4. Using the estimated regression equation for estimation and prediction Aa Aa M

Question

4. Using the estimated regression equation for estimation and prediction Aa Aa Market model is a term used in finance to describe a linear regression model in which the dependent variable is the return on a stock and the independent variable is the return on the overall market. The market model is sometimes extended to include other independent variables-for example, the return on a specific industry sector Company A is one of the leading software companies in the world. Suppose an analyst in an investment bank is creating a market model to predict returns on Company A stock from both market and industry returns. The multiple regression model is: where y daily returns for Company A stock X1daily returns for the Dow Jones Industrial Average x2daily returns for the NASDAQ Computer Index Returns for the Dow Jones Industrial Average (DJIA) will indicate market returns, while those for the NASDAO Computer Index (NCI) indicate industry returns The analyst estimates the parameters 0, 1, and 2 using daily returns for the period January 3, 2005, through December 30, 2005. The estimated multiple regression equation is: y 0.0008 + 0.6404X1 + 0.6869X2 The coefficient 0.6869 in the estimated multiple regression equation is: O The estimated change in average Company A stock return for a one-unit change in DJIA return, keeping the NCI return constant O The estimated average Company A stock return when the DJIA and NCI returns are zero O The estimated increase in average Company A stock return when the DJIA and NCI returns change by one unit O The estimated change in average Company A stock return for a one-unit change in NCI return, keeping the DJIA return constant Based on his study, the analyst expects a downturn for the overall market but an upturn for the computer industry He expects a-2%--0.02 return for the DJIA and a 1%-0.01 return for the NCI when the DJIA return is-2% and the NCI return is 196, the average Company A stock return for all trading days is estimated to be , and the predicted Company A stock return for one specific trading day is . This predicted return has the average returr

Explanation / Answer

The coefficient 0.689 corresponds to Option 4.

The estimated value (first fill in the blanks)=-0.005139 [Substitute the values of X1 and X2 in the given regression equation].

Second fill in the blanks value is -0.0000140.

The 95% confidence interval for given value is (-5.35,4.32)

The 95% prediction interval for given value is (-13.04,12.01)

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