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An Automatic Procedure for the Estimation of the Tail Index

MPRA Paper No. 37023

24 Pages Posted: 9 Mar 2012  

Ricardo Gimeno

Banco de España

Clara I. Gonzalez

Banco de España

Date Written: March 2012

Abstract

Extreme Value Theory is increasingly used in the modelling of financial time series. The non-normality of stock returns leads to the search for alternative distributions that allows skewness and leptokurtic behavior. One of the most used distributions is the Pareto Distribution because it allows non-normal behaviour, which requires the estimation of a tail index.

This paper provides a new method for estimating the tail index. We propose an automatic procedure based on the computation of successive nor- mality tests over the whole of the distribution in order to estimate a Gaussian Distribution for the central returns and two Pareto distributions for the tails. We find that the method proposed is an automatic procedure that can be computed without need of an external agent to take the decision, so it is clearly objective.

Keywords: Tail Index, Hill estimator, Normality Test

JEL Classification: C10, C15, G19

Suggested Citation

Gimeno, Ricardo and Gonzalez, Clara I., An Automatic Procedure for the Estimation of the Tail Index (March 2012). MPRA Paper No. 37023. Available at SSRN: https://ssrn.com/abstract=2018824 or http://dx.doi.org/10.2139/ssrn.2018824

Ricardo Gimeno

Banco de España ( email )

Madrid 28014
Spain

Clara I. Gonzalez (Contact Author)

Banco de España ( email )

Alcala 50
Madrid 28014
Spain

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