Adaptive prediction of stock exchange indices by state space wavelet networks

• Autorzy: Mietek A. Brdyś , Adam Borowa , Piotr Idźkowiak , Marcin T. Brdyś
• Języki publikacji: EN

Abstrakty

EN

The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session ahead and five sessions ahead adaptive predictors of the WIG20 index prices. The predictors are validated based on real data records to produce promising results. The state space wavelet network model may also be used as a forecasting tool for a wide range of economic and non-economic indicators, such as goods and row materials prices, electricity/fuel consumption or currency exchange rates.

Słowa kluczowe

EN

forecasting; stock exchange; artificial intelligence; state space wavelet network; simulated annealing

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2009
• Tom: 19
• Numer: 2
• Strony: 337-348

Daty

wydano

2009

otrzymano

2008-05-09

poprawiono

2008-09-14

Twórcy

autor

Mietek A. Brdyś

• School of Electronic, Electrical and Computer Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
• Department of Control Systems Engineering, Gdańsk University of Technology, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Adam Borowa

• Department of Control Systems Engineering, Gdańsk University of Technology, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Piotr Idźkowiak

• School of Electronic, Electrical and Computer Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
• Philips Lightning Poland BU CLE/IPLC GLS 10NC & CFL-i Burners Assistant Industrial Engineer

autor

Marcin T. Brdyś

• Corporate Banking & MIB Division, Financial Markets Department, Planning, Controlling & Support, Bank Pekao SA, ul. Grzybowska 53/57, 00-950 Warsaw, Poland

Bibliografia

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Identyfikatory

DOI

10.2478/v10006-009-0029-z