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A time-series monthly dataset is available for US stock portfolios between July 1927 and January 2020, including the excess return on the Telecommunications Sector portfolio
A time-series monthly dataset is available for US stock portfolios between July 1927 and January 2020, including the excess return on the Telecommunications Sector portfolio (Telcm-RF), the excess return on the market portfolio (Mkt-RF), the Small Minus Big size portfolio (SMB), High Minus Low value portfolio (HML) and the risk- free rate of the US economy (RF). The sample size (n) is 1123. The following model is considered for the purpose of explaining the excess return on the Telecommunications Sector portfolio: (Telcm - RF) = a + 1(Mkt - RF) + B2SMB + B3HML (2) The output of regression model (2) is provided in Table 2 below: Table 2: Summary Output for regression equation (2). Regression Statistics Multiple R 0.776 R Square 0.602 Adj. R Square 0.601 Standard Error 2.890 Observations 1123 ANOVA df SS MS F Signif. F Regression 3 14138.67299 4712.890997 564.3429198 2.574E-223 Residual 1119 9344.894461 8.351112119 Total 1122 23483.56745 Standard Coefficients Error t Stat Intercept 0.166 0.087 1.91 Mkt-RF 0.696 0.017 39.77 SMB -0.137 0.029 -4.77 HML -0.051 0.026 -1.98 a) Test the null hypothesis that Ho: a = 0 against H,: a = 0 using a size of 5%. (3 marks) b) Test the null hypothesis that Ho: a = 0 against H1: a > 0 using a size of 5%. What is the p-value of this test? (4 marks)c) Calculate the 99% confidence interval for parameter B, of regression equation (2). Based on the information provided by this interval, how likely is it for the Mkt - RF independent variable to be insignificant in the context of regression model (2)? (5 marks) d) Provided that _t=2(et - et-1) = 18140.31 calculate the Durbin-Watson statistic. What does the value of the statistic suggest about the possibility of the residuals of model (2) being autocorrelated? ((5 marks) e) Test the overall significance of model (2) at the 5% level. The 5% right-tail of the relevant F-distribution is approximately 2.6. Present clearly all the steps of the test. (5 marks) f) Explain what is the error autocorrelation problem. In the context of which type of models/data does this problem occur? Discuss possible treatments of this
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