Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/13340
Title: capturing extremes
Authors: Tolikas, K
Keywords: extreme Value Theory;probability Weighted Moments;Anderson-Darling goodness of fit test;Generalised Extreme Value distribution;Generalised Logistic distribution
Issue Date: 2008
Citation: Proceedings of The World Congress on Engineering, (2008) vol. 2
Abstract: The ability of the Generalised Extreme Value and Generalised Logistic distributions to describe adequately extreme financial returns is examined. The empirical results strongly reject the Generalised Extreme Value in favour of the fatter tailed Generalised Logistic. This implies that risk measurements which are based on the Generalised Extreme Value may underestimate risk since it assigns lower probabilities to the really ruinous events located deep into the tails of the returns distribution.
URI: https://bura.brunel.ac.uk/handle/2438/13340
Appears in Collections:Dept of Economics and Finance Research Papers

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