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Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression

Author

Listed:
  • Matthias Fischer

    (Lehrstuhl für Statistik und Ökonometrie, Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany)

  • Daniel Kraus

    (Zentrum Mathematik, Technische Universität München, Boltzmanstraße 3, 85748 Garching, Germany)

  • Marius Pfeuffer

    (Lehrstuhl für Statistik und Ökonometrie, Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany)

  • Claudia Czado

    (Zentrum Mathematik, Technische Universität München, Boltzmanstraße 3, 85748 Garching, Germany)

Abstract

Measuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors as covariates on other response sectors. We identify vine copula based quantile regression as an eligible tool for conducting such stress tests as this method has good robustness properties, takes into account potential nonlinearities of conditional quantile functions and ensures that no quantile crossing effects occur. We illustrate its performance by a data set of sector specific PDs for the German economy. Empirical results are provided for a rough and a fine-grained industry sector classification scheme. Amongst others, we confirm that a stressed automobile industry has a severe impact on the German economy as a whole at different quantile levels whereas, e.g., for a stressed financial sector the impact is rather moderate. Moreover, the vine copula based quantile regression approach is benchmarked against both classical linear quantile regression and expectile regression in order to illustrate its methodological effectiveness in the scenarios evaluated.

Suggested Citation

  • Matthias Fischer & Daniel Kraus & Marius Pfeuffer & Claudia Czado, 2017. "Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression," Risks, MDPI, vol. 5(3), pages 1-13, July.
    • Handle: RePEc:gam:jrisks:v:5:y:2017:i:3:p:38-:d:105140
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    References listed on IDEAS

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    Cited by:

    1. David E. Allen & Michael McAleer & Abhay K. Singh, 2017. "Risk Measurement and Risk Modelling Using Applications of Vine Copulas," Sustainability, MDPI, vol. 9(10), pages 1-34, September.
    2. Lubomira Gertler & Kristina Janovicova-Bognarova & Lukas Majer, 2020. "Explaining Corporate Credit Default Rates with Sector Level Detail," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(2), pages 96-120, August.

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