Bayesian Analysis of Stochastic Volatility Models

@article{Jacquier1994BayesianAO,
  title={Bayesian Analysis of Stochastic Volatility Models},
  author={E. Jacquier and Nicholas G. Polson and Peter E. Rossi},
  journal={Journal of Business \& Economic Statistics},
  year={1994},
  volume={20},
  pages={69 - 87}
}
New techniques for the analysis of stochastic volatility models in which the logarithm of conditional variance follows an autoregressive model are developed. A cyclic Metropolis algorithm is used to construct a Markov-chain simulation tool. Simulations from this Markov chain coverage in distribution to draws from the posterior distribution enabling exact finite-sample inference. The exact solution to the filtering/smoothing problem of inferring about the unobserved variance states is a by… Expand
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