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 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 (vii) When explaining the firm's analysis to an investor, a junior analyst suddenly found that he misplaced Y...
Answer to question 3 Let Y and X be weekly excess returns of a US firm and S&P 500 index for the past two years, respectively. (You can actually download similar data from http://finance.yahoo.com/) The regression output for this data set in shown in the table below: Variable Coefficient t-value s.е. Intercept -0.008194 0.003680 1.690067 0.136379 p-value 0.0282 2 x 10-16 12.392 Sq-0.03734 n= 103 17=0.6033 Suppose that the model satisfies the usual SLR model assumptions, and that the SST...
In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and from the company ABC Shares derived from weekly data over a 12 month period, can you please explain the key measures and what this all means eg. Number of Observations, R Square, Value of the Slope and the P-Value of the Slope etc. SUMMARY OUTPUT Regression Statistics Multiple R 0.045274332 R Square 0.002049765 Adjusted R Square -0.01790924 Standard Error 0.023996449 Observations 52 ANOVA df...