A risk manager performs an ordinary least squares (OLS) regression to estimate the sensitivity of a stock's return to the return on the S&P 500. This OLS procedure is designed to:
A. Minimize the square of the sum of differences between the actual and estimated S&P 500 returns.
B. Minimize the square of the sum of differences between the actual and estimated stock returns.
C. Minimize the sum of differences between the actual and estimated squared S&P 500 returns.
D. Minimize the sum of squared differences between the actual and estimated stock returns.
Answer:D
The OLS procedure is a method for estimating the unknown parameters in a linear regression model. The method minimizes the sum of squared differences between the actual (observed) returns and the returns estimated by the linear approximation. The smaller the sum of the squared differences between observed and estimated values, the better the estimated regression line fits the observed data points.

 
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