Full bayesian inference for GARCH and EGARCH models
Date
2000Source
Journal of Business and Economic StatisticsVolume
18Issue
2Pages
187-198Google Scholar check
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A full Bayesian analysis of GARCH and EGARCH models is proposed consisting of parameter estimation, model selection, and volatility prediction. The Bayesian paradigm is implemented via Markov-chain Monte Carlo methodologies. We provide implementation details and illustrations using the General Index of the Athens stock exchange. © 2000 Taylor & Francis Group, LLC.