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Considering multivariate strongly mixing time series, nonparametric tests fora constant copula with specified or unspecified change point (candidate) arederived; the tests are consistent against general alternatives. A tapered blockmultiplier technique based on serially dependent multiplier random variables isprovided to estimate p-values of the test statistics. Size and power of thetests in finite samples are evaluated with Monte Carlo simulations. The blockmultiplier technique might have several other applications for statisticalinference on copulas of serially dependent data.

Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique