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Extreme risk interdependence

Author

Listed:
  • Polanski, Arnold
  • Stoja, Evarist

Abstract

We define tail interdependence as a situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multiinformation to quantify tail interdependence, decompose it into systemic and residual interdependence and measure the contribution of a constituent to the interdependence of a system. Further, we devise statistical procedures to test: a) tail independence, b) whether an empirical interdependence structure is generated by a theoretical model and c) symmetry of the interdependence structure in the tails. We outline some additional extensions and illustrate this framework by applying it to several datasets. JEL Classification: C12, C14, C52

Suggested Citation

  • Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    • Handle: RePEc:srk:srkwps:201612
    as

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    File URL: https://www.esrb.europa.eu//pub/pdf/wp/esrbwp12.en.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    co-exceedance; Kullback-Leibler divergence; multi-information; relative entropy; risk contribution; risk interdependence;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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