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Traditional or behavioral finance?

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  • Bozhidar Nedev

Abstract

The main differences between the neoclassical financial theory and behavioural finance are presented. They include the concept of rational economic agents, the notion of objective probability, the capital asset pricing models, the portfolio theory and the efficient market hypothesis. The theory of expected utility and the prospect theory are the most distinguished scientific achievements in conventional and behavioural finance respectively. The theoretical assumptions and the practical implementations, on which they are built, are summarized. The psychological effects, determining the decision making process of economic agents in uncertainty, are alleged and compared to the notions of the normative theory. The two different viewpoints of the two opposing fields in finance are presented with regard to the financial markets and instruments, the decisions made by investors and the portfolios constructed by them.

Suggested Citation

  • Bozhidar Nedev, 2018. "Traditional or behavioral finance?," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 113-134.
    • Handle: RePEc:bas:econth:y:2018:i:3:p:113-134
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    References listed on IDEAS

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    1. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    2. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    3. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    4. Adam Szyszka, 2013. "Behavioral Finance and Capital Markets," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-36629-0, December.
    5. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 127-151, June.
    6. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    7. Shefrin, Hersh, 2008. "A Behavioral Approach to Asset Pricing," Elsevier Monographs, Elsevier, edition 2, number 9780123743565.
    8. Grether, David M & Plott, Charles R, 1979. "Economic Theory of Choice and the Preference Reversal Phenomenon," American Economic Review, American Economic Association, vol. 69(4), pages 623-638, September.
    9. 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.
    10. Nagel, Stefan, 2005. "Short sales, institutional investors and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 78(2), pages 277-309, November.
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    Cited by:

    1. Ivanka Mihaylova, 2022. "Workplace Conflict: Evidence from Bulgaria," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 115-136.

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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • 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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