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
Publisher:	Berlin : Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Subject:	Normal Inverse Gaussian distribution \| Bayesian Analysis \| Markov Chain Monte Carlo

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Series:	SFB 373 Discussion Paper ; 2000,112
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	723885109 [GVK] hdl:10419/62266 [Handle] RePEc:zbw:sfb373:2000112 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010310281