Question

In: Statistics and Probability

Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable (intercept), and RBUK, U.S.

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.727076179
R Square 0.528639771
Adjusted R Square 0.525504337
Standard Error 3.573206748
Observations 455
ANOVA
df SS MS F Significance F
Regression 3 6458.025113 2152.67504 168.601791 2.7119E-73
Residual 451 5758.280717 12.7678065
Total 454 12216.30583
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 99.0% Upper 99.0%
Intercept -0.250148858 0.359211364 -0.6963835 0.48654745 -0.9560846 0.45578693 -1.1793476 0.67904987
RBUK 0.025079378 0.023812698 1.05319345 0.29281626 -0.0217182 0.07187699 -0.0365187 0.08667745
RSUS 0.713727515 0.042328316 16.8617037 8.0578E-50 0.6305423 0.79691273 0.60423372 0.82322131
RSJA 0.222104292 0.029996288 7.40439254 6.5208E-13 0.16315445 0.28105414 0.14451066 0.29969792

Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable (intercept), and RBUK, U.S. Stock Returns RSUS, and Japan Stock Returns RSJA as the independent variables using the monthly data covering the sample period 1980-2017 (Finding the determinants of U.K. stock returns) 1) Show the estimated regression relationship 2) Conduct a t-test for statistical significance of the individual slope coefficients at the 1% level of significance. Provide the interpretation of the significant slope estimates Make sure you conduct the testing procedures by both methods of testing, the P value method and the Critical value method with all the details.

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Expert Solution

orchestra answered 2 years ago
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