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Detecting departures from meta-ellipticity for multivariate stationary time series

Author

Listed:
  • Bücher Axel

    (Heinrich-Heine-University Düsseldorf)

  • Jaser Miriam

    (Technical University of Munich)

  • Min Aleksey

    (Technical University of Munich)

Abstract

A test for detecting departures from meta-ellipticity for multivariate stationary time series is proposed. The large sample behavior of the test statistic is shown to depend in a complicated way on the underlying copula as well as on the serial dependence. Valid asymptotic critical values are obtained by a bootstrap device based on subsampling. The finite-sample performance of the test is investigated in a large-scale simulation study, and the theoretical results are illustrated by a case study involving financial log returns.

Suggested Citation

  • Bücher Axel & Jaser Miriam & Min Aleksey, 2021. "Detecting departures from meta-ellipticity for multivariate stationary time series," Dependence Modeling, De Gruyter, vol. 9(1), pages 121-140, January.
    • Handle: RePEc:vrs:demode:v:9:y:2021:i:1:p:121-140:n:6
    DOI: 10.1515/demo-2021-0105
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    References listed on IDEAS

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