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Co-dependence of Extreme Events in High Frequency FX Returns

Author

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  • Arnold Polanski

    (University of East Anglia)

  • Evarist Stoja

    (University of Bristol)

Abstract

In this paper, we investigate extreme events in high frequency, multivariate FX returns within a purposely built framework. We generalize univariate tests and concepts to multidimensional settings and employ these novel techniques for parametric and nonparametric analysis. In particular, we investigate and quantify the co-dependence of cross-sectional and intertemporal extreme events. We find evidence of the cubic law of extreme returns, their increasing and asymmetric dependence and of the scaling property of extreme risk in joint symmetric tails.

Suggested Citation

  • Arnold Polanski & Evarist Stoja, 2013. "Co-dependence of Extreme Events in High Frequency FX Returns," University of East Anglia Applied and Financial Economics Working Paper Series 040, School of Economics, University of East Anglia, Norwich, UK..
    • Handle: RePEc:uea:aepppr:2012_40
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    File URL: https://ueaeco.github.io/working-papers/papers/afe/UEA-AFE-040.pdf
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    References listed on IDEAS

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    Cited by:

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    2. Wu, Chih-Chiang & Chiu, Junmao, 2017. "Economic evaluation of asymmetric and price range information in gold and general financial markets," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 53-68.
    3. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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