IDEAS home Printed from https://ideas.repec.org/a/eee/glofin/v56y2023ics1044028322000837.html
   My bibliography  Save this article

Technical indicators and cross-sectional expected returns

Author

Listed:
  • Zeng, Hui
  • Marshall, Ben R.
  • Nguyen, Nhut H.
  • Visaltanachoti, Nuttawat

Abstract

This study shows that 14 widely documented technical indicators explain cross-sectional stock returns. These indicators have lower estimation errors than the three-factor Fama–French and historical mean models. The long-short portfolios based on the cross-sectional technical signals generate substantial excess returns. These remain consistent after controlling for well-known cross-sectional return determinants, including momentum, size, book-to-market ratio, investment, and profitability. Our findings suggest that technical indicators play an important role in determining variation in cross-sectional returns.

Suggested Citation

  • Zeng, Hui & Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2023. "Technical indicators and cross-sectional expected returns," Global Finance Journal, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:glofin:v:56:y:2023:i:c:s1044028322000837
    DOI: 10.1016/j.gfj.2022.100781
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1044028322000837
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.gfj.2022.100781?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

    Cross-sectional stock returns; Technical indicators; Three-factor Fama-French model; Cross-sectional expected return determinants;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:eee:glofin:v:56:y:2023:i:c:s1044028322000837. 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/inca/620162 .

    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.