Performance analysis of a counter-intuitive automated stock-trading agent

ABSTRACT

Autonomous trading in stock markets is an area of great interest in both academic and commercial circles. A lot of trading strategies have been proposed and practiced from the perspectives of Artificial Intelligence, market making, external data indication, technical analysis, etc. This paper examines some properties of a counter-intuitive automated stock-trading strategy in the context of the Penn-Lehman Automated Trading (PLAT) simulator [1], which is a realtime, real-data market simulator. While it might seem natural to buy when the market is on the rise and sell when it is on the decline, our strategy does exactly the opposite. As a result, we call it the reverse strategy. The reverse strategy was the winner strategy in the first and second PLAT live competitions. In this paper, we analyze the performance of the reverse strategy. Also, we suggest ways to control the risk of using the reverse strategy in certain kinds of markets.

REFERENCES

• 1: The Penn-Lehman Automated Trading Project: http://www.cis.upenn.edu/~mkearns/projects/pat.html
• 2: Archipelago: http://www.tradearca.com
• 3: Bloomberg: http://www.bloomberg.com
• 4: Island: http://www.island.com
• 5: The 2002 annual report of Securities Industry Foundation for Economic Education, 2002: http://www.sia.com/about_sia/pdf/annual2002.pdf
• 6: Virtual Stock Exchange: http://www.virtualstockexchange.com
• 7: R. Freedman et. al., eds., Artificial Intelligence in Capital Markets, Chicago, IL: Probus Pub., 1995.
• 8: A. Skabar and I. Cloete. "Discovery of Financial Trading Rules." In Proc. Artificial Intelligence and Applications, pp. 121--125, 2001.
• 9: Jason Kingdon , J. G. Taylor , C. L. Mannion, Intelligent Systems and Financial Forecasting, Springer-Verlag New York, Inc., Secaucus, NJ, 1997
• 10: M. Sheimo. Stock Market Rules: 50 of the most widely held investment axioms explained, examined and exposed, Chicago, IL: Probus Pub., 1991.
• 11: Peter Stone , Amy Greenwald, The First International Trading Agent Competition: Autonomous Bidding Agents, Electronic Commerce Research, v.5 n.2, p.229-265, April 2005 [doi>10.1007/s10660-005-6158-z]