Bandit Market Makers
Trading and Market Microstructure
2013-08-05 v4 Computer Science and Game Theory
Machine Learning
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.
Keywords
Cite
@article{arxiv.1112.0076,
title = {Bandit Market Makers},
author = {Nicolas Della Penna and Mark D. Reid},
journal= {arXiv preprint arXiv:1112.0076},
year = {2013}
}
Comments
A previous version of this work appeared in the NIPS 2011 Workshop on Computational Social Science and the Wisdom of the Crowds