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Running Header: ECONOMETRICS1ECONOMETRICSStudent's name:Institution:Professor's name:Course code:
Econometrics21.Regression model using Microsoft datarp_ms = 0.006 + 1.319rp_mktStandard Error0.008 0.161R2 = 0.342.The beta estimate for risk premium on the market portfolio is 1.319. The beta suggests that whenall other factors are kept constant, when the market portfolio risk premium increases by a unit, itwill result in a 1.319 increase in the Microsoft risk premium. Conversely, the standard error orthe market portfolio risk premium is 0.161. Thus, the standard error suggests that the mean datapoints distance from the line fitted is about 0.161.3.To test the null hypothesis that αj = 0 for the Microsoft stock, the following hypothesis wasdeveloped:Ho: αj = 0H1: αj ≠ 0The hypothesis was tested using Wald test.The decision is not to reject the null hypothesis since Wald p-values of t-statistic, F-statistic, andChi-square are greater than 0.00. Thus, αj for a security j under market efficiency is equal to 0(Schwert, 2003). However, the linear restrictions are identical since F-statistics and the Chi-square value are the same.
Econometrics34.On the other hand, to test the null hypothesis that βj = 0 for the Microsoft stock, the followinghypothesis was developed:Ho: βj = 0H1: βj ≠ 0The Wald Test was utilized.The decision derived is to reject the null hypothesis since probability values of t-statistics, F-statistic, and Chi-square are all 0.00. Thus, βj for a security j under market efficiency is not equalto 0. However, the linear restrictions are identical since F-statistics and the Chi-square value arethe same.5.To evaluate the claim that the tech stocks typically have a high beta value, a confidence intervalwas used (Altman & Bland, 2011). From the results, it was seen that at 90% confidence intervalthe beta ranged from 1.05 to 1.59. On the other hand, at 95% confidence interval, the beta rangedfrom 1.0008 to 1.6371. Thus, the tech stock typically has a high beta value (β > 1).6.From the regression model, the R2 was 0.34. The R2 for the regression means that the modelexplains 34% of the response data around its mean.7.
Econometrics4Risk free rate for December 2008:0.000025Market return as at December 2008: 0.21482Market return as at January 2009 = 0.21482 * 1.01 = 0.216968Regression model:rp_ms = 0.006 + 1.319rp_mktThus, predicted Microsoft return = 0.006 + 1.319*0.216968= 0.2921818.a)Regression model using GErp_ge = -0.001 + 0.899rp_mktStandard Errors0.005 0.099R2 = 0.39b)Regression model using GMrp_gm = -0.0116 + 1.261rp_mktStandard Errors 0.010 0.202R2 = 0.23c)Regression model using IBMrp_ibm = 0059 + 1.1882rp_mktStandard Errors0.006 0.126R2 = 0.40d)Regression model using Disneyrp_disney = -0.0011 + 0.8978rp_mktStandard Errors0.006 0.124