Applied Stochastic Models in Business and Industry · 2004 · 20 citations · 27 references
BusinessEconomicsFinanceBayesian Data AnalysisFinancial EconomicsFinancial ModelingBayesian EconometricsBayesian InferenceBayesian ModelingBayesian StatisticsMarkov Chain Monte CarloMonte Carlo SimulationBayesian Data AugmentationBayesian Density EstimationBayesian EstimationData AugmentationGibbs SamplingInverse Gaussian RegressionMarkov Chain Monte Carlo EstimationMixture Model
Abstract The normal inverse Gaussian (NIG) distribution is a promising alternative for modelling financial data since it is a continuous distribution that allows for skewness and fat tails. There is an increasing number of applications of the NIG distribution to financial problems. Due to the complicated nature of its density, estimation procedures are not simple. In this paper we propose Bayesian estimation for the parameters of the NIG distribution via an MCMC scheme based on the Gibbs sampler. Our approach makes use of the data augmentation provided by the mixture representation of the distribution. We also extend the model to allow for modelling heteroscedastic regression situations. Examples with financial and simulated data are provided. Copyright © 2004 John Wiley & Sons, Ltd.
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Bayes and Empirical Bayes Methods for Data Analysis.
Tom Leonard, Brad Carlin, Thomas A. Louis · Biometrics · 1997 · 790 citations