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Prospect theory and narrow framing bias: Evidence from emerging markets

Author

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  • do Nascimento Junior, Arnaldo João
  • Klotzle, Marcelo Cabus
  • Brandão, Luiz Eduardo T.
  • Pinto, Antonio Carlos Figueiredo

Abstract

Using prospect theory, we analyzed the narrow framing bias in investment decisions in certain emerging countries: Brazil, China, Russia, Mexico and South Africa. In all cases, we empirically identified the predictive power of prospect theory for stock returns. We also found that the probability weighting function is the most important factor in this predictive power. The relationship between prospect theory and stock returns is different in each country and may be influenced by factors associated with cultural aspects.

Suggested Citation

  • do Nascimento Junior, Arnaldo João & Klotzle, Marcelo Cabus & Brandão, Luiz Eduardo T. & Pinto, Antonio Carlos Figueiredo, 2021. "Prospect theory and narrow framing bias: Evidence from emerging markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 90-101.
    • Handle: RePEc:eee:quaeco:v:80:y:2021:i:c:p:90-101
    DOI: 10.1016/j.qref.2021.01.016
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    References listed on IDEAS

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    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    3. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
    4. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Asset Prices," American Economic Review, American Economic Association, vol. 103(3), pages 623-628, May.
    5. Helga Fehr-Duda & Thomas Epper, 2012. "Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 567-593, July.
    6. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    7. Nicholas Barberis & Abhiroop Mukherjee & Baolian Wang, 2016. "Prospect Theory and Stock Returns: An Empirical Test," The Review of Financial Studies, Society for Financial Studies, vol. 29(11), pages 3068-3107.
    8. Andy C.W. Chui & Sheridan Titman & K.C. John Wei, 2010. "Individualism and Momentum around the World," Journal of Finance, American Finance Association, vol. 65(1), pages 361-392, February.
    9. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    10. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    11. Son, Nguyen Truong & Nguyen, Nhat Minh, 2019. "Prospect theory value and idiosyncratic volatility: Evidence from the Korean stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 21(C), pages 113-122.
    12. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    13. Zhong, Xiaoling & Wang, Junbo, 2018. "Prospect theory and corporate bond returns: An empirical study," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 25-48.
    14. Thomas Epper & Helga Fehr-Duda, 2012. "The missing link: unifying risk taking and time discounting," ECON - Working Papers 096, Department of Economics - University of Zurich, revised Oct 2018.
    15. Henry Stott, 2006. "Cumulative prospect theory's functional menagerie," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 101-130, March.
    16. George Wu & Richard Gonzalez, 1996. "Curvature of the Probability Weighting Function," Management Science, INFORMS, vol. 42(12), pages 1676-1690, December.
    17. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    18. Eun, Cheol S. & Wang, Lingling & Xiao, Steven C., 2015. "Culture and R2," Journal of Financial Economics, Elsevier, vol. 115(2), pages 283-303.
    19. Wang, Zhiqiang & Su, Bingbai & Coakley, Jerry & Shen, Zhe, 2018. "Prospect theory and IPO returns in China," Journal of Corporate Finance, Elsevier, vol. 48(C), pages 726-751.
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    More about this item

    Keywords

    Prospect theory; Narrow framing bias; Probability weighting function; Emerging markets; Stock returns;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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