Corpus ID: 158848583

A Bayesian GED-Gamma stochastic volatility model for return data: a marginal likelihood approach

@article{Santos2018ABG,
  title={A Bayesian GED-Gamma stochastic volatility model for return data: a marginal likelihood approach},
  author={Thiago Rezende Dos Santos},
  journal={arXiv: Statistical Finance},
  year={2018}
}
  • T. R. Santos
  • Published 23 August 2018
  • Economics, Mathematics
  • arXiv: Statistical Finance
Several studies explore inferences based on stochastic volatility (SV) models, taking into account the stylized facts of return data. The common problem is that the latent parameters of many volatility models are high-dimensional and analytically intractable, which means inferences require approximations using, for example, the Markov Chain Monte Carlo or Laplace methods. Some SV models are expressed as a linear Gaussian state-space model that leads to a marginal likelihood, reducing the… Expand

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