Abstract
The paper describes the model of virtual stock market which is evolved by a genetic algorithm. The model consists of cooperating Agents that imitate behaviour of real investors. They act on the virtual market buying or selling stocks. The aim of the model is to generate stocks prices on a virtual market that are similar to real ones for a short period of time. Each Agent is described by its unique characteristics which determine his performance. The details of the model are presented in the paper. The applied genetic algorithm is generic one. Its main components such as: an individual, genetic operators and fitness function are described here, as well. The results of experiments investigating the role of genetic algorithm parameters are presented in the paper. Agent’s ability to predict the quotations values are presented and analysed. Future plans referring to the further development of the system are presented at the end of the paper.
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Markowska-Kaczmar, U., Kwasnicka, H., Szczepkowski, M. (2008). Genetic Algorithm as a Tool for Stock Market Modelling. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_44
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DOI: https://doi.org/10.1007/978-3-540-69731-2_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
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