In agent-based computational economics, many different trading strategies have been proposed. Given the kinds of market that such trading strategies are employed in, it is clear that the performance of the strategies depends heavily on the behavior of other traders. However, most trading strategies are studied in homogeneous populations, and those tests that have been carried out on heterogeneous populations are limited to a small number of strategies. In this paper we extend the range of strategies that have been exposed to a more extensive analysis, measuring the performance of eight trading strategies using an approach based on evolutionary game theory.
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