Abstract

http://ssrn.com/abstract=2018824
 
 

References (26)



 


 



An Automatic Procedure for the Estimation of the Tail Index


Ricardo Gimeno


Bank of Spain

Clara I. Gonzalez


Foundation for Applied Economic Research (FEDEA)

March 2012

MPRA Paper No. 37023

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.

Number of Pages in PDF File: 24

Keywords: Tail Index, Hill estimator, Normality Test

JEL Classification: C10, C15, G19

working papers series


Download This Paper

Date posted: March 9, 2012  

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: http://ssrn.com/abstract=2018824 or http://dx.doi.org/10.2139/ssrn.2018824

Contact Information

Ricardo Gimeno
Bank of Spain ( email )
Madrid 28014
Spain
Clara I. Gonzalez (Contact Author)
Foundation for Applied Economic Research (FEDEA) ( email )
Madrid 28001
Spain
Feedback to SSRN


Paper statistics
Abstract Views: 672
Downloads: 59
Download Rank: 214,506
References:  26

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo7 in 0.203 seconds