NO.PZ2022062760000016
问题如下：
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 Index. This OLS procedure is designed to:
选项：
A.
Minimize the square of the sum of differences between the actual and estimated S&P 500 Index 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 Index returns.
D.
Minimize the sum of squared differences between the actual and estimated stock returns.
解释：
中文解析：
OLS 过程是一种在线性回归模型中估计未知参数的方法。该方法最小化实际、观察到的收益与通过线性近似估计的收益之间的平方差之和。观察值和估计值之间的平方差之和越小，估计的回归线越适合观察到的数据点。
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.
选项A错在哪里？谢谢！
