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Catch me if you can. Can human observers identify insiders in asset markets?

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  • Stöckl, Thomas
  • Palan, Stefan

Abstract

Securities regulators around the globe face the challenge of identifying trades based on privileged information. We study human observers’ ability to identify informed traders and investigate which trading patterns are indicative of informed trading using experimental asset markets. We furthermore test how the behavioral response of informed traders to the threat of detection and punishment impacts observers’ detection abilities. We find that market trading data carries information which correlates with informed trading activity. Observers partly succeed in recognizing and using this information to identify informed traders.

Suggested Citation

  • Stöckl, Thomas & Palan, Stefan, 2018. "Catch me if you can. Can human observers identify insiders in asset markets?," Journal of Economic Psychology, Elsevier, vol. 67(C), pages 1-17.
    • Handle: RePEc:eee:joepsy:v:67:y:2018:i:c:p:1-17
    DOI: 10.1016/j.joep.2018.04.004
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    1. Schnitzlein, Charles R, 1996. "Call and Continuous Trading Mechanisms under Asymmetric Information: An Experimental Investigation," Journal of Finance, American Finance Association, vol. 51(2), pages 613-636, June.
    2. Martin Barner & Francesco Feri & Charles R. Plott, 2005. "On the microstructure of price determination and information aggregation with sequential and asymmetric information arrival in an experimental asset market," Annals of Finance, Springer, vol. 1(1), pages 73-107, January.
    3. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    4. Bloomfield, Robert & O'Hara, Maureen & Saar, Gideon, 2005. "The "make or take" decision in an electronic market: Evidence on the evolution of liquidity," Journal of Financial Economics, Elsevier, vol. 75(1), pages 165-199, January.
    5. Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-698, August.
    6. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    7. Kirchler, Michael, 2009. "Underreaction to fundamental information and asymmetry in mispricing between bullish and bearish markets. An experimental study," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 491-506, February.
    8. Pierre Collin-Dufresne & Vyacheslav Fos, 2015. "Do Prices Reveal the Presence of Informed Trading?," Journal of Finance, American Finance Association, vol. 70(4), pages 1555-1582, August.
    9. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    10. Jürgen Huber & Martin Angerer & Michael Kirchler, 2011. "Experimental asset markets with endogenous choice of costly asymmetric information," Experimental Economics, Springer;Economic Science Association, vol. 14(2), pages 223-240, May.
    11. Charles R. Schnitzlein, 2002. "Price Formation and Market Quality When the Number and Presence of Insiders Is Unknown," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1077-1109.
    12. Campbell, Joseph & LaMaster, Shawn & Smith, Vernon L & Van Boening, Mark, 1991. "Off-Floor Trading, Disintegration, and the Bid-Ask Spread in Experimental Markets," The Journal of Business, University of Chicago Press, vol. 64(4), pages 495-522, October.
    13. Nasser Arshadi, 1998. "Insider Trading Liability and Enforcement Strategy," Financial Management, Financial Management Association, vol. 27(2), Summer.
    14. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    15. Stöckl, Thomas & Kirchler, Michael, 2014. "Trading behavior and profits in experimental asset markets with asymmetric information," Journal of Behavioral and Experimental Finance, Elsevier, vol. 2(C), pages 18-30.
    16. Antoine J. BRUGUIER & Steven R. QUARTZ & Peter BOSSAERTS, 2010. "Exploring the Nature of 'Trader Intuition'," Swiss Finance Institute Research Paper Series 10-02, Swiss Finance Institute.
    17. Antoine J. Bruguier & Steven R. Quartz & Peter Bossaerts, 2010. "Exploring the Nature of “Trader Intuition”," Journal of Finance, American Finance Association, vol. 65(5), pages 1703-1723, October.
    18. Philipp Hornung & Ulrike Leopold-Wildburger & Roland Mestel & Stefan Palan, 2015. "Insider behavior under different market structures: experimental evidence on trading patterns, manipulation, and profitability," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(2), pages 357-373, June.
    19. Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
    20. Palan, Stefan & Stöckl, Thomas, 2017. "When chasing the offender hurts the victim: The case of insider legislation," Journal of Financial Markets, Elsevier, vol. 35(C), pages 104-129.
    21. Pierre Collin-Dufresne & Vyacheslav Fos, 2013. "Do Prices Reveal the Presence of Informed Trading?," Swiss Finance Institute Research Paper Series 13-69, Swiss Finance Institute, revised Sep 2015.
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    Cited by:

    1. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    2. Robert Merl, 2021. "Literature Review of Experimental Asset Markets with Insiders," Working Paper Series, Social and Economic Sciences 2021-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    3. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

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    More about this item

    Keywords

    Insider regulation; Insider detection; Asset market; Experiment;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • 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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