Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

@article{Takaishi2014BayesianEO,
  title={Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm},
  author={Tetsuya Takaishi},
  journal={Journal of Physics: Conference Series},
  year={2014},
  volume={490},
  pages={012092}
}
  • T. Takaishi
  • Published 11 March 2014
  • Computer Science
  • Journal of Physics: Conference Series
The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient… 
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