PL EN


2013 | 146 | 59-67
Article title

Porównanie podejścia aproksymującego i klasyfikującego w prognozowaniu kursów wybranych akcji na GPW w Warszawie S.A. z użyciem jednokierunkowych sieci neuronowych

Authors
Content
Title variants
EN
Forecasting Stock Prices Using Feed-Forward Neural Network - a Comparison of Approximation and Classification Approaches
Languages of publication
PL
Abstracts
EN
In this paper two approaches to financial time series forecasting using neural networks were compared. First one, the function approximation approach, in which neural networks are trained to forecast the exact one day ahead value of stock price. And the second one, classification approach, in which the output variable is the direction of future stock price movements. The aim of this work was to check if using the classification models can lead to better results in terms of direction of change forecasting and profits generated by their forecasts. This research was conducted on the basis of the time series of daily closing stock prices for three companies listed on the Warsaw Stock Exchange. Simulations show that some of the approximating models achieved satisfactory results in terms of the directional symmetry measure, although the best results for each of the analyzed company have been achieved for classification models.
Year
Volume
146
Pages
59-67
Physical description
Contributors
author
References
  • Gately E.J., Sieci neuronowe. Prognozowanie finansowe i projektowanie systemów transakcyjnych, WIG-Press, Warszawa 1999.
  • Huang W., Nakamori Y., Wang S., Zhang H., Select the Size of Training Set for Financial Forecasting with Neural Networks, Proceedings of the International Symposium on Neural Networks, Springer-Verlag, Berlin-Heidelberg 2005, s. 879-884.
  • Jankowski N., Ontogeniczne sieci neuronowe, EXIT, Warszawa 2003.
  • Kamruzzaman J., Begg R., Sarker R., Artificial Neural Networks in Finance and Manufacturing, Idea Group Inc., 2006.
  • Leung M.T., Daouk H., Chen A., Forecasting Stock Indices: A Comparison of Classification and Level Estimation Models, "International Journal of Forecasting" 2000, Vol. 16, s. 173-190.
  • Masters T., Sieci neuronowe w praktyce. Programowanie w języku C++, WNT, Warszawa 1996.
  • Neural Networks in the Capital Markets, red. A.-P. Refenes, John Wiley & Sons Ltd, 1995.
  • Trippi R., Lee J.K., Artificial Intelligence in Finance and Investments, IRWIN, 1996.
  • Walczak S., An Empirical Analysis of Data Requirements for Financial Forecasting with Neural Networks, "Journal of Management Information Systems" 2001, Vol. 17, No. 4, Spring, s. 203-222.
  • Zhang G., Eddy Patuwo B., Hu M.Y., Forecasting with Artificial Neural Networks: The State of Art, "International Journal of Forecasting" 1998, Vol. 14, s. 35-62.
Document Type
Publication order reference
Identifiers
ISSN
2083-8611
YADDA identifier
bwmeta1.element.desklight-d486abb6-276b-4dc5-ad6c-774d05ac1572
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