University of Hartford Barney School of Business Department of Economics, Finance, Insurance QNT 230 B. Kolluri Regression Project Summer 2016 Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable, and U.K. T-Bill Returns, U.S. Stock Returns, and Japan Stock Returns as the independent variables using the annual data covering the sample period 1981-2015 (Finding the determinants of U.K. stock returns). a. Show the estimated regression relationship b. Conduct a t-test for statistical significance of the individual slope coefficients. Provide the interpretation of the significant slope estimates. c. Conduct a test for the overall significance of the regression equation. (Test for the significance of the regression relationship as a whole) d. Present the R-Square (Coefficient of Determination) and its interpretation. NOTE 1. The Excel data file you need for this assignment is in this file with the name, \"GFD annual returns from 1981 to 2015. This is the same Global Financial Data that you have used a part of it in the lab assignment in Chapter 11. The following are the variable definitions for your information: 1. 2. 3. 4. RSUK stands for UK Stock returns RUK stands for UK T-bill returns RSUS stands for US Stock returns RSJA stands for Japan Stock returns NOTE 2. You can rearrange the Excel data starting with RSUK in the first column as the dependent variable and the rest of the variables in other columns as the independent variables in the order stated in the regression model. Use 0.01 level of significance in this project. Date 12/31/1981 12/31/1982 12/31/1983 12/31/1984 12/31/1985 12/31/1986 12/31/1987 12/31/1988 12/31/1989 12/31/1990 12/31/1991 12/31/1992 12/31/1993 12/31/1994 12/31/1995 12/31/1996 12/31/1997 12/31/1998 12/31/1999 12/31/2000 12/31/2001 12/31/2002 12/31/2003 12/31/2004 12/31/2005 12/31/2006 12/31/2007 12/31/2008 12/31/2009 12/31/2010 12/31/2011 12/31/2012 12/31/2013 12/31/2014 12/31/2015 SUMMARY OUTPUT RSUS -5.0530 21.4833 22.4997 6.1523 31.6476 18.6034 5.1709 16.6084 31.6862 -3.1043 30.4659 7.6194 10.0787 1.3205 37.5778 22.9603 33.3633 28.5786 21.0415 -9.1044 -11.8858 -22.1005 28.6846 10.8820 4.9114 15.7950 5.4937 -36.9976 26.4635 15.0640 2.1118 16.0032 32.3885 13.6884 1.3838 RSUK -8.9427 9.0876 15.8657 5.2976 49.2938 31.2841 37.5346 6.9492 21.1952 8.2424 16.5587 -2.4383 25.5652 -0.1560 22.6211 28.8714 20.3430 13.2230 20.8922 -12.8679 -15.6997 -14.3372 33.9844 21.2178 9.5188 32.8288 6.7166 -48.3966 43.8257 10.5840 -3.8507 17.3562 23.1877 -4.8262 -4.4394 RSJA 8.2192 -0.9560 26.4963 16.1085 45.6889 89.6874 45.0135 32.8039 6.5847 -35.7575 7.8105 -23.0680 23.8414 22.3367 -1.5505 -16.2528 -28.4572 7.9707 77.2184 -32.7224 -29.3984 -8.2484 38.8278 15.6021 26.9738 2.0798 -6.0036 -25.9680 5.0835 14.4818 -12.0352 8.1122 26.3030 -2.9372 11.1031 RUK -8.9190 -5.4473 -1.2883 -12.4870 39.4211 14.1438 39.6077 5.7781 1.6307 37.9559 7.5376 -11.4991 3.0392 11.6530 5.4308 17.0083 2.6133 7.5019 2.8874 -2.0297 2.0212 15.2766 15.0206 12.5200 -5.9878 19.1941 7.0430 -23.2280 11.1147 -2.8994 0.1284 4.8979 2.3507 -5.5539 -4.9255 Regression Statistics Multiple R 0.872403 R Square 0.761087 Adjusted R Square 0.737967 Standard Error 8.569922 Observations 35 ANOVA df Regression SS MS 3 7252.89 2417.63 31 2276.75 73.44356 34 Coefficient s 9529.64 Standard Error Intercept 4.429016 1.705159 2.59742 RSUK 0.996854 0.113253 RSJA -0.07949 0.061548 RUK -0.55425 0.139622 Residual Total t Stat F 32.9182 P-value Significance F 9.23E-10 Lower 95% Upper 95% Lower 99.0% Upper 99.0% 0.01424 0.95132 7.906711 -0.25001 9.108045 8.801995 6.15E-10 0.765872 1.227835 0.686082 1.307625 -1.29148 0.206084 -0.20502 0.04604 -0.24838 0.089402 -3.96962 0.000397 -0.83901 -0.26949 -0.93737 -0.17112