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Strategic Trading And Learning About Liquidity

Author

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  • Rady, Sven
  • Hong, Harrison G

Abstract

We develop a multi-period model of strategic trading in an asset market where traders are uncertain about market liquidity. In our model, informed traders strategically trade against competitive market makers to exploit their short-lived private information. Unlike market makers, informed traders do not know whether the liquidity ('noise') trades are generated from a distribution with high or low variance. Instead, informed traders have to learn about liquidity from past prices. We find the following. (1) Prices that deviate markedly from the forecast of terminal asset value based on public news tend to lead to revisions of informed traders' beliefs in favour of the low liquidity state. (2) This revision in beliefs results in less aggressive trading on private information by informed traders. (3) In turn, informational efficiency and trading volume are dependent on the path of prices. (4) Moreover, learning about liquidity also has interesting effects on the unconditional properties of optimal strategic trading policies.

Suggested Citation

  • Rady, Sven & Hong, Harrison G, 2000. "Strategic Trading And Learning About Liquidity," CEPR Discussion Papers 2416, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:2416
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    1. is not listed on IDEAS
    2. Jianhao Su & Yanliang Zhang, 2025. "The disclosure of information about the range of asset value in market," Papers 2511.11405, arXiv.org, revised Jan 2026.
    3. Julia M. Puaschunder, 2023. "Finance Followership," RAIS Conference Proceedings 2022-2025 0249, Research Association for Interdisciplinary Studies.
    4. Nam, Jouahn & Wang, Jun & Zhang, Ge, 2008. "Strategic trading against retail investors with loss-aversion," International Review of Economics & Finance, Elsevier, vol. 17(1), pages 45-55.
    5. Acharya, Viral V. & Johnson, Timothy C., 2007. "Insider trading in credit derivatives," Journal of Financial Economics, Elsevier, vol. 84(1), pages 110-141, April.
    6. Marmora, Paul & Rytchkov, Oleg, 2018. "Learning about noise," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 209-224.
    7. Alavi, Soogand & Haruvy, Ernan & Xie, Ying, 2025. "On the role of provenance in NFT trades," International Journal of Research in Marketing, Elsevier, vol. 42(3), pages 610-625.
    8. Mu-Shun Wang, 2022. "Shareholder Disputes and Commonality in Liquidity: Evidence from the Equity Markets in China," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(2), pages 291-325, June.

    More about this item

    Keywords

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    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • 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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