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Call: lm(formula = RetAIG RetSPX) Residuals: Min 1Q Median 3Q Max -7.8036 -1.5117 -0.2184 1.2153 9.5926 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.1381
Call: lm(formula = RetAIG RetSPX) Residuals: Min 1Q Median 3Q Max -7.8036 -1.5117 -0.2184 1.2153 9.5926 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.1381 0.2550 -0.542 0.589 RetSPX 1.6463 0.1815 9.071 9.23e-15 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.598 on 102 degrees of freedom Multiple R-squared: 0.4465,Adjusted R-squared: 0.4411 F-statistic: 82.29 on 1 and 102 DF, p-value: 9.225e-15 From the above summary of the regression of AIG's weekly excess returns (RetAIG) on the excess returns of S&P500 Index (RetSPX) from 2010 to 2011, answer the following: (i) What proportion of the variability in AIG's returns is explained by market returns, and what is the correlation between the two? (ii) What is the total sum of squares (SST)? (iii) What is a 95% confidence interval for the CAPM ? 4 (iv) What is the t-statistic for a hypothesis test of whether or not the CAPM is equal to 0.10? What do you conclude at significance level = 0.05
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