Bandit Market Makers
AbstractWe 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.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1112.0076.
Date of creation: Nov 2011
Date of revision: Aug 2013
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Web page: http://arxiv.org/
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- 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.
- Madureira, Leonardo & Underwood, Shane, 2008. "Information, sell-side research, and market making," Journal of Financial Economics, Elsevier, vol. 90(2), pages 105-126, November.
- Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
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