IDEAS home Printed from https://ideas.repec.org/p/bgu/wpaper/2012.html
   My bibliography  Save this paper

Manipulation And (Mis)Trust In Prediction Markets

Author

Listed:
  • Lawrence Choo

    (Nuremberg Germany)

  • Todd R. Kaplan

    (Haifa)

  • Ro’i Zultan

    (BGU)

Abstract

Markets are increasingly used as information aggregation mechanisms to predict future events. If policy makers make use markets, parties may attempt to manipulate the market in order to influence decisions. We experimentally find that policymakers could still benefit from following information contained in market prices. Nonetheless, manipulation is detrimental. First, manipulators affect market prices, making them less informative. Second, when there are manipulators, policy makers often ignore - or even act against - the information revealed in market prices. Finally, mere suspicion of manipulation erodes trust in the market, leading to the implementation of suboptimal policies - even without actual manipulation.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2020. "Manipulation And (Mis)Trust In Prediction Markets," Working Papers 2012, Ben-Gurion University of the Negev, Department of Economics.
    • Handle: RePEc:bgu:wpaper:2012
    as

    Download full text from publisher

    File URL: http://in.bgu.ac.il/en/humsos/Econ/Workingpapers/2012.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    2. Jan Hansen & Carsten Schmidt & Martin Strobel, 2004. "Manipulation in political stock markets - preconditions and evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 11(7), pages 459-463.
    3. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    4. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    5. Hellwig, Martin F., 1982. "Rational expectations equilibrium with conditioning on past prices: A mean-variance example," Journal of Economic Theory, Elsevier, vol. 26(2), pages 279-312, April.
    6. Colin F. Camerer, 1998. "Can Asset Markets Be Manipulated? A Field Experiment with Racetrack Betting," Journal of Political Economy, University of Chicago Press, vol. 106(3), pages 457-482, June.
    7. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    8. 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.
    9. Cary Deck & David Porter, 2013. "Prediction Markets In The Laboratory," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 589-603, July.
    10. Hanson, Robin & Oprea, Ryan & Porter, David, 2006. "Information aggregation and manipulation in an experimental market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(4), pages 449-459, August.
    11. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    12. Helena Veiga & Marc Vorsatz, 2010. "Information aggregation in experimental asset markets in the presence of a manipulator," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 379-398, December.
    13. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    14. Paul J. Healy & Sera Linardi & J. Richard Lowery & John O. Ledyard, 2010. "Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders," Management Science, INFORMS, vol. 56(11), pages 1977-1996, November.
    15. 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.
    16. Boris Maciejovsky & David V. Budescu, 2020. "Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets," Organization Science, INFORMS, vol. 31(6), pages 1497-1514, November.
    17. Charles R. Plott, 2000. "Markets as Information Gathering Tools," Southern Economic Journal, John Wiley & Sons, vol. 67(1), pages 1-15, July.
    18. Veiga, Helena & Vorsatz, Marc, 2009. "Price manipulation in an experimental asset market," European Economic Review, Elsevier, vol. 53(3), pages 327-342, April.
    19. Radner, Roy, 1979. "Rational Expectations Equilibrium: Generic Existence and the Information Revealed by Prices," Econometrica, Econometric Society, vol. 47(3), pages 655-678, May.
    20. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    21. Dubey, Pradeep & Geanakoplos, John & Shubik, Martin, 1987. "The revelation of information in strategic market games : A critique of rational expectations equilibrium," Journal of Mathematical Economics, Elsevier, vol. 16(2), pages 105-137, April.
    22. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1309-1341.
    23. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    24. Deck, Cary & Lin, Shengle & Porter, David, 2013. "Affecting policy by manipulating prediction markets: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 48-62.
    25. Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
    26. Ahrash Dianat & Christoph Siemroth, 2021. "Correction to: Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 1074-1074, September.
    27. Philip Bond & Itay Goldstein, 2015. "Government Intervention and Information Aggregation by Prices," Journal of Finance, American Finance Association, vol. 70(6), pages 2777-2812, December.
    28. Brice Corgnet & Mark DeSantis & David Porter, 2015. "Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency," Working Papers 15-15, Chapman University, Economic Science Institute.
    29. repec:reg:rpubli:460 is not listed on IDEAS
    30. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    31. Benjamin J. Gillen & Charles R. Plott & Matthew Shum, 2017. "A Pari-Mutuel-Like Mechanism for Information Aggregation: A Field Test inside Intel," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1075-1099.
    32. Paul W. Rhode & Koleman S. Strumpf, 2004. "Historical Presidential Betting Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 127-141, Spring.
    33. repec:grz:wpsses:2019-01 is not listed on IDEAS
    34. Colin Camerer, 1998. "Can asset markets be manipulated? A field experiment with racetrack betting," Natural Field Experiments 00222, The Field Experiments Website.
    35. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marco Mantovani & Antonio Filippin, 2024. "When do prediction markets return average beliefs? Experimental evidence," Working Papers 532, University of Milano-Bicocca, Department of Economics.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    2. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    3. Galanis, S. & Ioannou, C. & Kotronis, S., 2019. "Information Aggregation Under Ambiguity: Theory and Experimental Evidence," Working Papers 20/05, Department of Economics, City University London.
    4. Boris Maciejovsky & David V. Budescu, 2020. "Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets," Organization Science, INFORMS, vol. 31(6), pages 1497-1514, November.
    5. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    6. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    7. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    8. Veiga, Helena & Vorsatz, Marc, 2008. "Aggregation and dissemination of information in experimental asset markets in the presence of a manipulator," DES - Working Papers. Statistics and Econometrics. WS ws084110, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    10. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    11. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    12. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    13. Dorina Tila & David Porter, 2008. "Group Prediction in Information Markets With and Without Trading Information and Price Manipulation Incentives," Working Papers 08-06, Chapman University, Economic Science Institute.
    14. Johan Almenberg & Ken Kittlitz & Thomas Pfeiffer, 2009. "An Experiment on Prediction Markets in Science," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-7, December.
    15. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    16. Paul J. Healy & Sera Linardi & J. Richard Lowery & John O. Ledyard, 2010. "Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders," Management Science, INFORMS, vol. 56(11), pages 1977-1996, November.
    17. Andrea Albertazzi & Friederike Mengel & Ronald Peeters, 2021. "Benchmarking information aggregation in experimental markets," Economic Inquiry, Western Economic Association International, vol. 59(4), pages 1500-1516, October.
    18. RYan Oprea & David Porter & Chris Hibbert & Robin Hanson & Dorina Tila, 2008. "Can Manipulators Mislead Prediction Market Observers?," Working Papers 08-01, Chapman University, Economic Science Institute.
    19. Peeters, R.J.A.P. & Wolk, K.L., 2014. "Eliciting and aggregating individual expectations: An experimental study," Research Memorandum 029, Maastricht University, Graduate School of Business and Economics (GSBE).
    20. Cary Deck & David Porter, 2013. "Prediction Markets In The Laboratory," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 589-603, July.

    More about this item

    Keywords

    prediction markets; policy; experiment;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bgu:wpaper:2012. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Aamer Abu-Qarn (email available below). General contact details of provider: https://edirc.repec.org/data/edbguil.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.