Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/83431 
Year of Publication: 
2010
Series/Report no.: 
IES Working Paper No. 6/2010
Publisher: 
Charles University in Prague, Institute of Economic Studies (IES), Prague
Abstract: 
In this paper we study the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our method is not sensitive to the choice of k and works well also on small samples. The new estimator gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the main world stock market indices. On the two separate periods of 2002-2005 and 2006-2009 we estimate the tail exponent.
Subjects: 
Hill estimator
α-stable distributions
tail exponent estimation
JEL: 
C1
C13
C15
G0
Document Type: 
Working Paper

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