IDEAS home Printed from https://ideas.repec.org/a/eee/dyncon/v167y2024ics0165188924001234.html
   My bibliography  Save this article

Estimation of expected return integrating real-time asset prices implied information and historical data

Author

Listed:
  • Wang, Shikun
  • Zhu, Shushang
  • Huang, Yi
  • Li, Zhongfei

Abstract

In this paper, we develop a novel estimation for expected stock returns combining forward-looking information implied by real-time asset prices and backward-looking information implied by historical data. Considering a general heterogeneous market composed of both informed investors and noise investors, we investigate the market equilibrium characterized by the expected returns, risk-neutral moments and market portfolio. To mitigate the negative impact of the market noise on the forward-looking information implied in market equilibrium, we then incorporate historical data and propose the combined estimation for expected return within a Bayesian framework. The combined estimation is adaptive to the market composition and adjustable to changes in market states. Monte Carlo simulations and empirical studies are performed to validate the merits of the proposed approach.

Suggested Citation

  • Wang, Shikun & Zhu, Shushang & Huang, Yi & Li, Zhongfei, 2024. "Estimation of expected return integrating real-time asset prices implied information and historical data," Journal of Economic Dynamics and Control, Elsevier, vol. 167(C).
  • Handle: RePEc:eee:dyncon:v:167:y:2024:i:c:s0165188924001234
    DOI: 10.1016/j.jedc.2024.104931
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165188924001234
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jedc.2024.104931?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.

    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:eee:dyncon:v:167:y:2024:i:c:s0165188924001234. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jedc .

    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.