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Bootstrap Unit Root Tests for Heavy-Tailed Time Series

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Handbook of Computational and Numerical Methods in Finance

Abstract

We explore the applicability of bootstrap unit root tests to time series with heavy-tailed errors. The size and power of the tests are investigated using simulated data. Applications to financial time series are also presented. Two different bootstrap methods and the subsampling approach are compared. Conclusions on the optimal bootstrap parameters, the range of applicability, and the performance of the tests are presented.

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Author information

Authors and Affiliations

  1. Mathematics and Statistics, Utah State University, 3900 Old Main Hill, Logan, Utah, 84322-3900, USA

    Piotr Kokoszka & Andrejus Parfionovas

Authors
  1. Piotr Kokoszka
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  2. Andrejus Parfionovas
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Editor information

Editors and Affiliations

  1. Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, 93106, USA

    Svetlozar T. Rachev

  2. Department of Economics and Business Engineering, Universität Karlsruhe, D-76128, Karlsruhe, Germany

    Svetlozar T. Rachev

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Kokoszka, P., Parfionovas, A. (2004). Bootstrap Unit Root Tests for Heavy-Tailed Time Series. In: Rachev, S.T. (eds) Handbook of Computational and Numerical Methods in Finance. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8180-7_5

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  • DOI: https://doi.org/10.1007/978-0-8176-8180-7_5

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-6476-7

  • Online ISBN: 978-0-8176-8180-7

  • eBook Packages: Springer Book Archive

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