Co-Dependence of Extreme Events in High Frequency FX Returns

Evarist Stoja; Arnold Polanski

doi:10.1016/j.jimonfin.2014.02.001

Co-Dependence of Extreme Events in High Frequency FX Returns

Evarist Stoja, Arnold Polanski

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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.

Original language	English
Pages (from-to)	164-178
Number of pages	15
Journal	Journal of International Money and Finance
Volume	44
Early online date	19 Feb 2014
DOIs	https://doi.org/10.1016/j.jimonfin.2014.02.001
Publication status	Published - 1 Jun 2014

Keywords

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

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10.1016/j.jimonfin.2014.02.001

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Final published version, 1.2 MBLicence: CC BY

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Professor Evarist Stoja
- E.Stojabristol.acuk
- University of Bristol Business School - Professor of Finance
Person: Academic

Cite this

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title = "Co-Dependence of Extreme Events in High Frequency FX Returns",

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.",

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AU - Polanski, Arnold

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N2 - 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.

AB - 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.

KW - High Frequency Returns

KW - Distributional Characteristics

KW - Multidimensional Risk

KW - Dependence in Risk

KW - Extreme Risk Assessment

KW - Multidimensional Value at Risk

U2 - 10.1016/j.jimonfin.2014.02.001

DO - 10.1016/j.jimonfin.2014.02.001

M3 - Article (Academic Journal)

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VL - 44

SP - 164

EP - 178

JO - Journal of International Money and Finance

JF - Journal of International Money and Finance

ER -

Co-Dependence of Extreme Events in High Frequency FX Returns

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