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Filtering for partially observed diffusion and its applications

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  • Shoji, Isao

Abstract

This paper provides an analytic method of filtering for partially observed diffusions, which can be also used for parameter estimation with the quasi-maximum likelihood method. The filtering is shown to have consistency in a weak sense. In addition, using the stochastic volatility models, a comparative simulation study is carried out to see how well the proposed method numerically works. The performance of the proposed method is basically better than that of the extended Kalman filtering.

Suggested Citation

  • Shoji, Isao, 2013. "Filtering for partially observed diffusion and its applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4966-4976.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:20:p:4966-4976
    DOI: 10.1016/j.physa.2013.06.005
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    References listed on IDEAS

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    7. Paul Fearnhead & Omiros Papaspiliopoulos & Gareth O. Roberts, 2008. "Particle filters for partially observed diffusions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 755-777.
    8. Jones, Christopher S., 2003. "The dynamics of stochastic volatility: evidence from underlying and options markets," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 181-224.
    9. Bollerslev, Tim & Zhou, Hao, 2002. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 109(1), pages 33-65, July.
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