Abstract
Agent-based co-evolutionary systems seem to be convenient for modeling market-related behaviors, since they allow for defining competing and/or co-operating agents which can interact and communicate with each other and influence the environment and other agents. In the course of this paper the idea of utilizing of agent-based co-evolutionary approach for supporting decisions of financial investor through generating possible investment strategies is presented and experimentally verified.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Allen, F., Karjalainen, R.: Using genetic algorithms to find technical trading rules. Journal of Financial Economics 51(2), 245–271 (1999)
Bäck, T., Fogel, D., Michalewicz, Z.: Handbook of Evolutionary Computation. IOP Publishing and Oxford University Press (1997)
Dreżewski, R., Sepielak, J.: Evolutionary system for generating investment strategies. In: Giacobini, M. (ed.) EvoWorkshops 2008. LNCS. Springer, Heidelberg (accepted for publication, 2008)
Dreżewski, R., Siwik, L.: Co-evolutionary multi-agent system for portfolio optimization. In: Brabazon, A., O’Neill, M. (eds.) Natural Computation in Computational Finance, pp. 273–303. Springer, Heidelberg (in printing, 2008)
Historical stock data, http://www.parkiet.com/dane/dane_atxt.jsp
Kassicieh, S.K., Paez, T.L., Vora, G.: Investment decisions using genetic algorithms. In: Proceedings of the 30th Hawaii International Conference on System Sciences, vol. 5. IEEE Computer Society, Los Alamitos (1997)
Lintner, J.: The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics 47, 13–37 (1965)
Markowitz, H.: Portfolio selection. Journal of Finance 7(1), 77–91 (1952)
Markowitz, H.: The early history of portfolio theory: 1600-1960. Financial Analysts Journal 55(4), 5–16 (1999)
Pictet, O.V., Dacorogna, M.M., Dave, R.D., Chopard, B., Schirru, R., Tomassini, M.: Genetic algorithms with collective sharing for robust optimization in financial applications. Technical Report OVP.1995-02-06, Olsen & Associates Research Institure for Applied Economics (1995)
Potter, M.A., De Jong, K.A.: Cooperative coevolution: An architecture for evolving coadapted subcomponents. Evolutionary Computation 8(1), 1–29 (2000)
Rom, B., Ferguson, K.: Post-modern portfolio theory comes of age. The Journal of Investing (Winter, 1993)
Ross, S.: The arbitrage theory of capital asset pricing. Journal of Economic Theory 13(3) (1976)
Sharpe, W.F.: Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance 19(3), 425–442 (1964)
Tobin, J.: Liquidity preference as behavior towards risk. The Review of Economic Studies 25, 65–86 (1958)
Treynor, J.: Towards a theory of market value of risky assets (unpublished manuscript, 1961)
Yin, X.: A fast genetic algorithm with sharing scheme using cluster analysis methods in multimodal function optimization. In: Forrest, S. (ed.) Proceedings of the Fifth International Conference on Genetic Algorithms. Morgan Kaufman, San Francisco (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dreżewski, R., Sepielak, J., Siwik, L. (2008). Generating Robust Investment Strategies with Agent-Based Co-evolutionary System. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2008. ICCS 2008. Lecture Notes in Computer Science, vol 5103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69389-5_74
Download citation
DOI: https://doi.org/10.1007/978-3-540-69389-5_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69388-8
Online ISBN: 978-3-540-69389-5
eBook Packages: Computer ScienceComputer Science (R0)