Peter Stone's Selected Publications

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Three Automated Stock-Trading Agents: A Comparative Study

Alexander Sherstov and Peter Stone. Three Automated Stock-Trading Agents: A Comparative Study. In P. Faratin and J.A. Rodriguez-Aguilar, editors, Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC 2004), Lecture Notes in Artificial Intelligence, pp. 173–187, Springer Verlag, Berlin, 2005.
Official version from Publisher's Webpage© Springer-Verlag

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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. 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.

BibTeX Entry

@InCollection(AMEC04-plat,
        author="Alexander Sherstov and Peter Stone",
        title="Three Automated Stock-Trading Agents: A Comparative Study",
        booktitle="Agent Mediated Electronic Commerce {VI}:  Theories for and Engineering of Distributed Mechanisms and Systems (AMEC 2004)",
        editor="P.~Faratin and J.A.~Rodriguez-Aguilar",
        series="Lecture Notes in Artificial Intelligence",      
	volume="3435",
        Publisher="Springer Verlag",address="Berlin",year="2005",
	pages="173--187",
        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. 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.
                 },
  wwwnote={Official version from <a href="http://dx.doi.org/10.1007/11575726_13">Publisher's Webpage</a>&copy Springer-Verlag},
)

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