Testing for relevant dependence change in financial data: a CUSUM copula approach

Tim Kutzker (), Florian Stark () and Dominik Wied
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Tim Kutzker: University of Cologne
Florian Stark: University of Cologne

Empirical Economics, 2021, vol. 60, issue 4, No 10, 1875-1894

Abstract: Abstract We propose a new nonparametric test for detecting relevant breaks in copula functions. We assume that the data is driven by two non-equal copulas $$C_1$$ C 1 and $$C_2$$ C 2 . Under the null hypothesis, the copula difference within an appropriate norm is smaller than a certain positive adjustable threshold $$\varDelta $$ Δ . Within the alternative hypothesis, the copula difference exceeds the fixed value $$\varDelta $$ Δ . The test is based on a cumulative sum approach of the empirical copula with sequentially estimated marginals. We propose a bootstrap procedure to compute critical values. The Monte Carlo simulation indicates that the test results in a reasonable sized and powered testing procedure. A real data application of the DAX30 up to cross-sectional dimension $$N=30$$ N = 30 shows the test’s ability to detect relevant break points.

Keywords: Relevant change; Copula; Break testing; Bootstrap; CUSUM (search for similar items in EconPapers)
JEL-codes: C12 C13 C32 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00181-019-01811-4

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