Ontology type: schema:ScholarlyArticle
2019-04
AUTHORSPeter N. Posch, Daniel Ullmann, Dominik Wied
ABSTRACTModel-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... »
PAGES1341-1357
http://scigraph.springernature.com/pub.10.1007/s00181-017-1392-5
DOIhttp://dx.doi.org/10.1007/s00181-017-1392-5
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