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

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  • Lillestøl, Jostein

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.

Suggested Citation

  • Lillestøl, Jostein, 2000. "Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods," SFB 373 Discussion Papers 2000,112, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:2000112
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    Citations

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    Cited by:

    1. Lillestöl, Jostein, 2002. "Some crude approximation, calibration and estimation procedures for NIG-variates," SFB 373 Discussion Papers 2002,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Adam Misiorek & Rafal Weron, 2010. "Heavy-tailed distributions in VaR calculations," HSC Research Reports HSC/10/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. Szymon Borak & Adam Misiorek & Rafał Weron, 2010. "Models for Heavy-tailed Asset Returns," SFB 649 Discussion Papers SFB649DP2010-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Dominique Guegan & Julien Houdain, 2006. "Hedging tranches index products : illustration of model dependency," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179325, HAL.
    5. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    6. Dominique Guegan & Julien Houdain, 2006. "Hedging tranches index products : illustration of model dependency," Post-Print halshs-00179325, HAL.
    7. Weron, Rafał, 2004. "Computationally intensive Value at Risk calculations," Papers 2004,32, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    8. Sanjeena Subedi & Paul McNicholas, 2014. "Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(2), pages 167-193, June.

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