Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62266 
Year of Publication: 
2000
Series/Report no.: 
SFB 373 Discussion Paper No. 2000,112
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
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.
Subjects: 
Normal Inverse Gaussian distribution
Bayesian Analysis
Markov Chain Monte Carlo
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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