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Measuring Tail Thickness under GARCH and an Application to Extremal Exchange Rate Changes

Author

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  • Wagner, Niklas
  • Marsh, Terry A.

Abstract

Accurate modeling of extremal price changes is vital to financial risk management. We examine the small sample properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and propose a model-based bias-corrected estimation approach. Our simulation results indicate that bias strongly relates to the underlying model and may be positively as well as negatively signed. The empirical study of daily exchange rate changes reveals substantial differences in measured tail-thickness due to small sample bias. As a consequence, high quantile estimation may lead to a substantial underestimation of tail risk.

Suggested Citation

  • Wagner, Niklas & Marsh, Terry A., 2003. "Measuring Tail Thickness under GARCH and an Application to Extremal Exchange Rate Changes," Research Program in Finance, Working Paper Series qt7pb301tr, Research Program in Finance, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:rpfina:qt7pb301tr
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    Cited by:

    1. Francq, Christian & Zakoïan, Jean-Michel, 2022. "Testing the existence of moments for GARCH processes," Journal of Econometrics, Elsevier, vol. 227(1), pages 47-64.

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