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Liquidity Sentiments

Author

Listed:
  • Vladimir Asriyan
  • William Fuchs
  • Brett Green

Abstract

We develop a rational theory of liquidity sentiments in which the market outcome in any given period depends on agents' expectations about market conditions in future periods. Our theory is based on the interaction between adverse selection and resale considerations giving rise to an intertemporal coordination problem that yields multiple self-fulfilling equilibria. We construct "sentiment" equilibria in which sunspots generate fluctuations in prices, volume, and welfare, all of which are positively correlated. The intertemporal nature of the coordination problem disciplines the set of possible sentiment dynamics. In particular, sentiments must be sufficiently persistent and transitions must be stochastic. We consider an extension with production in which asset quality is endogenously determined and provide conditions under which sentiments are a necessary feature of any equilibrium. A testable implication is that assets produced in good times are of lower average quality than those produced in bad times.

Suggested Citation

  • Vladimir Asriyan & William Fuchs & Brett Green, 2019. "Liquidity Sentiments," American Economic Review, American Economic Association, vol. 109(11), pages 3813-3848, November.
    • Handle: RePEc:aea:aecrev:v:109:y:2019:i:11:p:3813-48
    Note: DOI: 10.1257/aer.20180998
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    File URL: https://www.aeaweb.org/doi/10.1257/aer.20180998
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    Citations

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    Cited by:

    1. Zhou, Jing, 2022. "Collateral quality and house prices," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    2. Jehiel, Philippe & Mohlin, Erik, 2021. "Cycling and Categorical Learning in Decentralized Adverse Selection Economies," Working Papers 2021:11, Lund University, Department of Economics.
    3. Lee, Michael Junho & Neuhann, Daniel, 2023. "Collateral quality and intervention traps," Journal of Financial Economics, Elsevier, vol. 147(1), pages 159-171.
    4. Emiliano S Pagnotta, 2022. "Decentralizing Money: Bitcoin Prices and Blockchain Security," The Review of Financial Studies, Society for Financial Studies, vol. 35(2), pages 866-907.
    5. Asriyan, Vladimir & Fuchs, William & Green, Brett, 2021. "Aggregation and design of information in asset markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 191(C).
    6. Laura Nowzohour & Livio Stracca, 2020. "More Than A Feeling: Confidence, Uncertainty, And Macroeconomic Fluctuations," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 691-726, September.
    7. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Research Discussion Papers 5/2020, Bank of Finland.
    8. Han, Jungsuk & Wang, Yenan, 2025. "All that glitters: A theory of multiple bubbles with implications for cryptocurrencies," Journal of Monetary Economics, Elsevier, vol. 152(C).
    9. Priit Jeenas & Alberto Martin & Vladimir Asriyan, 2026. "Frost and Fire: A Tale of Two Crises," Working Papers 1567, Barcelona School of Economics.
    10. Mäkinen, Taneli & Palazzo, Francesco, 2024. "Adverse selection and search congestion in over-the-counter markets," Journal of Monetary Economics, Elsevier, vol. 146(C).
    11. Wang, Xinyu & Fang, Zhuangzhi & Wang, Zhenxin, 2025. "The dual role of sentiment on housing prices in China," International Review of Economics & Finance, Elsevier, vol. 97(C).

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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