Detecting structural changes in large portfolios View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Peter N. Posch, Daniel Ullmann, Dominik Wied

ABSTRACT

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. More... »

PAGES

1341-1357

Journal

TITLE

Empirical Economics

ISSUE

4

VOLUME

56

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00181-017-1392-5

DOI

http://dx.doi.org/10.1007/s00181-017-1392-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100315031


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