Abstract

In this chapter we describe a stock market simulation in which stock market participants use genetic algorithms to gradually improve their trading strategies over time. A variety of experiments show that, under certain conditions, some market participants can make consistent profits over an extended period of time, a finding that might explain the success of some real-world money managers. These experiments suggest a four parameter model of market participants. Each participant can be described along four dimensions: information set, constraint set, algorithm set, and model set. The information set captures what data the participant has access to (e.g., the participant has access to all historical price data). The constraint set describes under what restrictions the participant operates (e.g., the participant can borrow money at 1% above the prime rate). The algorithm set indicates what programs the participant can use (e.g., the participant is restricted to hill-climbing optimization ...

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