Nonparametric tests for constant tail dependence with an application to energy and finance
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Date
2013-08-14
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Abstract
The present paper proposes new tests for detecting structural breaks in the tail
dependence of multivariate time series using the concept of tail copulas. To obtain
asymptotic properties, we derive a new limit result for the sequential empirical tail
copula process. Moreover, consistency of both the tests and a change-point estimator
are proven. We analyze the finite sample behavior of the tests by Monte Carlo
simulations. Finally, and crucial from a risk management perspective, we apply the
new findings to datasets from energy and financial markets.
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Keywords
Change-point detection, Multiplier bootstrap, Tail dependence, Weak convergence