Inference in Infinite Superpositions of Non-Gaussian Ornstein – Uhlenbeck Processes Using Bayesian Nonparametic Methods

@inproceedings{Griffin2010InferenceII,
  title={Inference in Infinite Superpositions of Non-Gaussian Ornstein – Uhlenbeck Processes Using Bayesian Nonparametic Methods},
  author={Jim E. Griffin},
  year={2010}
}
This paper describes a Bayesian nonparametric approach to volatility estimation. Volatility is assumed to follow a superposition of an infinite number of Ornstein–Uhlenbeck processes driven by a compound Poisson process with a parametric or nonparametric jump size distribution. This model allows a wide range of possible dependencies and marginal distributions for volatility. The properties of the model and prior specification are discussed, and a Markov chain Monte Carlo algorithm for inference… CONTINUE READING

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