Modeling and forecasting volatility in a bayesian approach

Esmail Amiri

A chapter in Maximum Simulated Likelihood Methods and Applications, 2010, pp 323-356 from Emerald Group Publishing Limited

Abstract: In a Bayesian approach, we compare the forecasting performance of five classes of models: ARCH, GARCH, SV, SV-STAR, and MSSV using daily Tehran Stock Exchange (TSE) market data. To estimate the parameters of the models, Markov chain Monte Carlo (MCMC) methods is applied. The results show that the models in the fourth and the fifth class perform better than the models in the other classes.

Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(2010)0000026014

DOI: 10.1108/S0731-9053(2010)0000026014

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