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 |
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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 | |
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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Dive into the research topics of 'Co-Dependence of Extreme Events in High Frequency FX Returns'. Together they form a unique fingerprint.Profiles
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Professor Evarist Stoja
- School of Accounting and Finance - Business School - Professor of Finance
Person: Academic