Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods.

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Year of publication:	2000
Authors:	Lillestøl, Jostein
Institutions:	Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät
Subject:	Normal Inverse Gaussian distribution \| Bayesian Analysis \| Markov Chain Monte Carlo

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Extent:	application/pdf
Series:	SFB 373 Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 2000,112
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010983473