Summary
In this chapter an evolutionary system for generating investment strategies is presented. The algorithms used in the system (evolutionary algorithm, co-evolutionary algorithm, and agent-based co-evolutionary algorithm) are verified and compared on the basis of the results coming from experiments carried out with the use of real-life stock data. The conclusions drawn from the results of experiments are such that co-evolutionary and agent-based co-evolutionary techniques better maintain population diversity and generate more general investment strategies than evolutionary algorithms.
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Dreżewski, R., Sepielak, J., Siwik, L. (2009). Classical and Agent-Based Evolutionary Algorithms for Investment Strategies Generation. In: Brabazon, A., O’Neill, M. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95974-8_9
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