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Heavy tails and currency crises

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  • Hartmann, P.
  • Straetmans, S.
  • de Vries, C.G.

Abstract

In affine models of foreign exchange rate returns, the nature of cross sectional interdependence in crisis periods hinges on the tail properties of the fundamentals' distribution. If the fundamentals exhibit thin tails like the normal distribution, the dependence vanishes asymptotically; while the dependence remains in the case of heavy tailed fundamentals as in case of the Student-t distribution. The linearity of the monetary model and heavy tail distributed fundamentals are sufficient conditions for fundamentals-based repeated joint currency crises. An estimator for the extreme exchange rate interdependencies is obtained and applied to Western, Asian and Latin American currency block data.

Suggested Citation

  • Hartmann, P. & Straetmans, S. & de Vries, C.G., 2010. "Heavy tails and currency crises," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 241-254, March.
  • Handle: RePEc:eee:empfin:v:17:y:2010:i:2:p:241-254
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Tomas Fiala & Tomas Havranek, 2014. "Ailing Mothers, Healthy Daughters? Contagion in the Central European Banking Sector," Working Papers IES 2014/10, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2014.
    2. João Nicolau & Paulo M.M. Rodrigues, 2015. "A New Regression-Based Tail Index Estimator: An Application to Exchange Rates," Working Papers w201514, Banco de Portugal, Economics and Research Department.
    3. Charnchai Leuwattanachotinan & Casper G. de Vries, 2015. "Extreme Linkages in Financial Markets: Macro Shocks and Systemic Risk," PIER Discussion Papers 2., Puey Ungphakorn Institute for Economic Research, revised Sep 2015.
    4. Xiao, Weilin & Zhang, Weiguo & Zhang, Xili & Chen, Xiaoyan, 2014. "The valuation of equity warrants under the fractional Vasicek process of the short-term interest rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 320-337.
    5. van Oordt, Maarten R.C. & Zhou, Chen, 2012. "The simple econometrics of tail dependence," Economics Letters, Elsevier, vol. 116(3), pages 371-373.
    6. Qin, Xiao & Liu, Liya, 2014. "Extremes, return level and identification of currency crises," Economic Modelling, Elsevier, vol. 37(C), pages 439-450.
    7. Narcisa Kadlcakova & Lubos Komarek & Zlatuse Komarkova & Michal Hlavacek, 2016. "Identification of Asset Price Misalignments on Financial Markets With Extreme Value Theory," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(11), pages 2595-2609, November.
    8. Fiala, Tomas & Havranek, Tomas, 2017. "The sources of contagion risk in a banking sector with foreign ownership," Economic Modelling, Elsevier, vol. 60(C), pages 108-121.
    9. Maarten van Oordt & Chen Zhou, 2016. "Estimating Systematic Risk Under Extremely Adverse Market Conditions," Staff Working Papers 16-22, Bank of Canada.
    10. Polanski, Arnold & Stoja, Evarist, 2014. "Co-dependence of extreme events in high frequency FX returns," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 164-178.
    11. Sun, Pengfei & Zhou, Chen, 2014. "Diagnosing the distribution of GARCH innovations," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 287-303.

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