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  • In this paper we apply neural network with denoising layer method for forecasting of Central European Stock Exchanges, namely Prague, Budapest and Warsaw. Hard threshold denoising with Daubechies 6 wavelet filter and three level decomposition is used to denoise the stock index returns, and two-layer feed-forward neural network with Levenberg-Marquardt learning algorithm is used for modeling. The results show that wavelet network structure is able to approximate the underlying process of considered stock markets better that multilayered neural network architecture without using wavelets. Further on we discuss the impact of structural changes of the market on forecasting accuracy, and we find that for certain periods the one-step-ahead prediction accuracy of the direction of the stock index can reach 60% to 70%.
  • In this paper we apply neural network with denoising layer method for forecasting of Central European Stock Exchanges, namely Prague, Budapest and Warsaw. Hard threshold denoising with Daubechies 6 wavelet filter and three level decomposition is used to denoise the stock index returns, and two-layer feed-forward neural network with Levenberg-Marquardt learning algorithm is used for modeling. The results show that wavelet network structure is able to approximate the underlying process of considered stock markets better that multilayered neural network architecture without using wavelets. Further on we discuss the impact of structural changes of the market on forecasting accuracy, and we find that for certain periods the one-step-ahead prediction accuracy of the direction of the stock index can reach 60% to 70%. (en)
  • Vlnové neurálních sítě předvídající centrální evropský trh s cennými papíry (cs)
Title
  • Wavelet Neural Networks Prediction of Central European Stock Markets
  • Vlnové neurálních sítě předvídající centrální evropský trh s cennými papíry (cs)
  • Wavelet Neural Networks Prediction of Central European Stock Markets (en)
skos:prefLabel
  • Wavelet Neural Networks Prediction of Central European Stock Markets
  • Vlnové neurálních sítě předvídající centrální evropský trh s cennými papíry (cs)
  • Wavelet Neural Networks Prediction of Central European Stock Markets (en)
skos:notation
  • RIV/67985556:_____/08:00311416!RIV09-GA0-67985556
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA402/06/1417), P(GP402/08/P207), S, Z(AV0Z10750506), Z(MSM0021620841)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 405566
http://linked.open...ai/riv/idVysledku
  • RIV/67985556:_____/08:00311416
http://linked.open...riv/jazykVysledku
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  • neural networks; hard threshold denoising; wavelets (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B0730C203B60]
http://linked.open...v/mistoKonaniAkce
  • Tatranská Lomnica
http://linked.open...i/riv/mistoVydani
  • Bratislava
http://linked.open...i/riv/nazevZdroje
  • Quantitative Methods in Economics: Multiple Criteria Decision making XIV
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Baruník, Jozef
  • Vácha, Lukáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Ekonomická univerzita v Bratislave
https://schema.org/isbn
  • 978-80-8078-217-7
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