Solve the previous problem, but analyze GE instead of Microsoft.

Data from Previous Problem:

Given the data in the file Stock Beta.xlsx, estimate the beta (and alpha) for Microsoft (MSFT). Do this for each criterion and each period of time to obtain a table analogous to that in the top right of Figure 7.49. What do you conclude about Microsoft?

Figure 7.49:

The Beta Estimation Model (for McDonald's) K 1 Model for estimating company betas Possible objectives 3-year Betas for various objectives for McDonald's 2 3 Parameters All data 3-year All data 4 Alpha 5 Beta 0.5023 0.0062 SE 0.0350 0.2010 SSE 0.3112 WSSE SAE MaxAE 0.3112 0.0318 0.1426 WSSE 0.3197 0.4737 0.4713 0.5203 0.7626 0.8906 3.9385 SAE 7 Weighting constant 0.3475 0.995 0.0640 0.1091 8. SqError 0.00029 Weight Mkt return AbsError Range names used: Alpha Beta Date Stock return -0.0088 Predicted Error =Model!$B$4 |=Model!$B$5 =Model!$E$7 |=Model!$F$7 =Model!$E$6 =Model!$F$6 |=Model!$E$4 =Modell$F$4 |=Model!$E$5 0.0083 0.0149 0.0200 0.0154 -0.0036 10 Dec-2013 11 Nov-2013 12 Oct-2013 13 Sep-2013 14 Aug-2013 15 Jul-2013 16 Jun-2013 17 May-2013 18 Apr-2013 0.0069 -0.0171 0.0171 0.9950 0.0024 0.0280 0.0172 0.00001 0.0024 |a_3 |a_All -0.0169 0.0042 -0.0266 -0.0309 0.0446 0.0031 0.00029 0.0169 0.9900 0.0042 0.0297 0.0197 0.00002 0.9851 0.00071 -0.0313 SAE_3 SAE_All -0.0302 0.0266 0.9801 0.0215 0.9752 -0.0093 0.00095 0.0309 0.0495 0.0015 0.0126 0.0118 0.0174 0.0009 0.0011 0.0100 SSE 3 |SSE_All WSSE 3 0.00056 -0.0150 0.0252 0.0237 0.0237 0.9704 -0.0597 0.0128 0.0222 -0.0480 0.9655 0.0208 -0.0470 0.00356 0.0597 0.0181 0.0246 0.00016 0.0128 0.9607 19 Mar-2013 126 Apr-2004 127 Mar-2004 128 Feb-2004 129 Jan-2004 0.0222 0.9559 0.5591 0.5563 0.0395 0.0360 0.00049 0.0023 -0.0168 -0.0471 0.0480 0.0087 0.0087 0.0895 -0.0164 0.0098 0.0001 0.0895 0.0122 0.0995 0.0080 0.5535 0.5507 -0.0379 0.0011 -0.0390 0.0015 0.0390 -0.0163