Quasi-exact Approximation of Hidden Markov Chain Filters
AbstractThis paper studies the application of exact simulation methods for multi-dimensional multiplicative noise stochastic differential equations to filtering. Stochastic differential equations with multiplicative noise naturally occur as Zakai equation in hidden Markov chain filtering. The paper proposes a quasi-exact approximation method for hidden Markov chain filters, which can be applied when discrete time approximations, such as the Euler scheme, may fail in practice.
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Bibliographic InfoPaper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 258.
Date of creation: 01 Oct 2009
Date of revision:
stochastic differential equations; Zakai equation; quasi-exact approximation; hidden Markov chain filtering;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-11-21 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Eckhard Platen & Lei Shi, 2008. "On the Numerical Stability of Simulation Methods for SDES," Research Paper Series 234, Quantitative Finance Research Centre, University of Technology, Sydney.
- P. Fischer & Eckhard Platen, 1999. "Applications of the Balanced Method to Stochastic Differential Equations in Filtering," Research Paper Series 16, Quantitative Finance Research Centre, University of Technology, Sydney.
- Nicola Bruti-Liberati & Eckhard Platen, 2008. "Strong Predictor-Corrector Euler Methods for Stochastic Differential Equations," Research Paper Series 222, Quantitative Finance Research Centre, University of Technology, Sydney.
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