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cenwandada · 2024年07月28日

这道题可以详细介绍一下吗,考点是啥

NO.PZ2023100703000064

问题如下:

Risk analyst uses data from the HS300 index over the past 260 weeks to estimate the long-term average correlation of the common stocks and mean reverting rate. And find the average long-term stock correlation of the HS 300 Index is 22%, and the regression output estimates the following regression relationship: Y = 0.34-0.55X. Assume that in first week of March 2020, the average weekly correlation of all HS300 stocks was 65%. Based on the mean reverting rate in regression analysis, what is the estimated one-week autocorrelation?

选项:

A.0.219

B.0.23

C.0.35

D.0.45

解释:

To find the estimated one-week autocorrelation based on the mean reverting process, we can use the following formula:



单期自相关率+均值回归率=1,所以自相关率只要拿1减去均值回归率,即1-0.55=0.45

这道题可以详细介绍一下吗,考点是啥

1 个答案

pzqa27 · 2024年07月29日

嗨,努力学习的PZer你好:




要解决这个问题,我们需要理解如何使用回归输出基于均值回复来估计一周的自相关性。


给定数据

  • 长期平均股票相关性 (ρ): 22% (或 0.22)
  • 回归方程: Y=0.34−0.55XY = 0.34 - 0.55XY=0.34−0.55X
  • 2020年3月第一周的初始周度相关性 (ρ0​): 65% (或 0.65)


均值复归

在这种情况下,均值复归意味着相关性将随着时间推移回归到其长期平均值。回归为我们提供了当前相关性与未来相关性之间关系的信息。

回归方程是: Y=0.34−0.55X

这里,Y代表未来的相关性值,而 X 代表当前的相关性值。

回归方程中 X 的系数给出了均值回复率。在这种情况下,它是 −0.55。这可以解释为:如果相关性高于长期平均值,它将趋于减少;如果低于平均值,它将趋于增加。


估计一周自相关性

要估计一周的自相关性,我们需要理解当前周的相关性与下周相关性的关系。可以从均值回复率推导出一周的自相关性 (α)。

由于均值回复模型是: ρt+1=αρt+(1−α)ρ

我们从回归中知道: ρt+1=0.34−0.55ρt

我们可以将其与均值回复模型形式进行比较: α=1−0.55 α=0.45

因此,估计的一周自相关性为:

α=0.45

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