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Slope-takers in anonymous markets

Author

Listed:
  • Marek Weretka

    (University of Wisconsin-Madison
    Group for Research in Applied Economics (GRAPE))

  • Daniel Quint

    (University of Wisconsin-Madison)

Abstract

We present a learning-based selection argument for Linear Bayesian Nash equilibrium in a Walrasian auction. Endowments vary stochastically; traders model residual supply as linear, estimate its slope from past trade data, and periodically update these estimates. With quadratic preferences, this learning process converges to the unique LBN. In an example with non-quadratic preferences, it converges to a steady state close to a particular equilibrium of the corresponding deterministic setting; strategies played are not an equilibrium, but utility sacrificed is negligible. Anonymity and statistical learning therefore support use of LBN under quadratic utility, and motivate a related concept under non-quadratic utility.

Suggested Citation

  • Marek Weretka & Daniel Quint, 2022. "Slope-takers in anonymous markets," GRAPE Working Papers 64, GRAPE Group for Research in Applied Economics.
    • Handle: RePEc:fme:wpaper:64
    as

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    File URL: http://grape.org.pl/WP/64_QuintWeretka_website.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Walrasian auction; anonymous thin markets; price impacts;
    All these keywords.

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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