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Market Selection With Differential Financial Constraints

Author

Listed:
  • Ani Guerdjikova

    (GAEL - Laboratoire d'Economie Appliquée de Grenoble - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INRA - Institut National de la Recherche Agronomique - CNRS - Centre National de la Recherche Scientifique - UGA [2016-2019] - Université Grenoble Alpes [2016-2019])

  • John Quiggin

    (UQ [All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations] - The University of Queensland)

Abstract

We analyze financial markets in which agents face differential constraints on the set of assets in which they can trade. In particular, the assets available to each agent span a partition of the state space that can be strictly coarser than the partition spanned by the assets available in the market. We first show that the existence of differential constraints has an impact on prices and allocations as compared to a complete financial market with unconstrained agents. We consider the implications for survival, taking the work of Blume and Easley (2006) as a starting point. We show that whenever agents have identical correct beliefs and equal discount factors, and their partitions are nested, all agents survive. When agents have heterogeneous beliefs, differential constraints may allow agents with wrong beliefs to survive. Provided constraints are relevant (in a sense we define more precisely), the condition for an agent to survive is that his survival index is at least as large as that of the agents with finer partitions. We also study the impact of deregulation (an increase in the set of assets available to some agents). Unless the agent can adopt beliefs that are closer to the truth on the newly refined partition than those of less constrained agents, increasing his opportunities for trade might harm his chances for survival.

Suggested Citation

  • Ani Guerdjikova & John Quiggin, 2019. "Market Selection With Differential Financial Constraints," Post-Print hal-02324713, HAL.
    • Handle: RePEc:hal:journl:hal-02324713
    DOI: 10.3982/ECTA15328
    Note: View the original document on HAL open archive server: https://hal.science/hal-02324713v1
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    Cited by:

    1. Pietro Dindo & Filippo Massari, 2025. "Learning Models from Prices," Working Papers 2025: 17, Department of Economics, University of Venice "Ca' Foscari".
    2. Pau Milán & Johannes Gierlinger, 2021. "The Limits to Local Insurance," Working Papers 1293, Barcelona School of Economics.
    3. Zimper, Alexander, 2023. "Unrealized arbitrage opportunities in naive equilibria with non-Bayesian belief processes," Mathematical Social Sciences, Elsevier, vol. 125(C), pages 27-41.
    4. Minardi, Stefania & Savochkin, Andrei, 2019. "Subjective contingencies and limited Bayesian updating," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1-45.
    5. Jan Libich & Liam Lenten, 2022. "Hero or villain? The financial system in the 21st century," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 3-40, February.
    6. Guerdjikova, A. & Quiggin, J., 2020. "Financial market equilibrium with bounded awareness," Working Papers 2020-10, Grenoble Applied Economics Laboratory (GAEL).
    7. Bottazzi, Giulio & Giachini, Daniele & Ottaviani, Matteo, 2023. "Market selection and learning under model misspecification," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).
    8. Bottazzi, Giulio & Dindo, Pietro, 2022. "Drift criteria for persistence of discrete stochastic processes on the line," Journal of Mathematical Economics, Elsevier, vol. 101(C).

    More about this item

    Keywords

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    JEL classification:

    • D50 - Microeconomics - - General Equilibrium and Disequilibrium - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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