IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v55y2019icp46-62.html
   My bibliography  Save this article

Investor sentiment and the price-earnings ratio in the G7 stock markets

Author

Listed:
  • Rahman, Md Lutfur
  • Shamsuddin, Abul

Abstract

Investment practitioners often interpret an excessively high price-earnings ratio as a reflection of an overvalued market fuelled by optimistic investor sentiment. We examine the role of investor sentiment in explaining the P/E ratio in the G7 countries. The results suggest that after controlling for the effects of fundamental factors, the P/E ratio generally increases with an improvement in investor sentiment. The robustness of the findings to the use of forward P/E ratios, alternative data frequency, and controlling for financial crises is checked. Furthermore, the results from quantile regressions reveal that the effects of investor sentiment vary across the P/E quantiles.

Suggested Citation

  • Rahman, Md Lutfur & Shamsuddin, Abul, 2019. "Investor sentiment and the price-earnings ratio in the G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 55(C), pages 46-62.
    • Handle: RePEc:eee:pacfin:v:55:y:2019:i:c:p:46-62
    DOI: 10.1016/j.pacfin.2019.03.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X18305560
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2019.03.003?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. Apergis, Nicholas, 2022. "Overconfidence and US stock market returns," Finance Research Letters, Elsevier, vol. 45(C).
    2. Ahmed, Walid M.A., 2020. "Stock market reactions to domestic sentiment: Panel CS-ARDL evidence," Research in International Business and Finance, Elsevier, vol. 54(C).
    3. van Eyden, Reneé & Gupta, Rangan & Nielsen, Joshua & Bouri, Elie, 2023. "Investor sentiment and multi-scale positive and negative stock market bubbles in a panel of G7 countries," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    4. Haritha P H & Abdul Rishad, 2020. "An empirical examination of investor sentiment and stock market volatility: evidence from India," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-15, December.
    5. Gao, Yang & Zhao, Chengjie & Wang, Yaojun, 2024. "Investor sentiment and stock returns: New evidence from Chinese carbon-neutral stock markets based on multi-source data," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 438-450.
    6. Peng, Kang-Lin & Wu, Chih-Hung & Lin, Pearl M.C. & Kou, IokTeng Esther, 2023. "Investor sentiment in the tourism stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    7. Dimitrios Kenourgios & Spyros Papathanasiou & Anastasia Christina Bampili, 2022. "On the predictive power of CAPE or Shiller’s PE ratio: the case of the Greek stock market," Operational Research, Springer, vol. 22(4), pages 3747-3766, September.
    8. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
    9. Li Shuangjie & Hu Xuefeng & Wang Liming, 2020. "Could the Stock Market Adjust Itself? An Empirical Study Based on Mean Reversion Theory," Journal of Systems Science and Information, De Gruyter, vol. 8(2), pages 97-115, April.
    10. Fu, Junhui & Wu, Xiang & Liu, Yufang & Chen, Rongda, 2021. "Firm-specific investor sentiment and stock price crash risk," Finance Research Letters, Elsevier, vol. 38(C).

    More about this item

    Keywords

    Price-earnings ratio; Consumer confidence; Business confidence; G7 stock markets;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:pacfin:v:55:y:2019:i:c:p:46-62. 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/pacfin .

    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.