Bandit Market Makers
Date
2011
Authors
Della Penna, Nicolas
Reid, Mark
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Abstract
We propose a flexible framework for profit-seeking market making by combining cost function based automated market makers with bandit learning algorithms. The key idea is to consider each parametrisation of the cost function as a bandit arm, and the minimum expected profits from trades executed during a period as the rewards. This allows for the creation of market makers that can adjust liquidity and bid-asks spreads dynamically to maximise profits.
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Computing Research Repository (CoRR)
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Conference paper
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Open Access
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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
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