IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v08y2005i01ns0219024905002883.html
   My bibliography  Save this article

Bayesian Model Selection Via Filtering For A Class Of Micro-Movement Models Of Asset Price

Author

Listed:
  • MICHAEL A. KOURITZIN

    (Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta T6G 2G1, Canada)

  • YONG ZENG

    (Department of Mathematics and Statistics, University of Missouri at Kansas City, Kansas City, MO 64110, USA)

Abstract

This paper develops the Bayesian model selection based on Bayes factor for a rich class of partially-observed micro-movement models of asset price. We focus on one recursive algorithm to calculate the Bayes factors, first deriving the system of SDEs for them and then applying the Markov chain approximation method to yield a recursive algorithm. We prove the consistency (or robustness) of the recursive algorithm. To illustrate the construction of such a recursive algorithm, we consider a model selection problem for two micro-movement models with and without stochastic volatility, and provide simulation and real-data examples to demonstrate the effectiveness of the Bayes factor in the model selection for this class of models.

Suggested Citation

  • Michael A. Kouritzin & Yong Zeng, 2005. "Bayesian Model Selection Via Filtering For A Class Of Micro-Movement Models Of Asset Price," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 97-121.
    • Handle: RePEc:wsi:ijtafx:v:08:y:2005:i:01:n:s0219024905002883
    DOI: 10.1142/S0219024905002883
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024905002883
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219024905002883?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael A. Kouritzin, 2016. "Explicit Heston Solutions and Stochastic Approximation for Path-dependent Option Pricing," Papers 1608.02028, arXiv.org, revised Apr 2018.
    2. Kouritzin, Michael A., 2017. "Residual and stratified branching particle filters," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 145-165.
    3. Michael A. Kouritzin, 2018. "Explicit Heston Solutions And Stochastic Approximation For Path-Dependent Option Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-45, February.
    4. Zhiqiang Li & Jie Xiong, 2015. "Stability of the filter with Poisson observations," Statistical Inference for Stochastic Processes, Springer, vol. 18(3), pages 293-313, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijtafx:v:08:y:2005:i:01:n:s0219024905002883. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijtaf/ijtaf.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.