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Extreme risk interdependence

Author

Listed:
  • Polanski, Arnold

    (University of East Anglia)

  • Stoja, Evarist

    (University of Bristol)

Abstract

Tail interdependence is defined as the situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multi-information to quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part 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. The application of this approach to multidimensional financial data confirms some known and uncovers new stylized facts on extreme returns.

Suggested Citation

  • Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    • Handle: RePEc:boe:boeewp:0563
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    Cited by:

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    2. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).

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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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