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

Kutzker, Tim; Stark, Florian; Wied, Dominik

doi:10.1007/s00181-019-01811-4

Cited by 3 publications

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“…Bücher and Ruppert (2013) proposed a test for breaks in copula in the presence of general time dependencies. Kutzker et al (2019) considered a test for relevant changes in the copula. Recently, several tests for the constancy of certain dependence measures have also been developed.…”

Section: Introductionmentioning

confidence: 99%

Testing and dating structural changes in copula-based dependence measures

Stark

Otto

2020

Journal of Applied Statistics

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This paper is concerned with testing and dating structural breaks in the dependence structure of multivariate time series. We consider a cumulative sum (CUSUM) type test for constant copula-based dependence measures, such as Spearman's rank correlation and quantile dependencies. The asymptotic null distribution is not known in closed form and critical values are estimated by an i.i.d. bootstrap procedure. We analyze size and power properties in a simulation study under different dependence measure settings, such as skewed and fat-tailed distributions. To date break points and to decide whether two estimated break locations belong to the same break event, we propose a pivot confidence interval procedure. Finally, we apply the test to the historical data of ten large financial firms during the last financial crisis from 2002 to mid-2013.

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Section: Introductionmentioning

confidence: 99%

Testing and dating structural changes in copula-based dependence measures

Stark

Otto

2020

Journal of Applied Statistics

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Testing the correct specification of a system of spatial dependence models for stock returns

Kutzker,

Wied

2023

Empir Econ

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This paper provides two specification tests for the system of spatial autoregressive model of order m. We derive the theoretical limit distributions and show in a detailed Monte Carlo simulation study that the tests result in reasonable sized testing procedures with large power. In the empirical application, we analyze Euro Stoxx 50 returns in two different time spans, looking for insights how well models with different specifications of the spatial weighting matrices (local, country, industry and country-industry specific dependencies including interaction effects) fit to the data. The analyzes also demonstrate the ability of the tests to detect inaccurate Value-at-Risk forecasts.

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