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On Adaptive Tail Index Estimation for Financial Return Models

Author

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  • Wagner, Niklas
  • Marsh, Terry

Abstract

Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the well-known Hill estimator is optimal only under iid draws from an exact Pareto model. We provide a small sample simulation study of recently suggested adaptive estimators under ARCH-type dependence. The Hill estimator's performance is found to be dominated by a ratio estimator. Dependence increases estimation error which can remain substantial even in larger data sets. As small sample bias is related to the magnitude of the tail index, recent standard applications may have overestimated (underestimated) the risk of assets with low (high) degrees of fat-tailedness.

Suggested Citation

  • Wagner, Niklas & Marsh, Terry, 2000. "On Adaptive Tail Index Estimation for Financial Return Models," Research Program in Finance, Working Paper Series qt2651k8f5, Research Program in Finance, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:rpfina:qt2651k8f5
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    Cited by:

    1. Mohammad Karimi & Marcel Voia, 2015. "Identifying extreme values of exchange market pressure," Empirical Economics, Springer, vol. 48(3), pages 1055-1078, May.
    2. Fasika Damte Haile & Susan Pozo, 2006. "Exchange Rate Regimes and Currency Crises: an Evaluation using Extreme Value Theory," Review of International Economics, Wiley Blackwell, vol. 14(4), pages 554-570, September.
    3. Wagner, Niklas & Marsh, Terry A., 2005. "Measuring tail thickness under GARCH and an application to extreme exchange rate changes," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 165-185, January.
    4. Haile, Fasika & Pozo, Susan, 2008. "Currency crisis contagion and the identification of transmission channels," International Review of Economics & Finance, Elsevier, vol. 17(4), pages 572-588, October.

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