IDEAS home Printed from https://ideas.repec.org/a/spt/apfiba/v9y2019i1f9_1_6.html
   My bibliography  Save this article

Investor Behavior Biases and Stock Market Reaction in Kenya

Author

Listed:
  • Irene Cherono
  • Tobias Olweny
  • Tabitha Nasieku

Abstract

A challenge to EMH is that individuals often overreact and underreact to news causing stock markets to react according to investor behaviour in their investment decision making. Generally, the study determined the effect of investor behaviour on stock market reaction of listed companies in Kenya. Specifically, the study determined the effect of investor herd behaviour on stock market reactions of listed companies in Kenya; determined the effect of investor loss aversion on stock market reactions of listed companies in Kenya; determined the effect of investor mental accounting on stock market reactions of listed companies in Kenya; and determined the effect of investor overconfidence on stock market reactions of listed companies in Kenya. The target population was 67 listed companies at the Nairobi Securities Exchange. A sample of 48 listed companies was used for analysis. Secondary data extracted from NSE historical data of listed companies for the period 2004 to 2016 was used for analysis. The study adopted quantitative research design. Panel data regression analysis model was used. The results indicated that herd behaviour did not have a significant effect on stock market reaction. However, loss aversion, mental accounting and overconfidence had significant effect on stock market reaction in Kenya. JEL classification numbers: C91, D03, D84Keywords: Herding Behaviour; Loss Aversion; Overconfidence; Mental Accounting; Overreaction; Stock Market Reaction; Under-reaction.

Suggested Citation

  • Irene Cherono & Tobias Olweny & Tabitha Nasieku, 2019. "Investor Behavior Biases and Stock Market Reaction in Kenya," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(1), pages 1-6.
  • Handle: RePEc:spt:apfiba:v:9:y:2019:i:1:f:9_1_6
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JAFB%2fVol%209_1_6.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9781107034662 is not listed on IDEAS
    2. Badi H. Baltagi & Espen Bratberg & Tor Helge Holmås, 2005. "A panel data study of physicians' labor supply: the case of Norway," Health Economics, John Wiley & Sons, Ltd., vol. 14(10), pages 1035-1045, October.
    3. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    4. Kent Daniel & David Hirshleifer, 2015. "Overconfident Investors, Predictable Returns, and Excessive Trading," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
    5. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    6. Simon Gächter & Eric J. Johnson & Andreas Herrmann, 2022. "Individual-level loss aversion in riskless and risky choices," Theory and Decision, Springer, vol. 92(3), pages 599-624, April.
    7. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    8. Boubaker Adel & Talbi Mariem, 2013. "The Impact of Overconfidence on Investors' Decisions," Business and Economic Research, Macrothink Institute, vol. 3(2), pages 53-75, December.
    9. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    10. Shefrin, Hersh, 2002. "Behavioral decision making, forecasting, game theory, and role-play," International Journal of Forecasting, Elsevier, vol. 18(3), pages 375-382.
    11. Shengle Lin, 2010. "Gradual Information Diffusion and Asset Price Momentum," Working Papers 10-04, Chapman University, Economic Science Institute.
    12. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    13. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    14. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    15. Nicholas Barberis & Ming Huang & Tano Santos, "undated". "Prospect Theory and Asset Prices," CRSP working papers 494, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    16. Nicholas Barberis & Ming Huang, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," Journal of Finance, American Finance Association, vol. 56(4), pages 1247-1292, August.
    17. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    18. Mobarek, Asma & Mollah, Sabur & Keasey, Kevin, 2014. "A cross-country analysis of herd behavior in Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 107-127.
    19. Brooks,Chris, 2014. "Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9781107661455, December.
    20. Chiang, Thomas C. & Zheng, Dazhi, 2010. "An empirical analysis of herd behavior in global stock markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1911-1921, August.
    21. Haroon Khan & Slim Hassairi & Jean-Laurent Viviani, 2011. "Herd behavior and market stress: The case of four European countries," Post-Print halshs-00657380, HAL.
    22. Die Wan & Ke Cheng & Xiaoguang Yang, 2014. "The reverse volatility asymmetry in Chinese financial market," Applied Financial Economics, Taylor & Francis Journals, vol. 24(24), pages 1555-1575, December.
    23. Nicholas Barberis & Ming Huang, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," NBER Working Papers 8190, National Bureau of Economic Research, Inc.
    24. Natividad Blasco & Pilar Corredor & Sandra Ferreruela, 2012. "Does herding affect volatility? Implications for the Spanish stock market," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 311-327, July.
    25. Philip Shane & Peter Brous, 2001. "Investor and (Value Line) Analyst Underreaction to Information about Future Earnings: The Corrective Role of Non‐Earnings‐Surprise Information," Journal of Accounting Research, Wiley Blackwell, vol. 39(2), pages 387-404, September.
    26. Utku Uygur & Oktay Taş, 2014. "The impacts of investor sentiment on returns and conditional volatility of international stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1165-1179, May.
    27. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    2. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    3. B. Luppi, 2005. "Prospect Theory and the Law of Small Numbers in the Evaluation of Asset Prices," Working Papers 539, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    5. Stracca, Livio, 2004. "Behavioral finance and asset prices: Where do we stand?," Journal of Economic Psychology, Elsevier, vol. 25(3), pages 373-405, June.
    6. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    7. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.
    8. Grinblatt, Mark & Han, Bing, 2001. "The Disposition Effect and Momentum," University of California at Los Angeles, Anderson Graduate School of Management qt6qg5d62p, Anderson Graduate School of Management, UCLA.
    9. Li An & Huijun Wang & Jian Wang & Jianfeng Yu, 2020. "Lottery-Related Anomalies: The Role of Reference-Dependent Preferences," Management Science, INFORMS, vol. 66(1), pages 473-501, January.
    10. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral finance," Papers 03-14, Sonderforschungsbreich 504.
    11. Syed Aliya Zahera & Rohit Bansal, 2018. "Do investors exhibit behavioral biases in investment decision making? A systematic review," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 10(2), pages 210-251, May.
    12. Ritika & Nawal Kishor, 2020. "Development and validation of behavioral biases scale: a SEM approach," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 14(2), pages 237-259, November.
    13. Itzhak Venezia, 2018. "Lecture Notes in Behavioral Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 10751, January.
    14. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    15. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    16. Ramiah, Vikash & Xu, Xiaoming & Moosa, Imad A., 2015. "Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 89-100.
    17. Yacine AÏT‐SAHALI & Michael W. Brandt, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, August.
    18. Uri Benzion & Yochanan Shachmurove & Joseph Yagil, 2004. "Subjective discount functions - an experimental approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(5), pages 299-311.
    19. Li, Yan & Yang, Liyan, 2013. "Prospect theory, the disposition effect, and asset prices," Journal of Financial Economics, Elsevier, vol. 107(3), pages 715-739.
    20. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.

    More about this item

    Keywords

    herding behaviour; loss aversion; overconfidence; mental accounting; overreaction; stock market reaction; under-reaction.;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

    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:spt:apfiba:v:9:y:2019:i:1:f:9_1_6. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    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.