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Modelling the distribution of the extreme share returns in Singapore

Konstantinos Tolikas and Gareth D. Gettinby

Journal of Empirical Finance, 2009, vol. 16, issue 2, 254-263

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.

Keywords: Extreme; share; returns; Risk; measurement; Generalized; Logistic; distribution; Generalized; Extreme; Value; distribution; L-moments; Probability; Weighted; Moments (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:16:y:2009:i:2:p:254-263

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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