IDEAS home Printed from https://ideas.repec.org/a/eme/qrfmpp/qrfm-03-2017-0015.html
   My bibliography  Save this article

Determinants of overconfidence bias in Indian stock market

Author

Listed:
  • Priya Kansal
  • Seema Singh

Abstract

Purpose - The purpose of this paper is to conduct an exploratory analysis of the demographic factors and investors’ characteristics, which cause changes in the extent of overconfidence level and its constituents among the individuals. Design/methodology/approach - A survey has been conducted to explore the determinants of overconfidence and its constituents with the help of a well-structured close-ended questionnaire. The four constituents of overconfidence considered for the study are “better than average effect,” “planning fallacy,” “self-attribution” and “positive illusion.” The collected data are analyzed with the help oft-test, ANOVA and standard ordinary least square regression. Findings - The results show that those who earn high, have more dependents, share the earning responsibility, have high investment frequency, less time horizon and more investment experience and invest in large cap stocks are more subject to the overconfidence. The study also concludes that gender, age and general education do not affect the level of overconfidence. Research limitations/implications - The results of the study are useful for the market regulators, financial educators, stock market advisors and individual investors in avoiding costly investment mistakes, especially when transiting from one category of demographic and investment characteristics to another category of demographic and investment characteristics. Originality/value - The study is unique in itself, as it contributes an instrument to quantify the level of overconfidence among the individual investors. Moreover, the study attempts to explore the impact of all demographic and investment characteristics in one go, which makes it a valuable contribution in the existing literature.

Suggested Citation

  • Priya Kansal & Seema Singh, 2018. "Determinants of overconfidence bias in Indian stock market," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 10(4), pages 381-394, October.
  • Handle: RePEc:eme:qrfmpp:qrfm-03-2017-0015
    DOI: 10.1108/QRFM-03-2017-0015
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/QRFM-03-2017-0015/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/QRFM-03-2017-0015/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/QRFM-03-2017-0015?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. Esra Alp Coşkun & Hakan Kahyaoglu & Chi Keung Marco Lau, 2023. "Which return regime induces overconfidence behavior? Artificial intelligence and a nonlinear approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-34, December.
    2. Cui, Xin & Sensoy, Ahmet & Nguyen, Duc Khuong & Yao, Shouyu & Wu, Yiyao, 2022. "Positive information shocks, investor behavior and stock price crash risk," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 493-518.
    3. Jitender Kumar & Neha Prince, 2022. "Overconfidence bias in the Indian stock market in diverse market situations: an empirical study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 3031-3047, December.

    More about this item

    Keywords

    Overconfidence; Demographic variables; Investment characteristics; Planning fallacy; Positive illusion; Self-attribution; G02; G11; J10;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - 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:qrfmpp:qrfm-03-2017-0015. 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.