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Answer to question 3 Let Y and X be weekly excess returns of a US firm...
Let Y and X be weekly excess returns of a US firm and S&P 500 index...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 Suppose that the model satisfies the usual SLR model assumptions, and that the SST for Y is 0.355....
Let Y and X be weekly excess returns of a US firm and S&P 500 index...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (iv) Suppose further that X = 0.0001 and 8x = 0.02711201. Construct the 90% forecast interval for the...
Let Y and X be weekly excess returns of a US firm and S&P 500 index...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (ii) Compute the sample variance for Y (รื่.) and sample correlation between X and Y (Txy).
Let Y and X be weekly excess returns of a US firm and S&P 500 index...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (vii) When explaining the firm's analysis to an investor, a junior analyst suddenly found that he misplaced Y...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 Suppose that the model satisfies the usual SLR model assumptions, and that the SST for Y is 0.355....
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (iv) Suppose further that X = 0.0001 and 8x = 0.02711201. Construct the 90% forecast interval for the...
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (ii) Compute the sample variance for Y (รื่.) and sample correlation between X and Y (Txy).
Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. The regression output for this data set in shown in the table below: (You can actually download similar data from http://finance.yahoo.com/) Variable Coefficient Intercept -0.008194 1.690067 t-value p-value 0.0282 12.392<2×10-16 s.e. 0.003680-2.22 7 0.136379 n 103 R 0.6033 s 0.03734 (vii) When explaining the firm's analysis to an investor, a junior analyst suddenly found that he misplaced Y...
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