Detecting structural changes in large portfolios

被引：3

作者：

Posch, Peter N. ^{[1
]}

Ullmann, Daniel ^{[1
]}

Wied, Dominik ^{[2
]}

机构：

[1] TU Dortmund Univ, Fac Business & Econ, D-44227 Dortmund, Germany

[2] Univ Cologne, Fac Business Econ & Social Sci, D-50923 Cologne, Germany

来源：

EMPIRICAL ECONOMICS | 2019年 / 56卷 / 04期

关键词：

Correlation; Structural change; Cluster analysis; Portfolio management; CLUSTER-ANALYSIS; HIERARCHICAL STRUCTURE; PRINCIPAL; CONSTANT; POINTS;

D O I：

10.1007/s00181-017-1392-5

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Model-free tests for constant parameters often fail to detect structural changes in high dimensions. In practice, this corresponds to a portfolio with many assets and a reasonable long time series. We reduce the dimensionality of the problem by looking at a compressed panel of time series obtained by cluster analysis and the principal components of the data. With this procedure, we can extend tests for constant correlation matrix from a sub-portfolio to whole indices, which we exemplify using a major stock index.

引用

页码：1341 / 1357

页数：17

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