IDEAS home Printed from https://ideas.repec.org/a/eme/ijmfpp/ijmf-05-2017-0088.html
   My bibliography  Save this article

Does investor sentiment predict Mexican equity returns?

Author

Listed:
  • Daniel Liston-Perez
  • Patricio Torres-Palacio
  • Sidika Gulfem Bayram

Abstract

Purpose - The purpose of this paper is to test whether investor sentiment is a significant predictor of future Mexican stock market returns. It also estimates the dynamic correlation between investor sentiment and equity returns. Finally, it examines if investor sentiment innovations impact unexpected returns for a variety of portfolios. Design/methodology/approach - This study utilizes predictive regressions to determine if sentiment can predict Mexican equity returns. Multivariate GARCH models are estimated to examine the time-varying correlations between investor sentiment and equity returns. Findings - The results show that Mexican investor sentiment is a significant predictor of Mexican equity returns for up to 24 months ahead. The findings show that high levels of sentiment today are associated with lower equity returns over the near term. Furthermore, multivariate GARCH estimations indicate that the correlation between investor sentiment and equity returns is not static and varies considerably over time. Finally, the findings indicate that sentiment innovations are significantly correlated with unexpected returns, reinforcing the notion that unexplained sentiment fluctuations lead to unexplained changes in stock market returns. Overall, these results suggest that investor sentiment is a significant source of risk for the Mexican stock market. Originality/value - This study seeks to further our understanding of how behavioral factors influence and predict Mexican equity returns.

Suggested Citation

  • Daniel Liston-Perez & Patricio Torres-Palacio & Sidika Gulfem Bayram, 2018. "Does investor sentiment predict Mexican equity returns?," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 14(4), pages 484-502, May.
  • Handle: RePEc:eme:ijmfpp:ijmf-05-2017-0088
    DOI: 10.1108/IJMF-05-2017-0088
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/IJMF-05-2017-0088/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/IJMF-05-2017-0088/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1108/IJMF-05-2017-0088?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. Yousra Trichilli & Mouna Abdelhédi & Mouna Boujelbène Abbes, 2020. "The thermal optimal path model: Does Google search queries help to predict dynamic relationship between investor’s sentiment and indexes returns?," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 261-279, May.

    More about this item

    Keywords

    Mexico; Returns; Investor sentiment; Predictive regressions; G02; G12; G15; G40;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General

    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:eme:ijmfpp:ijmf-05-2017-0088. 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: Emerald Support (email available below). General contact details of provider: .

    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.