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Rational expectations equilibrium with uncertain proportion of informed traders

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  • Gao, Feng
  • Song, Fengming
  • Wang, Jun

Abstract

This paper introduces uncertainty regarding the proportion of informed traders in a rational expectation equilibrium model with asymmetric information. The proportion uncertainty dramatically changes the properties of the resulting equilibrium. First, it may generate multiple nonlinear rational expectations equilibria, which can help explain the excessive volatility of stock prices. Second, the expected price informativeness is a non-monotonic function of the proportion of informed traders, which suggests that the traders will have more incentive to become informed as the proportion of informed traders gets larger.

Suggested Citation

  • Gao, Feng & Song, Fengming & Wang, Jun, 2013. "Rational expectations equilibrium with uncertain proportion of informed traders," Journal of Financial Markets, Elsevier, vol. 16(3), pages 387-413.
    • Handle: RePEc:eee:finmar:v:16:y:2013:i:3:p:387-413
    DOI: 10.1016/j.finmar.2012.04.001
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    Cited by:

    1. Banerjee, Snehal & Green, Brett, 2015. "Signal or noise? Uncertainty and learning about whether other traders are informed," Journal of Financial Economics, Elsevier, vol. 117(2), pages 398-423.
    2. Yang Hao, 2023. "Financial Market with Learning from Price under Knightian Uncertainty," Working Papers hal-03686748, HAL.
    3. H. Henry Cao & Dongyan Ye, 2016. "Transaction Risk, Derivative Assets, and Equilibrium," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
    4. Ping-Chen Tsai & Chi-Ming Tsai, 2021. "Estimating the proportion of informed and speculative traders in financial markets: evidence from exchange rate," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 443-470, July.
    5. Nihad Aliyev, 2019. "Financial Markets with Multidimensional Uncertainty," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2019, January-A.
    6. Shiyang Huang & Bart Zhou Yueshen, 2021. "Speed Acquisition," Management Science, INFORMS, vol. 67(6), pages 3492-3518, June.
    7. Peress, Joël & Schmidt, Daniel, 2024. "Uncertainty about what is in the price," Journal of Financial Economics, Elsevier, vol. 161(C).
    8. Jean-Edouard Colliard, 2017. "Catching Falling Knives: Speculating on Liquidity Shocks," Management Science, INFORMS, vol. 63(8), pages 2573-2591, August.
    9. Dimitris Papadimitriou, 2023. "Trading under uncertainty about other market participants," The Financial Review, Eastern Finance Association, vol. 58(2), pages 343-367, May.
    10. Marmora, Paul & Rytchkov, Oleg, 2018. "Learning about noise," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 209-224.
    11. Rossi, Stefano & Tinn, Katrin, 2021. "Rational quantitative trading in efficient markets," Journal of Economic Theory, Elsevier, vol. 191(C).
    12. Juan Carlos Hatchondo & Per Krusell & Martin Schneider, 2014. "Asset Trading and Valuation with Uncertain Exposure," Working Paper 14-5, Federal Reserve Bank of Richmond.
    13. Sadzik, Tomasz & Woolnough, Chris, 2021. "Snowballing private information," Journal of Economic Theory, Elsevier, vol. 198(C).

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    More about this item

    Keywords

    Nonlinear rational expectations equilibrium; Asymmetric information; Multiplicity; Complementarity;
    All these keywords.

    JEL classification:

    • 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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