English, Article, Journal or magazine article edition: Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models Jean-Francois Richard; Roman Liesenfeld

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Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models
Author
  • Jean-Francois Richard
  • Roman Liesenfeld
Physical Description
  • preprint
Notes
  • In this paper, Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as well as simulation smoothing where the latent volatilities are sampled at once. Based on this EIS simulation smoother a Bayesian Markov Chain Monte Carlo (MCDC) posterior analysis of the parameters of SV models can be performed.
  • RePEc:pit:wpaper:322
Language
  • English
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