# Adaptive prediction of stock exchange indices by state space wavelet networks

Mietek A. Brdyś; Adam Borowa; Piotr Idźkowiak; Marcin T. Brdyś

International Journal of Applied Mathematics and Computer Science (2009)

- Volume: 19, Issue: 2, page 337-348
- ISSN: 1641-876X

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topMietek A. Brdyś, et al. "Adaptive prediction of stock exchange indices by state space wavelet networks." International Journal of Applied Mathematics and Computer Science 19.2 (2009): 337-348. <http://eudml.org/doc/207940>.

@article{MietekA2009,

abstract = {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.},

author = {Mietek A. Brdyś, Adam Borowa, Piotr Idźkowiak, Marcin T. Brdyś},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {forecasting; stock exchange; artificial intelligence; state space wavelet network; simulated annealing},

language = {eng},

number = {2},

pages = {337-348},

title = {Adaptive prediction of stock exchange indices by state space wavelet networks},

url = {http://eudml.org/doc/207940},

volume = {19},

year = {2009},

}

TY - JOUR

AU - Mietek A. Brdyś

AU - Adam Borowa

AU - Piotr Idźkowiak

AU - Marcin T. Brdyś

TI - Adaptive prediction of stock exchange indices by state space wavelet networks

JO - International Journal of Applied Mathematics and Computer Science

PY - 2009

VL - 19

IS - 2

SP - 337

EP - 348

AB - 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.

LA - eng

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

UR - http://eudml.org/doc/207940

ER -

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