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Modelling the distribution of the extreme share returns in Singapore

Author

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  • Tolikas, Konstantinos
  • Gettinby, Gareth D.

Abstract

This study aims to model the probability distribution of the extreme daily share returns in Singapore Stock Exchange over the period 1973 to 2005. For that reason the suitability of the Generalized Extreme Value (GEV), Generalized Pareto (GP) and Generalized Logistic (GL) distributions are investigated. The empirical results indicate that the GL distribution best fitted the empirical data over the period of study. Using the too much celebrated GEV and GP distributions for risk assessment could, therefore, lead to underestimation of the extreme risk which could potentially lead to inadequate protection against catastrophic losses.

Suggested Citation

  • Tolikas, Konstantinos & Gettinby, Gareth D., 2009. "Modelling the distribution of the extreme share returns in Singapore," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 254-263, March.
    • Handle: RePEc:eee:empfin:v:16:y:2009:i:2:p:254-263
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    Cited by:

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    2. Kerstens, Kristiaan & Mounir, Amine & de Woestyne, Ignace Van, 2011. "Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1190-1201, May.
    3. Tolikas, Konstantinos, 2014. "Unexpected tails in risk measurement: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 476-493.
    4. Christopher Lynch & Benjamin Mestel, 2019. "Change-Point Analysis Of Asset Price Bubbles With Power-Law Hazard Function," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-24, November.
    5. Santanu Dutta & Tushar Kanti Powdel, 2023. "Modeling Long Term Return Distribution and Nonparametric Market Risk Estimation," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 257-289, May.
    6. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".

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