IDEAS home Printed from https://ideas.repec.org/a/idn/jimfjn/v9y2023i3ep465-490.html
   My bibliography  Save this article

Information Efficiency In The U.S. And Shariah-Complaint Stocks In Malaysia During Covid-19

Author

Listed:
  • Ooi Kok Loang

    (SEGi University, Malaysia)

Abstract

This study examines the impact of analysts’ forecast of market liquidity and information efficiency in the U.S (developed) and Malaysia (emerging – Shariah-compliant stocks) before and during COVID-19. The results show that the analysts’ forecast is significant to the market liquidity in the pre-COVID period but its influence diminishes during the COVID-19. Moreover, the impact of the analysts’ forecast is significant in the upper quantiles (0.7 and 0.9 quantiles) of the U.S market and in the lower quantiles (0.1 and 0.3 quantiles) of Malaysia's Islamic market. Similarly, the buy-sell recommendations in the U.S market and all variables forecasted are significant before COVID-19. Both markets become inefficient during COVID-19, and analysts’ forecast is no longer correlated to information efficiency. These results inform practitioners and investors to inspect the market conditions and investor's behavior under market stress such as COVID-19, which has disrupted the international financial markets.

Suggested Citation

  • Ooi Kok Loang, 2023. "Information Efficiency In The U.S. And Shariah-Complaint Stocks In Malaysia During Covid-19," Journal of Islamic Monetary Economics and Finance, Bank Indonesia, vol. 9(3), pages 465-490, September.
  • Handle: RePEc:idn:jimfjn:v:9:y:2023:i:3e:p:465-490
    DOI: https://doi.org/10.21098/jimf.v9i3.1509
    as

    Download full text from publisher

    File URL: https://jimf-bi.org/index.php/JIMF/article/view/1509/946
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.21098/jimf.v9i3.1509?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
    ---><---

    More about this item

    Keywords

    Analysts’ forecast; Market liquidity; Information efficiency; Investor behavior; COVID-19;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G4 - Financial Economics - - Behavioral Finance
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:idn:jimfjn:v:9:y:2023:i:3e:p:465-490. 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: Lutzardo Tobing or Jimmy Kathon (email available below). General contact details of provider: https://edirc.repec.org/data/bigovid.html .

    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.