Testing for structural changes in large portfolios

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 a compressed panel of time series obtained by cluster analysis and the principal components of the data. Using our methodology we are able to extend a test for a constant correlation matrix from a sub portfolio to whole indices and exemplify the procedure with the EuroStoxx index.