Co-Dependence of Extreme Events in High Frequency FX Returns

Evarist Stoja, Arnold Polanski

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
340 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)164-178
Number of pages15
JournalJournal of International Money and Finance
Early online date19 Feb 2014
Publication statusPublished - 1 Jun 2014


  • High Frequency Returns
  • Distributional Characteristics
  • Multidimensional Risk
  • Dependence in Risk
  • Extreme Risk Assessment
  • Multidimensional Value at Risk


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