Abstract
This paper documents the development of three autonomous stock-trading agents within the framework of the Penn Exchange Simulator (PXS), a novel stock-trading simulator that takes advantage of electronic crossing networks to realistically mix agent bids with bids from the real stock market [1]. The three approaches presented take inspiration from reinforcement learning, myopic trading using regression-based price prediction, and market making. These approaches are fully implemented and tested with results reported here, including individual evaluations using a fixed opponent strategy and a comparative analysis of the strategies in a joint simulation. The market-making strategy described in this paper was the winner in the fall 2003 PLAT live competition and the runner-up in the spring 2004 live competition, exhibiting consistent profitability. The strategy’s performance in the live competitions is presented and analyzed.
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Sherstov, A.A., Stone, P. (2006). Three Automated Stock-Trading Agents: A Comparative Study. In: Faratin, P., Rodríguez-Aguilar, J.A. (eds) Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems. AMEC 2004. Lecture Notes in Computer Science(), vol 3435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575726_13
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DOI: https://doi.org/10.1007/11575726_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29737-6
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