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Estimation of stable distributions by indirect inference

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Author Info
GARCIA, RenŽ
RENAULT, Eric
VEREDAS, David

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Abstract

This article deals with the estimation of the parameters of an -stable distribution by the indirect inference method with the skewed-t distribution as an auxiliary model. The latter distribution appears as a good candidate for an auxiliary model since it has the same number of parameters as the -stable distribution, with each parameter playing a similar role. To improve the properties of the estimator in finite sample, we use a variant of the method called Constrained Indirect Inference. In a Monte Carlo study, we show that this method delivers estimators with good properties in finite sample. In particular they are much more efficient than two other prevalent methods based on the characteristic function and the empirical quantiles. We provide an empirical application to hedge fund returns.

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Publisher Info
Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2006112.

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Date of creation: 01 Dec 2006
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Handle: RePEc:cor:louvco:2006112

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Related research
Keywords: stable distribution; indirect inference; constrained indirect inference; skewed-t distribution;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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