An automatic procedure for the estimation of the tail index

Gimeno, Ricardo and Gonzalez, Clara I. (2012): An automatic procedure for the estimation of the tail index.

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 normality 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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Tail Index; Hill estimator; Normality Test
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; G - Financial Economics > G1 - General Financial Markets > G19 - Other; G - Financial Economics > G0 - General > G00 - General

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