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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. |
