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Estimating a structural model of herd behavior in financial markets

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  • Marco Cipriani
  • Antonio Guarino

Abstract

We develop a new methodology for estimating the importance of herd behavior in financial markets. Specifically, we build a structural model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using 1995 stock market data for Ashland Inc., a company listed on the New York Stock Exchange. Herding occurs often and is particularly pervasive on certain days. In an information-event day, on average, 2 percent (4 percent) of informed traders herd-buy (sell). In 7 percent (11 percent) of information-event days, the proportion of informed traders who herd-buy (sell) is greater than 10 percent. Herding causes important informational inefficiencies, amounting, on average, to 4 percent of the asset's expected value.

Suggested Citation

  • Marco Cipriani & Antonio Guarino, 2012. "Estimating a structural model of herd behavior in financial markets," Staff Reports 561, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:561
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    References listed on IDEAS

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    1. Mathias Drehmann & Jörg Oechssler & Andreas Roider, 2005. "Herding and Contrarian Behavior in Financial Markets: An Internet Experiment," American Economic Review, American Economic Association, vol. 95(5), pages 1403-1426, December.
    2. Marco Cipriani & Antonio Guarino, 2009. "Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 206-233, March.
    3. Cipriani Marco & Guarino Antonio, 2008. "Herd Behavior and Contagion in Financial Markets," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 8(1), pages 1-56, October.
    4. Marco Cipriani & Antonio Guarino, 2005. "Herd Behavior in a Laboratory Financial Market," American Economic Review, American Economic Association, vol. 95(5), pages 1427-1443, December.
    5. Avery, Christopher & Zemsky, Peter, 1998. "Multidimensional Uncertainty and Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 88(4), pages 724-748, September.
    6. Andreas Park & Hamid Sabourian, 2011. "Herding and Contrarian Behavior in Financial Markets," Econometrica, Econometric Society, vol. 79(4), pages 973-1026, July.
    7. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets; A Review," IMF Working Papers 00/48, International Monetary Fund.
    8. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 805-835.
    9. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
    10. Chung, Kee H. & Li, Mingsheng & McInish, Thomas H., 2005. "Information-based trading, price impact of trades, and trade autocorrelation," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1645-1669, July.
    11. In Ho Lee, 1998. "Market Crashes and Informational Avalanches," Review of Economic Studies, Oxford University Press, vol. 65(4), pages 741-759.
    12. Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
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    Cited by:

    1. Marco Cipriani & Antonio Guarino, 2009. "Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 206-233, March.
    2. repec:eee:jetheo:v:176:y:2018:i:c:p:118-157 is not listed on IDEAS
    3. Xiong, Hang & Payne, Diane & Kinsella, Stephen, 2016. "Peer effects in the diffusion of innovations: Theory and simulation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 1-13.
    4. da Gama Batista, João & Massaro, Domenico & Bouchaud, Jean-Philippe & Challet, Damien & Hommes, Cars, 2017. "Do investors trade too much? A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 18-34.
    5. repec:eee:finsta:v:35:y:2018:i:c:p:172-191 is not listed on IDEAS
    6. repec:eee:phsmap:v:507:y:2018:i:c:p:335-346 is not listed on IDEAS
    7. Aymanns, Christoph & Georg, Co-Pierre, 2015. "Contagious synchronization and endogenous network formation in financial networks," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 273-285.
    8. Frey, Stefan & Herbst, Patrick & Walter, Andreas, 2014. "Measuring mutual fund herding – A structural approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 219-239.

    More about this item

    Keywords

    Financial markets ; Uncertainty ; Human behavior ; Information theory;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • 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

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