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我的世界守则 · 2023年07月07日

p= SD(X) / SD(Y) ∗ b 这个公式在基础班讲义里没看到呀 ​

NO.PZ2016062402000020

问题如下:

Consider the following linear regression model: Y=a+bX+e. Suppose a=0.05, b=1.2, SD(Y) = 0.26, and SD(e) = 0.1. What is the correlation between X and Y?

选项:

A.

0.923

B.

0.852

C.

0.701

D.

0.462

解释:

We can find the volatility of X from the variance decomposition Equation: V(y)=β2V(x)+V(e)V(y)=\beta^2V(x)+V(e). This gives V(x)=V(y)V(e)β2=0.2620.1021.22=0.04V(x)=\frac{V(y)-V(e)}{\beta^2}=\frac{0.26^\wedge2-0.10^\wedge2}{1.2^2}=0.04. Then SD(X) = 0.2, and p=SD(X)bSD(Y)=1.2×0.20.26=0.923p=\frac{SD{(X)^\ast b}}{SD{(Y)}}=\frac{1.2\times0.2}{0.26}=0.923.

我试着自己推了一下,不知道是不是可以把这个当成一个结论。


Y = a + bX + ε, 因此V(Y) = (bX)^2 + V(ε), 带入得 0.26^2 = 1.2^2 * V(X) +0.1^2, 得到V(X)=0.04。

Cov(X,Y)= E[(X-E(X)]*E[(Y-E(Y))], 把= a + bX + ε 代入,得

Cov (X,Y)= E[(X-E(X)] *E(a+bX+ε - a-b*E(X)) = E[(X-E(X)] * b* E(X-E(X)) = b*E(X-E(X))^2 = b*V(X)


所以我们得到Cov(X,Y) = b*V(X) 这个等式,代入讲义中ρ的公式两边取平方,ρ^2 = b^2 * V(X)/V(Y) = 1.2^2 * 0.04 / 0.26^2, 因此ρ = 0.923


1 个答案
已采纳答案

李坏_品职助教 · 2023年07月07日

嗨,从没放弃的小努力你好:


下面这个是β的计算(基础班讲义197页):

因为β=ρ*σY/σX,所以ρ=β*σX/σY。


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虽然现在很辛苦,但努力过的感觉真的很好,加油!

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