Institute of Information Theory and Automation

Publication details

Monte Carlo-based tail exponent estimator

Journal Article

Baruník Jozef, Vácha Lukáš


serial: Physica. A : Statistical Mechanics and its Applications vol.389, 21 (2010), p. 4863-4874

research: CEZ:AV0Z10750506

project(s): GA402/09/0965, GA ČR, GD402/09/H045, GA ČR, GP402/08/P207, GA ČR

keywords: Hill estimator, α-stable distributions, Tail exponent estimation

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abstract (eng):

In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals.

RIV: AH

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Last modification: 21.12.2012
Institute of Information Theory and Automation