Financial Risk Manager Part 1
Get started today
Ultimate access to all questions.
Comments
Loading comments...
Ultimate access to all questions.
In the context of financial risk management, particularly when evaluating the statistical relationship between variables, regression analysis is a pivotal tool. Consider a scenario where a linear regression analysis has been performed to determine the relationship between a dependent variable (such as asset returns) and one or more independent variables (such as economic indicators). Given this setup, which statement accurately reflects the correct interpretation of the regression results?
A
The estimated coefficient of 0.3533 indicates that the returns of the Russell 3000 Index are more statistically significant in determining the portfolio returns than the other two indexes.
B
The high adjusted R2 indicates that the estimated coefficients on the Russell 1000, Russell 2000, and Russell 3000 Indexes are statistically significant.
C
The high p-value of 0.9452 indicates that the regression coefficient of the returns of the Russell 1000 Index is more statistically significant than the other two indexes.
D
This is an example of multicollinearity, which arises when one of the regressors is very highly correlated with the other regressors. In this case, all three regressors are highly correlated with each other, so multicollinearity exists between all three.