Bücher, AxelJäschke, StefanWied, Dominik2013-08-142013-08-142013-08-14http://hdl.handle.net/2003/3047910.17877/DE290R-5511The 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.enDiscussion Paper / SFB 823;28/2013Change-point detectionMultiplier bootstrapTail dependenceWeak convergence310330620Nonparametric tests for constant tail dependence with an application to energy and financeworking paper