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Bandit Market Makers

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  • Nicolas Della Penna
  • Mark D. Reid

Abstract

We introduce a modular framework for market making. It combines cost-function based automated market makers with bandit algorithms. We obtain worst-case profits guarantee's relative to the best in hindsight within a class of natural "overround" cost functions . This combination allow us to have distribution-free guarantees on the regret of profits while preserving the bounded worst-case losses and computational tractability over combinatorial spaces of the cost function based approach. We present simulation results to better understand the practical behaviour of market makers from the framework.

Suggested Citation

  • Nicolas Della Penna & Mark D. Reid, 2011. "Bandit Market Makers," Papers 1112.0076, arXiv.org, revised Aug 2013.
    • Handle: RePEc:arx:papers:1112.0076
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    References listed on IDEAS

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    1. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    2. Sébastien Bubeck & Rémi Munos & Gilles Stoltz & Csaba Szepesvari, 2011. "X-Armed Bandits," Post-Print hal-00450235, HAL.
    3. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    4. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    5. Omar Besbes & Assaf Zeevi, 2009. "Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms," Operations Research, INFORMS, vol. 57(6), pages 1407-1420, December.
    6. Madureira, Leonardo & Underwood, Shane, 2008. "Information, sell-side research, and market making," Journal of Financial Economics, Elsevier, vol. 90(2), pages 105-126, November.
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