An automatic procedure for the estimation of the tail index

Ricardo Gimeno and Clara Gonzalez

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Tail Index; Hill estimator; Normality Test (search for similar items in EconPapers)
JEL-codes: C10 C15 G00 G19 (search for similar items in EconPapers)
Date: 2012
New Economics Papers: this item is included in nep-ecm and nep-ets
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