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Smooth Trading with Overconfidence and Market Power

Author

Listed:
  • Albert S. Kyle

    (Robert H. Smith School of Business, University of Maryland)

  • Anna Obizhaeva

    (New Economic School)

  • Yajun Wang

    (Robert H. Smith School of Business, University of Maryland)

Abstract

We describe a symmetric continuous-time model of trading among relatively overconfident, oligopolistic informed traders with exponential utility. Traders agree to disagree about the precisions of their continuous flows of Gaussian private information. The price depends on a trader’s inventory (permanent price impact) and the derivative of a trader’s inventory (temporary price impact). More disagreement makes the market more liquid; without enough disagreement, there is no trade. Target inventories mean-revert at the same rate as private signals. Actual inventories smoothly adjust toward target inventories at an endogenous rate which increases with disagreement. Faster-than-equilibrium trading generates “flash crashes” by increasing temporary price impact. A “Keynesian beauty contest” dampens price fluctuations.

Suggested Citation

  • Albert S. Kyle & Anna Obizhaeva & Yajun Wang, 2016. "Smooth Trading with Overconfidence and Market Power," Working Papers w0226, Center for Economic and Financial Research (CEFIR).
    • Handle: RePEc:cfr:cefirw:w0226
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Fabrice Rousseau & Herve Boco & Laurent Germain, 2020. "When Overconfident Traders Meet Feedback Traders - Updated from 2016," Economics Department Working Paper Series n270-16.pdf, Department of Economics, National University of Ireland - Maynooth.
    2. Kyle, Albert S. & Obizhaeva, Anna A. & Tuzun, Tugkan, 2020. "Microstructure invariance in U.S. stock market trades," Journal of Financial Markets, Elsevier, vol. 49(C).
    3. Frei, Christoph & Mitra, Joshua, 2021. "Optimal closing benchmarks," Finance Research Letters, Elsevier, vol. 40(C).
    4. Lou, Youcheng & Rahi, Rohit, 2021. "Information, market power and welfare," LSE Research Online Documents on Economics 118843, London School of Economics and Political Science, LSE Library.
    5. Lou, Youcheng & Yang, Yaqing, 2023. "Information linkages in a financial market with imperfect competition," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
    6. Guo, Mng, 2023. "Dampening effect and market efficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    7. Rahi, Rohit, 2021. "Information acquisition with heterogeneous valuations," Journal of Economic Theory, Elsevier, vol. 191(C).
    8. Albert S. Kyle & Anna Obizhaeva & Yajun Wang, 2016. "Beliefs Aggregation and Return Predictability," Working Papers w0231, Center for Economic and Financial Research (CEFIR).
    9. Cujean, Julien & Bustamante, Maria Cecilia & Frésard, Laurent, 2019. "Knowledge Cycles and Corporate Investment," CEPR Discussion Papers 14152, C.E.P.R. Discussion Papers.
    10. Michail Anthropelos & Scott Robertson & Konstantinos Spiliopoulos, 2021. "Optimal investment, derivative demand, and arbitrage under price impact," Mathematical Finance, Wiley Blackwell, vol. 31(1), pages 3-35, January.
    11. Puru Gupta & Saul D. Jacka, 2023. "Portfolio Choice In Dynamic Thin Markets: Merton Meets Cournot," Papers 2309.16047, arXiv.org.
    12. Michail Anthropelos & Constantinos Kardaras & Georgios Vichos, 2020. "Effective risk aversion in thin risk‐sharing markets," Mathematical Finance, Wiley Blackwell, vol. 30(4), pages 1565-1590, October.
    13. Michail Anthropelos & Scott Robertson & Konstantinos Spiliopoulos, 2018. "Optimal Investment, Demand and Arbitrage under Price Impact," Papers 1804.09151, arXiv.org, revised Dec 2018.
    14. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    15. Sudhanshu Pani, 2020. "A Theory of 'Auction as a Search' in speculative markets," Papers 2006.00775, arXiv.org.
    16. Eric Budish & Robin S. Lee & John J. Shim, 2019. "A Theory of Stock Exchange Competition and Innovation: Will the Market Fix the Market?," NBER Working Papers 25855, National Bureau of Economic Research, Inc.
    17. Eric Budish & Peter Cramton & Albert S. Kyle & Jeongmin Lee & David Malec, 2022. "Flow Trading," ECONtribute Discussion Papers Series 146, University of Bonn and University of Cologne, Germany.
    18. Albert S. Kyle & Anna Obizhaeva & Yajun Wang, 2016. "Beliefs Aggregation and Return Predictability," Working Papers w0231, New Economic School (NES).
    19. Stepan Gorban & Anna A. Obizhaeva & Yajun Wang, 2020. "Trading in Crowded Markets," Working Papers w0275, New Economic School (NES).
    20. Lou, Youcheng & Rahi, Rohit, 2023. "Information, market power and welfare," LSE Research Online Documents on Economics 120479, London School of Economics and Political Science, LSE Library.
    21. Albert S. Kyle & Anna A. Obizhaeva & Yajun Wang, 2023. "Beliefs Aggregation and Return Predictability," Journal of Finance, American Finance Association, vol. 78(1), pages 427-486, February.

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    More about this item

    Keywords

    market microstructure; price impact; liquidity; transaction costs; double auctions; information aggregation; rational expectations; agreement-to-disagree; imperfect competition; Keynesian beauty contest; overconfidence; strategic trading; dynamic trading; flash crash;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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