Multiple break detection in the correlation structure of financial returns
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Date
2011-09-07
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Abstract
Correlations between asset returns plays an important role in financial analysis.
More precisely, accurate estimates of the correlation between financial returns are
crucial in portfolio management. In particular, in periods of fi nancial crisis, extreme movements in asset prices are found to be more highly correlated than small movements.
It is precisely under these conditions that investors are extremely concerned
about changes on correlations. We propose a sequential procedure to detect the
number and position of multiple change points in the correlation structure of financial returns. It is shown analytically that the proposed algorithm asymptotically
gives the correct number of change points and the change points are consistently
estimated. It is also shown by simulation studies and by an empirical application
that the algorithm yields reasonable results.
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Keywords
Correlations, CUSUM statistics, Financial returns, Multiple change point detection, Sequential procedure