IDEAS home Printed from https://ideas.repec.org/a/spr/jecfin/v35y2011i2p164-180.html
   My bibliography  Save this article

The wisdom of the few or the wisdom of the many? An indirect test of the marginal trader hypothesis

Author

Listed:
  • Calvin Blackwell
  • Robert Pickford

Abstract

No abstract is available for this item.

Suggested Citation

  • Calvin Blackwell & Robert Pickford, 2011. "The wisdom of the few or the wisdom of the many? An indirect test of the marginal trader hypothesis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(2), pages 164-180, April.
  • Handle: RePEc:spr:jecfin:v:35:y:2011:i:2:p:164-180
    DOI: 10.1007/s12197-009-9092-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12197-009-9092-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s12197-009-9092-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rubinstein, Ariel, 1982. "Perfect Equilibrium in a Bargaining Model," Econometrica, Econometric Society, vol. 50(1), pages 97-109, January.
    2. Berg, Joyce & Forsythe, Robert & Nelson, Forrest & Rietz, Thomas, 2008. "Results from a Dozen Years of Election Futures Markets Research," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 80, pages 742-751, Elsevier.
    3. Ernst Fehr & Jean-Robert Tyran, 2005. "Individual Irrationality and Aggregate Outcomes," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 43-66, Fall.
    4. Camerer, Colin & Loewenstein, George & Weber, Martin, 1989. "The Curse of Knowledge in Economic Settings: An Experimental Analysis," Journal of Political Economy, University of Chicago Press, vol. 97(5), pages 1232-1254, October.
    5. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
    6. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 83-110, May.
    7. Kenneth Oliven & Thomas A. Rietz, 2004. "Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on an Electronic Futures Market," Management Science, INFORMS, vol. 50(3), pages 336-351, March.
    8. Calvin Blackwell, 2010. "Rational Expectations in the Classroom: A Learning Activity," Journal for Economic Educators, Middle Tennessee State University, Business and Economic Research Center, vol. 10(2), pages 1-6, Fall.
    9. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    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. Manahov, Viktor & Hudson, Robert & Hoque, Hafiz, 2015. "Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 85-98.

    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. Berg, Joyce E. & Rietz, Thomas A., 2019. "Longshots, overconfidence and efficiency on the Iowa Electronic Market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 271-287.
    2. Joyce E. Berg & John Geweke & Thomas A. Rietz, 2010. "Memoirs of an indifferent trader: Estimating forecast distributions from prediction markets," Quantitative Economics, Econometric Society, vol. 1(1), pages 163-186, July.
    3. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    4. Bin-Tzong Chie & Chih-Hwa Yang, 2021. "Efficiency of the Experimental Prediction Market: Public Information, Belief Evolution, and Personality Traits," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(4), pages 1-3.
    5. Siemroth, Christoph, 2014. "Why prediction markets work : The role of information acquisition and endogenous weighting," Working Papers 14-02, University of Mannheim, Department of Economics.
    6. Dai, Min & Jia, Yanwei & Kou, Steven, 2021. "The wisdom of the crowd and prediction markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 561-578.
    7. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    8. Joyce E. Berg & George R. Neumann & Thomas A. Rietz, 2009. "Searching for Google's Value: Using Prediction Markets to Forecast Market Capitalization Prior to an Initial Public Offering," Management Science, INFORMS, vol. 55(3), pages 348-361, March.
    9. Bialkowski, Jedrzej & Gottschalk, Katrin & Wisniewski, Tomasz Piotr, 2008. "Stock market volatility around national elections," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1941-1953, September.
    10. Ho Cheung Brian Lee & Jan Stallaert & Ming Fan, 2020. "Anomalies in Probability Estimates for Event Forecasting on Prediction Markets," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2077-2095, September.
    11. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
    12. Abraham Othman & Tuomas Sandholm, 2013. "The Gates Hillman prediction market," Review of Economic Design, Springer;Society for Economic Design, vol. 17(2), pages 95-128, June.
    13. 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.
    14. Berlemann, Michael & Vöpel, Henning, 2012. "Tournament incentives and asset price bubbles: Evidence from a field experiment," Economics Letters, Elsevier, vol. 115(2), pages 232-235.
    15. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    16. Wiesen, Taylor, 2023. "Aggregate earnings and market expectations in United States presidential election prediction markets," Advances in accounting, Elsevier, vol. 60(C).
    17. Forsell, Eskil & Viganola, Domenico & Pfeiffer, Thomas & Almenberg, Johan & Wilson, Brad & Chen, Yiling & Nosek, Brian A. & Johannesson, Magnus & Dreber, Anna, 2019. "Predicting replication outcomes in the Many Labs 2 study," Journal of Economic Psychology, Elsevier, vol. 75(PA).
    18. 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.
    19. Imlak Shaikh, 2019. "The U.S. Presidential Election 2012/2016 and Investors’ Sentiment: The Case of CBOE Market Volatility Index," SAGE Open, , vol. 9(3), pages 21582440198, July.
    20. Ackert, Lucy F. & Church, Bryan K. & Zhang, Ping, 2004. "Asset prices and informed traders' abilities: Evidence from experimental asset markets," Accounting, Organizations and Society, Elsevier, vol. 29(7), pages 609-626, October.

    More about this item

    Keywords

    Marginal Trader Hypothesis; Prediction Market; Prediction Contest; C9; D4; G1;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • G1 - Financial Economics - - General Financial Markets

    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:spr:jecfin:v:35:y:2011:i:2:p:164-180. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.