2) where Ri,t = rit rft and Rm,tImt rft. Do the estimates of B correspond well with your prior intuition or beliefs about these stocks? Why or why not? 2. For each company, make a scatter plot with the company return on the vertical axis, the return on the market portfolio on the horizontal axis, and the estimated single index model regression line drawn through the scatter. Based on the scatter plot, comment on the fit of the regression by interpreting the RP of the regression. 3. For each company, construct a 95% confidence interval for 3. Then, using a 5% significance level, test the null hypothesis that the company's risk is the same as the risk of the market portfolio against the alternative that it is different (i.e., a two-tailed test with (H :B + 1). Also, if the estimated B is less than 1, conduct a one-tailed test with (H :B 1). Did you find any surprises in these tests? (Note: when you cannot reject the null hypothesis, do not say "accept the null. Just say that you fail to reject the null.) 1. Using the 60 observations from January 1983 to December 1987, estimate by OLS (ordinary least squares) the parameters di and B; in the single index model regression: rit rft = di + Bi (rmt - rft) + Eit, i = Delta, IBM (1) for each of the two stocks. Report the estimated regression line with the estimated standard error underneath the estimated coefficients and the R-squared statistic. e.g., Ri,t= 0.003 +0.673Rm,t , R2 = 0.432 (0.008) (0.059) (2) where Ri,t = rit rft and Rm,tImt rft. Do the estimates of B correspond well with your prior intuition or beliefs about these stocks? Why or why not? 2. For each company, make a scatter plot with the company return on the vertical axis, the return on the market portfolio on the horizontal axis, and the estimated single index model regression line drawn through the scatter. Based on the scatter plot, comment on the fit of the regression by interpreting the RP of the regression. 3. For each company, construct a 95% confidence interval for 3. Then, using a 5% significance level, test the null hypothesis that the company's risk is the same as the risk of the market portfolio against the alternative that it is different (i.e., a two-tailed test with (H :B + 1). Also, if the estimated B is less than 1, conduct a one-tailed test with (H :B 1). Did you find any surprises in these tests? (Note: when you cannot reject the null hypothesis, do not say "accept the null. Just say that you fail to reject the null.)