IDEAS home Printed from https://ideas.repec.org/a/taf/jnlbes/v29y2011i4p468-480.html
   My bibliography  Save this article

Sequential Bayesian Analysis of Time-Changed Infinite Activity Derivatives Pricing Models

Author

Listed:
  • Junye Li

Abstract

This article investigates time-changed infinite activity derivatives pricing models from the sequential Bayesian perspective. It proposes a sequential Monte Carlo method with the proposal density generated by the unscented Kalman filter. This approach overcomes to a large extent the particle impoverishment problem inherent to the conventional particle filter. Simulation study and real applications indicate that (1) using the underlying alone cannot capture the dynamics of states, and by including options, the precision of state filtering is dramatically improved; (2) the proposed method performs better and is more robust than the conventional one; and (3) joint identification of the diffusion, stochastic volatility, and jumps can be achieved using both the underlying data and the options data.

Suggested Citation

  • Junye Li, 2011. "Sequential Bayesian Analysis of Time-Changed Infinite Activity Derivatives Pricing Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 468-480, October.
    • Handle: RePEc:taf:jnlbes:v:29:y:2011:i:4:p:468-480
    DOI: 10.1198/jbes.2010.08310
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1198/jbes.2010.08310
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1198/jbes.2010.08310?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. Hanxue Yang & Juho Kanniainen, 2017. "Jump and Volatility Dynamics for the S&P 500: Evidence for Infinite-Activity Jumps with Non-Affine Volatility Dynamics from Stock and Option Markets," Review of Finance, European Finance Association, vol. 21(2), pages 811-844.
    2. Fulop, Andras & Heng, Jeremy & Li, Junye & Liu, Hening, 2022. "Bayesian estimation of long-run risk models using sequential Monte Carlo," Journal of Econometrics, Elsevier, vol. 228(1), pages 62-84.
    3. Michele Bianchi & Frank Fabozzi, 2015. "Investigating the Performance of Non-Gaussian Stochastic Intensity Models in the Calibration of Credit Default Swap Spreads," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 243-273, August.
    4. Peter Christoffersen & Christian Dorion & Kris Jacobs & Lotfi Karoui, 2014. "Nonlinear Kalman Filtering in Affine Term Structure Models," Management Science, INFORMS, vol. 60(9), pages 2248-2268, September.
    5. Michele Leonardo Bianchi & Svetlozar T. Rachev & Frank J. Fabozzi, 2018. "Calibrating the Italian Smile with Time-Varying Volatility and Heavy-Tailed Models," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 339-378, March.
    6. Jiling Cao & Xinfeng Ruan & Shu Su & Wenjun Zhang, 2021. "Specification analysis of VXX option pricing models under Lévy processes," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1456-1477, September.

    More about this item

    Statistics

    Access and download statistics

    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:taf:jnlbes:v:29:y:2011:i:4:p:468-480. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UBES20 .

    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.