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Herding in Financial Behaviour: A Behavioural and Neuroeconomic Analysis of Individual Differences

Author

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  • Baddeley, M.
  • Burke, C.
  • Schultz, W.
  • Tobler, P.

Abstract

Experimental analyses have identified significant tendencies for individuals to follow herd decisions, a finding which has been explained using Bayesian principles. This paper outlines the results from a herding task designed to extend these analyses using evidence from a functional magnetic resonance imaging (fMRI) study. Empirically, we estimate logistic functions using panel estimation techniques to quantify the impact of herd decisions on individuals' financial decisions. We confirm that there are statistically significant propensities to herd and that social information about others' decisions has an impact on individuals' decisions. We extend these findings by identifying associations between herding propensities and individual characteristics including gender, age and various personality traits. In addition fMRI evidence shows that individual differences correlate strongly with activations in the amygdala – an area of the brain commonly associated with social decision-making. Individual differences also correlate strongly with amygdala activations during herding decisions. These findings are used to construct a two stage least squares model of financial herding which confirms that individual differences and neural responses play a role in modulating the propensity to herd.

Suggested Citation

  • Baddeley, M. & Burke, C. & Schultz, W. & Tobler, P., 2012. "Herding in Financial Behaviour: A Behavioural and Neuroeconomic Analysis of Individual Differences," Cambridge Working Papers in Economics 1225, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1225
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    Cited by:

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    2. Saeed Ahmad Sabir & Hisham Bin Mohammad & Hanita Binti Kadir Shahar, 2019. "The Role of Overconfidence and Past Investment Experience in Herding Behaviour with a Moderating Effect of Financial Literacy: Evidence from Pakistan Stock Exchange," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(4), pages 480-490, April.
    3. Prince K Sarpong, 2014. "Against the Herd: Contrarian Investment Strategies on the Johannesburg Stock Exchange," Journal of Economics and Behavioral Studies, AMH International, vol. 6(2), pages 120-129.
    4. Leković Milјan, 2020. "Cognitive Biases as an Integral Part of Behavioral Finance," Economic Themes, Sciendo, vol. 58(1), pages 75-96, March.
    5. Jan René Judek, 2024. "Willingness to Use Algorithms Varies with Social Information on Weak vs. Strong Adoption: An Experimental Study on Algorithm Aversion," FinTech, MDPI, vol. 3(1), pages 1-11, January.

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    More about this item

    Keywords

    herding; social influence; individual differences; neuroeconomics; fMRI; amygdala;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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