Generalized Extreme Value distribution for fitting opening/closing asset prices and returns in stock-exchange

Abstract : Robust estimation of stock-exchange fluctuations is a challenging problem. The accuracy of statistical extrapolation is fairly sensitive to both model and sampling error. Using the opening/closing quotation and return data (concerning stock-exchange), this paper presents a comparative assessment using various theoretical distributions : Normal, LogNormal, Gamma, Gumbel, Weibull, Generalized Extreme Value (GEV). We used GEV distribution in an other context than extreme value theory (indeed dedicated to this domain). From the empirical distribution on short periods (3, 6, 9 and 12 months), we prove that GEV distribution allows to correctly fit returns and opening/closing quotations (without studying only the behaviour of maxima or minima in a sample, but overall of the sample) by comparison with the other distributions. This paper focuses on the GEV distribution in the univariate case. Following a review of the literature, univariate GEV distribution is applied to a series of daily stock-exchange of TOTAL oil company. We illustrate this article with the opening/closing quotations minus the moving average of the five last days and the returns of this company on short and medium terms (3, 6, 9, 12 months moving forward 1 month).
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https://hal-ujm.archives-ouvertes.fr/ujm-00105663
Contributor : Catherine Combes <>
Submitted on : Wednesday, October 11, 2006 - 6:45:26 PM
Last modification on : Friday, July 26, 2019 - 1:32:14 PM

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  • HAL Id : ujm-00105663, version 1

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Catherine Combes, Alain Dussauchoy. Generalized Extreme Value distribution for fitting opening/closing asset prices and returns in stock-exchange. Operational Research, Springer, 2006, 6 (1), pp.3-26. ⟨ujm-00105663⟩

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