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

Jostein Lillestøl

No 2000,112, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

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.

Keywords: Normal Inverse Gaussian distribution; Bayesian Analysis; Markov Chain Monte Carlo (search for similar items in EconPapers)
Date: 2000
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