Keywords
artificial intelligence methods
genetic algorithms
neural networks
financial markets
decision support systems
portfolio management
genetic algorithms
neural networks
financial markets
decision support systems
portfolio management
How to Cite
MorajdaJ. (2006). Usefulness of neutral networks and genetic algorithms in the development of investment decision systems. The Malopolska School of Economics in Tarnow Research Papers Collection, 9(1), 217-230. https://doi.org/10.25944/znmwse.2006.01.217230
Abstract
The paper discusses basic aspects of application of active investment strategies in financial markets - in the context of classic theories of portfolio management. Such active strategies are generated with the use of decision support systems (transaction systems). The main assumptions of utilisation of artificial intelligence methods, such as neural networks and genetic algorithms, in the construction of investment decision systems have been indicated. The characteristic of neural networks and genetic algorithms as effective tools in financial markets modelling and prediction has also been discussed here.
References
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Bauer R. 1994. Genetic Algorithms and Investment Strategies. New York: Wiley. ISBN 0471576794
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Markowitz H.M. 1952. Portfolio selection. "Journal of Finance" March 1952.
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Morajda J. 2002. Czynniki efektywnego wykorzystania sieci neuronowych w procesie modelowania rynków finansowych. Zeszyty Naukowe AE w Krakowie nr 604. Kraków.
Morajda J. 2003a. Neural Networks and Their Economic Applications. W: Artificial Intelligence and Security in Computing Systems. Boston - Dordrecht - London: Kluwer Academic Publishers. ISBN 1402073968.
Morajda J. 2003b. Evolutionarily Developed Neural Networks for Investment Strategies Construction. Advances in Soft Computing. W: Neural Networks and Soft Computing. Heidelberg: Physica Verlag. ISBN 3790800058.
Morajda J., Domaradzki R. 2005. Application of Cluster Analysis Performed by SOM Neural Network to the Creation of Financial Transaction Strategies. "Journal of Applied Computer Science" 2005, Volume 13, No 1. Łódź: Technical University Press.
Peters E. E. 1997. Teoria chaosu a rynki kapitałowe. Warszawa: WIG-Press. ISBN 83-87014-01-X.
Refenes A.P. (ed.). 1995. Neural networks in the capital markets. Chichester: Wiley. ISBN 0471943649.
Rutkowska D., Piliński M., Rutkowski L. 1997. Sieci neuronowe, algorytmy genetyczne i systemy rozmyte. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-12304-4.
Rutkowski L. 2005. Metody i techniki sztucznej inteligencji. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-14529-3.
Sharpe W. F. 1963. A simplified model for portfolio analysis. "Management Science" 1963, no.19.
Tadeusiewicz R. 1993. Sieci neuronowe. Warszawa: Akademicka Oficyna Wydawnicza RM. ISBN 83-85769-03-X.
Taylor W.R.L., Yoder J.A. 1994. Mutual fund trading activity and investor utility. "Financial Analysis Journal" May-June 1994.
Zieliński J.S. (red.) 2000. Inteligentne systemy w zarządzaniu. Teoria i praktyka. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-12968-9.
Bauer R. 1994. Genetic Algorithms and Investment Strategies. New York: Wiley. ISBN 0471576794
Bodie Z., Kane A., Marcus A.I. 1993. Investments. 2nd ed. Boston: Irwin. ISBN 0256122148.
Fama E.F. 1970. Efficient capital markets: A review of theory and empirical work. "Journal of Finance" No. 25, May 1970.
Goldberg D. E. 1998. Algorytmy genetyczne i ich zastosowania. Warszawa: WNT. ISBN 83-204-2272-8.
Haugen R.A. 1996. Teoria nowoczesnego inwestowania. Warszawa: WIG Press. ISBN 83-903296-5-4.
Haykin S. 1994. Neural networks. A comprehensive foundation. New York: Macmillan College Publishing Company. ISBN 0023527617.
Jajuga K., Jajuga T. 1996. Inwestycje: instrumenty finansowe, ryzyko finansowe, inżynieria finansowa. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-12021-5.
Markowitz H.M. 1952. Portfolio selection. "Journal of Finance" March 1952.
Michalewicz Z. 1999. Algorytmy genetyczne + struktury danych = programy ewolucyjne. Warszawa: WNT. ISBN 83-204-2881-5.
Morajda J. 2002. Czynniki efektywnego wykorzystania sieci neuronowych w procesie modelowania rynków finansowych. Zeszyty Naukowe AE w Krakowie nr 604. Kraków.
Morajda J. 2003a. Neural Networks and Their Economic Applications. W: Artificial Intelligence and Security in Computing Systems. Boston - Dordrecht - London: Kluwer Academic Publishers. ISBN 1402073968.
Morajda J. 2003b. Evolutionarily Developed Neural Networks for Investment Strategies Construction. Advances in Soft Computing. W: Neural Networks and Soft Computing. Heidelberg: Physica Verlag. ISBN 3790800058.
Morajda J., Domaradzki R. 2005. Application of Cluster Analysis Performed by SOM Neural Network to the Creation of Financial Transaction Strategies. "Journal of Applied Computer Science" 2005, Volume 13, No 1. Łódź: Technical University Press.
Peters E. E. 1997. Teoria chaosu a rynki kapitałowe. Warszawa: WIG-Press. ISBN 83-87014-01-X.
Refenes A.P. (ed.). 1995. Neural networks in the capital markets. Chichester: Wiley. ISBN 0471943649.
Rutkowska D., Piliński M., Rutkowski L. 1997. Sieci neuronowe, algorytmy genetyczne i systemy rozmyte. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-12304-4.
Rutkowski L. 2005. Metody i techniki sztucznej inteligencji. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-14529-3.
Sharpe W. F. 1963. A simplified model for portfolio analysis. "Management Science" 1963, no.19.
Tadeusiewicz R. 1993. Sieci neuronowe. Warszawa: Akademicka Oficyna Wydawnicza RM. ISBN 83-85769-03-X.
Taylor W.R.L., Yoder J.A. 1994. Mutual fund trading activity and investor utility. "Financial Analysis Journal" May-June 1994.
Zieliński J.S. (red.) 2000. Inteligentne systemy w zarządzaniu. Teoria i praktyka. Warszawa: Wydawnictwo Naukowe PWN. ISBN 83-01-12968-9.
© Copyright by Małopolska School of Economics in Tarnów. The articles are available under the Creative Commons Attribution NonCommercial-NoDerivatives 4.0 International License
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