为何这里不用研究每个变量系数的t值？

问题如下：

Based on past research, Hansen selects the following independent variables to predict IPO initial returns:

Underwriter rank = 1–10, where 10 is highest rank

Pre-offer price adjustment (Expressed as a decimal) = (Offer price – Initial filing price)/Initial filing price

Offer size ($ millions) = Shares sold × Offer price

Fraction retained (Expressed as a decimal) = Fraction of total company shares retained by insiders

Hansen’s Regression Results Dependent Variable: IPO Initial Return (Expressed in Decimal Form, i.e., 1% = 0.01)

The upcoming IPO has the following characteristics:

l underwriter rank = 6;

l pre-offer price adjustment = 0.04;

l offer size = $40 million;

l fraction retained = 0.70.

Based on Hansen’s regression, the predicted initial return for the upcoming IPO is closest to:

选项：

A.

0.0943.

B.

0.1064.

C.

0.1541.

解释：

C is correct.

The predicted initial return (IR) is:

IR = 0.0477 + (0.0150 × 6) + (0.435 × 0.04) – (0.0009 × 40) + (0.05 × 0.70) = 0.1541