Adaptive filtering for stochastic volatility by using exact sampling

ShinIchi Aihara, Arunabha Bagchi, S. Saha

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    We study the sequential identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility is constructed. The systems parameters are sequentially estimated with the aid of parallel filtering algorithm. To improve the estimation performance for unknown parameters, the new resampling procedure is proposed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.
    Original languageUndefined
    Title of host publicationProceedings of the 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2013)
    PublisherSCITEPRESS
    Pages326-335
    Number of pages10
    ISBN (Print)978-989-8565-70-9
    DOIs
    Publication statusPublished - 2013
    Event10th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2013 - University of Reykjavik, Reykjavik, Iceland
    Duration: 29 Jul 201331 Jul 2013
    Conference number: 10
    http://www.icinco.org/?y=2013

    Publication series

    Name
    PublisherSciTePress
    Volume1

    Conference

    Conference10th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2013
    Abbreviated titleICINCO 2013
    CountryIceland
    CityReykjavik
    Period29/07/1331/07/13
    Internet address

    Keywords

    • EWI-24086
    • METIS-300213
    • IR-88293

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