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@InCollection(AMEC03,
author = "Yi Feng and Ronggang Yu and Peter Stone",
title="Two Stock-Trading Agents: Market Making and Technical Analysis",
booktitle="Agent Mediated Electronic Commerce {V}: Designing Mechanisms and Systems",
editor="Peyman Faratin and David C.\ Parkes and Juan A.\ Rodriguez-Aguilar and William E.\ Walsh",
series="Lecture Notes in Artificial Intelligence",
publisher="Springer Verlag",
volume="3048",
year="2004",
pages="18--36",
abstract={
Evolving information technologies have brought
computational power and real-time facilities into
the stock market. Automated stock trading draws much
interest from both the fields of computer science
and of business, since it promises to provide
superior ability in a trading market than any
individual trader. Trading strategies have been
proposed and practiced from the perspectives of
Artificial Intelligence, market making, external
information feedback, technical analysis etc. This
paper examines two automated stock-trading agents in
the context of the Penn-Lehman Automated Trading
(PLAT) simulator, which is a real-time, real-data
market simulator. The first agent devises a
market-making strategy exploiting market volatility
without predicting the exact direction of the stock
price movement. The second agent uses technical
analysis. It might seem natural to buy when the
market is on the rise and sell when it's on the
decline, but the second agent does exactly the
opposite. As a result, we call it the reverse
strategy. The strategies used by both agents are
adapted for automated trading. Both agents performed
well in the PLAT live competition. In this paper, we
analyze the performance of these two automated
trading strategies. Comparisons between them are
also provided.
},
wwwnote={AMEC-2003},
)