Inference for Lévy Driven Stochastic Volatility Models Via Adaptive Sequential Monte Carlo

@inproceedings{Jasra2008InferenceFL,
  title={Inference for L{\'e}vy Driven Stochastic Volatility Models Via Adaptive Sequential Monte Carlo},
  author={Ajay Jasra and David A. Stephens and Arnaud Doucet and Theodoros Tsagaris},
  year={2008}
}
In the following paper we investigate simulation and inference for a class Lévy driven stochastic volatility (SV) models. The model is comprised of a Heston type model ([22]) with an independent, additive, variance-Gamma process ([28]) in the returns equation. The infinite activity nature of the driving gamma process can capture the observed behaviour of many financial time series, and a discretized version, fit in a Bayesian manner, has been found to be very useful for modelling equity data… CONTINUE READING
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References

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A Bayesian analysis of return dynamics with Lévy jumps, Rev. Fin

H. Li, M. T. Wells, C. Yu
2008
View 5 Excerpts
Highly Influenced

Sequential Monte Carlo Methods in Practice

View 3 Excerpts
Highly Influenced

The expected auxiliary variable principle for Monte Carlo computation

C. Andrieu, A. Berthelsen, A. Doucet, G. O. Roberts
2009

Inference and model choice for sequentially ordered hidden Markov models

N. Chopin
J. R. Statist. Soc. B, • 2007
View 1 Excerpt

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