IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v29y2025i2p147-175n1005.html
   My bibliography  Save this article

A Simulation and Empirical Study of the Maximum Likelihood Estimator for Stochastic Volatility Jump-Diffusion Models

Author

Listed:
  • Bégin Jean-François

    (Department of Statistics and Actuarial Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, British Columbia, Canada)

  • Boudreault Mathieu

    (Department of Mathematics, 14845 Université du Québec à Montréal , C.P. 8888, Succursale Centre-ville, H3C 3P8, Montréal, Québec, Canada)

Abstract

We investigate the behaviour of the maximum likelihood estimator (MLE) for stochastic volatility jump-diffusion models commonly used in financial risk management. A simulation study shows the practical conditions under which the MLE behaves according to theory. In an extensive empirical study based on nine indices and more than 6000 individual stocks, we nonetheless find that the MLE is unable to replicate key higher moments. We then introduce a moment-targeted MLE – robust to model misspecification – and revisit both simulation and empirical studies. We find it performs better than the MLE, improving the management of financial risk.

Suggested Citation

  • Bégin Jean-François & Boudreault Mathieu, 2025. "A Simulation and Empirical Study of the Maximum Likelihood Estimator for Stochastic Volatility Jump-Diffusion Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(2), pages 147-175.
    • Handle: RePEc:bpj:sndecm:v:29:y:2025:i:2:p:147-175:n:1005
    DOI: 10.1515/snde-2023-0028
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2023-0028
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2023-0028?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.

    More about this item

    Keywords

    maximum likelihood; jump-diffusion models; stochastic volatility; discrete nonlinear filtering; moment targeting;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:bpj:sndecm:v:29:y:2025:i:2:p:147-175:n:1005. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.