IDEAS home Printed from https://ideas.repec.org/a/ris/iosalg/0035.html
   My bibliography  Save this article

Predictable markets? A news-driven model of the stock market

Author

Listed:
  • Gusev, Maxim

    (IBC Quantitative Strategies)

  • Kroujiline, Dimitri

    (LGT Capital Partners)

  • Govorkov, Boris

    (IBC Quantitative Strategies)

  • Sharov, Sergey V.

    (N.I. Lobachevsky State University)

  • Ushanov, Dmitry

    (Department of Mechanics and Mathematics)

  • Zhilyaev, Maxim

    (Mozilla Corporation)

Abstract

We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.

Suggested Citation

  • Gusev, Maxim & Kroujiline, Dimitri & Govorkov, Boris & Sharov, Sergey V. & Ushanov, Dmitry & Zhilyaev, Maxim, 2015. "Predictable markets? A news-driven model of the stock market," Algorithmic Finance, IOS Press, vol. 4(1-2), pages 5-51.
  • Handle: RePEc:ris:iosalg:0035
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Rameeza Andleeb & Arshad Hassan, 2023. "Impact of Investor Sentiment on Contemporaneous and Future Equity Returns in Emerging Markets," SAGE Open, , vol. 13(3), pages 21582440231, August.
    2. Kroujiline, Dimitri & Gusev, Maxim & Ushanov, Dmitry & Sharov, Sergey V. & Govorkov, Boris, 2015. "Forecasting stock market returns over multiple time horizons," MPRA Paper 66175, University Library of Munich, Germany.
    3. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    4. Dimitri Kroujiline & Maxim Gusev & Dmitry Ushanov & Sergey V. Sharov & Boris Govorkov, 2018. "An Endogenous Mechanism of Business Cycles," Papers 1803.05002, arXiv.org, revised Sep 2019.
    5. Karl Naumann-Woleske & Michael Benzaquen & Maxim Gusev & Dimitri Kroujiline, 2021. "Capital Demand Driven Business Cycles: Mechanism and Effects," Papers 2110.00360, arXiv.org, revised Sep 2022.

    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:ris:iosalg:0035. 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: Saskia van Wijngaarden (email available below). General contact details of provider: http://www.iospress.nl/ .

    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.