The Generalized Extreme Value (GEV) Distribution, Implied Tail Index and Option Pricing

Sheri Marina Markose and Amadeo Alentorn ()

No 594, Economics Discussion Papers from University of Essex, Department of Economics

Abstract: Crisis events such as the 1987 stock market crash, the Asian Crisis and the bursting of the Dot-Com bubble have radically changed the view that extreme events in financial markets have negligible probability. This paper argues that the use of the Generalized Extreme Value (GEV) distribution to model the Risk Neutral Density (RND) function provides a flexible framework that captures the negative skewness and excess kurtosis of returns, and also delivers the market implied tail index of asset returns. We obtain an original analytical closed form solution for the Harrison and Pliska (1981) no arbitrage equilibrium price for the European option in the case of GEV asset returns. The GEV based option prices successfully remove the well known pricing bias of the Black-Scholes model. We explain how the implied tail index is efficacious at identifying the fat tailed behaviour of losses and hence the left skewness of the price RND functions, particularly around crisis events.

New Economics Papers: this item is included in nep-rmg
Date: 2005-04-25
View list of references View citations in EconPapers

Downloads: (external link)
http://www.essex.ac.uk/economics/discussion-papers/papers-text/dp594.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:esx:essedp:594

Ordering information: This working paper can be ordered from
Discussion Papers Administrator, Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, U.K.
http://www.essex.ac. ... /papers-request.shtm

Access Statistics for this paper

More papers in Economics Discussion Papers from University of Essex, Department of Economics
Contact information at EDIRC.
Series data maintained by Essex Economics Web Manager ().