IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v60y2014i10p2509-2524.html
   My bibliography  Save this article

Information Aggregation and Allocative Efficiency in Smooth Markets

Author

Listed:
  • Krishnamurthy Iyer

    (School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853)

  • Ramesh Johari

    (Department of Management Science and Engineering, Stanford University, Stanford, California 94305)

  • Ciamac C. Moallemi

    (Graduate School of Business, Columbia University, New York, New York 10027)

Abstract

Recent years have seen extensive investigation of the information aggregation properties of markets. However, relatively little is known about conditions under which a market will aggregate the private information of rational risk-averse traders who optimize their portfolios over time; in particular, what features of a market encourage traders to ultimately reveal their private information through trades? We consider a market model involving finitely many informed risk-averse traders interacting with a market maker. Our main result identifies a basic asymptotic smoothness condition on prices in the market that ensures information is aggregated as long as portfolios converge; furthermore, under this assumption, the allocation achieved is ex post Pareto efficient. Asymptotic smoothness is fairly mild: it requires that, eventually, infinitesimal purchases or sales should see the same per-unit price. Notably, we demonstrate that, under some mild conditions, algorithmic markets based on cost functions (or, equivalently, markets based on market scoring rules) aggregate the information of traders. This paper was accepted by Brad M. Barber, finance .

Suggested Citation

  • Krishnamurthy Iyer & Ramesh Johari & Ciamac C. Moallemi, 2014. "Information Aggregation and Allocative Efficiency in Smooth Markets," Management Science, INFORMS, vol. 60(10), pages 2509-2524, October.
    • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:10:p:2509-2524
    DOI: 10.1287/mnsc.2014.1929
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2014.1929
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2014.1929?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
    ---><---

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Tirole, Jean, 1991. "Perfect Bayesian equilibrium and sequential equilibrium," Journal of Economic Theory, Elsevier, vol. 53(2), pages 236-260, April.
    2. DeMarzo, Peter & Skiadas, Costis, 1998. "Aggregation, Determinacy, and Informational Efficiency for a Class of Economies with Asymmetric Information," Journal of Economic Theory, Elsevier, vol. 80(1), pages 123-152, May.
    3. 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.
    4. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    5. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    6. Radner, Roy, 1979. "Rational Expectations Equilibrium: Generic Existence and the Information Revealed by Prices," Econometrica, Econometric Society, vol. 47(3), pages 655-678, May.
    7. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    8. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    9. Drew Fudenberg & David Levine, 2008. "Subgame–Perfect Equilibria of Finite– and Infinite–Horizon Games," World Scientific Book Chapters, in: Drew Fudenberg & David K Levine (ed.), A Long-Run Collaboration On Long-Run Games, chapter 1, pages 3-20, World Scientific Publishing Co. Pte. Ltd..
    10. 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.
    11. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    12. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    13. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    14. Shipra Agrawal & Erick Delage & Mark Peters & Zizhuo Wang & Yinyu Ye, 2011. "A Unified Framework for Dynamic Prediction Market Design," Operations Research, INFORMS, vol. 59(3), pages 550-568, June.
    15. Mailath, George J. & Samuelson, Larry, 2006. "Repeated Games and Reputations: Long-Run Relationships," OUP Catalogue, Oxford University Press, number 9780195300796.
    16. 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.
    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. Heraud, Florian & Page, Lionel, 2024. "Does the left-digit bias affect prices in financial markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 20-29.
    2. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.
    3. 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.
    4. Rajiv Sethi & Jennifer Wortman Vaughan, 2016. "Belief Aggregation with Automated Market Makers," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 155-178, June.
    5. Dian Yu & Jianjun Gao & Weiping Wu & Zizhuo Wang, 2022. "Price Interpretability of Prediction Markets: A Convergence Analysis," Papers 2205.08913, arXiv.org, revised Nov 2023.
    6. Kimon Drakopoulos & Ali Makhdoumi, 2023. "Providing Data Samples for Free," Management Science, INFORMS, vol. 69(6), pages 3536-3560, June.
    7. Mintz, Yonatan & Aswani, Anil & Kaminsky, Philip & Flowers, Elena & Fukuoka, Yoshimi, 2023. "Behavioral analytics for myopic agents," European Journal of Operational Research, Elsevier, vol. 310(2), pages 793-811.

    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. 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.
    2. Elchanan Mossel & Manuel Mueller‐Frank & Allan Sly & Omer Tamuz, 2020. "Social Learning Equilibria," Econometrica, Econometric Society, vol. 88(3), pages 1235-1267, May.
    3. Spyros Galanis & Christos A Ioannou & Stelios Kotronis, 2024. "Information Aggregation Under Ambiguity: Theory and Experimental Evidence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3423-3467.
    4. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    5. Morone, Andrea & Nuzzo, Simone, 2015. "Market Efficiency, Trading Institutions and Information Mirages: evidence from an experimental asset market," MPRA Paper 67448, University Library of Munich, Germany.
    6. Chitru S. Fernando & Richard J. Herring, 2001. "Liquidity Shocks, Systemic Risk, and Market Collapse: Theory and Application to the Market for Perps," Center for Financial Institutions Working Papers 01-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
    7. Alessio Emanuele Biondo, 2020. "Information versus imitation in a real-time agent-based model of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 613-631, July.
    8. Jason Shachat & Anand Srinivasan, 2022. "Informational Price Cascades and Non-Aggregation of Asymmetric Information in Experimental Asset Markets," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(4), pages 388-407, November.
    9. Galanis Spyros & Kotronis Stelios, 2021. "Updating Awareness and Information Aggregation," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 21(2), pages 613-635, June.
    10. Dasgupta, Amil & Prat, Andrea, 2008. "Information aggregation in financial markets with career concerns," Journal of Economic Theory, Elsevier, vol. 143(1), pages 83-113, November.
    11. Arjoon, Vaalmikki & Bhatnagar, Chandra Shekhar & Ramlakhan, Prakash, 2020. "Herding in the Singapore stock Exchange," Journal of Economics and Business, Elsevier, vol. 109(C).
    12. Malinova, Katya & Park, Andreas, 2013. "Liquidity, volume and price efficiency: The impact of order vs. quote driven trading," Journal of Financial Markets, Elsevier, vol. 16(1), pages 104-126.
    13. Andrea Prat & Amil Dasgupta, 2005. "Reputation and Price Dynamics in Financial Markets," 2005 Meeting Papers 222, Society for Economic Dynamics.
    14. Marco Cipriani & Antonio Guarino, 2014. "Estimating a Structural Model of Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 104(1), pages 224-251, January.
    15. Decamps, Jean-Paul & Lovo, Stefano, 2006. "Informational cascades with endogenous prices: The role of risk aversion," Journal of Mathematical Economics, Elsevier, vol. 42(1), pages 109-120, February.
    16. Spyros Galanis & Sergei Mikhalishchev, 2024. "Information Aggregation with Costly Information Acquisition," Papers 2406.07186, arXiv.org, revised Nov 2024.
    17. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    18. Pooya Molavi & Ceyhun Eksin & Alejandro Ribeiro & Ali Jadbabaie, 2016. "Learning to Coordinate in Social Networks," Operations Research, INFORMS, vol. 64(3), pages 605-621, June.
    19. J. Ford & D. Kelsey & W. Pang, 2013. "Information and ambiguity: herd and contrarian behaviour in financial markets," Theory and Decision, Springer, vol. 75(1), pages 1-15, July.
    20. Andreas Park & Daniel Sgroi, 2008. "Herding and Contrarianism in a Financial Trading Experiment with Endogenous Timing," Working Papers tecipa-341, University of Toronto, Department of Economics.

    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:inm:ormnsc:v:60:y:2014:i:10:p:2509-2524. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.