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The behavioural finance paradigm and the adaptive market hypothesis

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  • Zakhiyya Yousuf
  • Daniel Makina

Abstract

This study tests for the applicability of the Adaptive Market Hypothesis (AMH) and Bounded rationality theories on the Johannesburg Stock Exchange (JSE). This is in order to determine the influence of behavioural risk factors on the efficiency of the stock market. Behavioural theories show a gap in the theory of Efficient Market Hypothesis. Using quantile regression, our study established the applicability of the Adaptive Market Hypothesis on the JSE. Past market returns were shown to be significant in predicting future returns and thus did not follow a random walk. The lagged return increased at higher quantiles and differed with changes in market conditions (i.e. pre-financial crisis, financial crisis and post-financial crisis). Thus, the predictability of returns varies with a change in market conditions. This paper is focused on only on the Johannesburg stock exchange in South Africa, more specifically the movement is the all share index. The findings should be able to be applied to emerging and developed economies. Business confidence is found to have a negative relationship with returns showing a lag in time for sentiment to be incorporated in prices. In contrast, consumer confidence is found to have a positive relationship with returns. In summary, investors are shown to be influenced by fundamental and behavioural factors.

Suggested Citation

  • Zakhiyya Yousuf & Daniel Makina, 2022. "The behavioural finance paradigm and the adaptive market hypothesis," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 11(2), pages 34-48, April.
    • Handle: RePEc:rbs:ijfbss:v:11:y:2022:i:2:id:1761
    DOI: 10.20525/ijfbs.v11i2.1761
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    References listed on IDEAS

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    1. Lingjie Ma & Larry Pohlman, 2008. "Return forecasts and optimal portfolio construction: a quantile regression approach," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 409-425.
    2. 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.
    3. Werner De Bondt, 2020. "Investor and market overreaction: a retrospective," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 12(1), pages 11-20, May.
    4. Graham Smith & Aneta Dyakova, 2014. "African Stock Markets: Efficiency and Relative Predictability," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 258-275, June.
    5. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    6. Hiremath, Gourishankar S & Kumari, Jyoti, 2014. "Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India," MPRA Paper 58378, University Library of Munich, Germany.
    7. Pyemo N. Afego, 2015. "Market efficiency in developing African stock markets: what do we know?," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(1), pages 243-266, January-M.
    8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    9. Mlambo, Chipo & Biekpe, Nicholas, 2007. "The efficient market hypothesis: Evidence from ten African stock markets," MPRA Paper 25968, University Library of Munich, Germany, revised 2007.
    10. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
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