FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL
NETWORK AND STATISTICS

D 2016

FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS

MARČEK, Dušan

Základní údaje

Originální název

FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS

Autoři

MARČEK, Dušan (703 Slovensko, garant, domácí)

Vydání

Volume 10. Singapore, Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference (FLINS 2016), od s. 1137-1142, 6 s. 2016

Nakladatel

World Scientific Publishing

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20205 Automation and control systems

Stát vydavatele

Singapur

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/47813059:19240/16:A0000126

Organizační jednotka

Filozoficko-přírodovědecká fakulta v Opavě

ISBN

978-981-314-698-3

DOI

http://dx.doi.org/10.1142/9789813146976_0175

UT WoS

000417158200175

Klíčová slova anglicky

Financial Data Forecasting; Fuzzy neural network; Statistical modelling; Combined model

Štítky

ÚI

Příznaky

Mezinárodní význam, Recenzováno

Návaznosti

LQ1602, projekt VaV.

Změněno: 7. 1. 2020 11:14, Mgr. Kamil Matula, Ph.D.

Anotace

V originále

In this paper, we apply the ARMA/ARCH methodology to develop forecasting models and compare their forecast accuracy with a class of novel hybrid fuzzy logic RBF neural network models. The used novel approach deals with nonlinear estimate of various RBF NN-based ARMA/GARCH methodologies. Our results show that the proposed approach achieves better forecast accuracy on the validation dataset than most available techniques.

Citovat

MARČEK, Dušan. FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS. Online. In ZENG, Xianyi; LU, Jie; KERRE, Etienne E.; MARTINEZ, Luis; KOEHL, Ludovic. Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference (FLINS 2016). Volume 10. Singapore: World Scientific Publishing, 2016, s. 1137-1142. ISBN 978-981-314-698-3. Dostupné z: https://dx.doi.org/10.1142/9789813146976_0175.

@inproceedings{29811,
   author = {Marček, Dušan},
   address = {Singapore},
   booktitle = {Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference (FLINS 2016)},
   doi = {http://dx.doi.org/10.1142/9789813146976_0175},
   edition = {Volume 10},
   editor = {ZENG, Xianyi; LU, Jie; KERRE, Etienne E.; MARTINEZ, Luis; KOEHL, Ludovic},
   keywords = {Financial Data Forecasting; Fuzzy neural network; Statistical modelling; Combined model},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Singapore},
   isbn = {978-981-314-698-3},
   pages = {1137-1142},
   publisher = {World Scientific Publishing},
   title = {FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS},
   year = {2016}
}

TY  - JOUR
ID  - 29811
AU  - Marček, Dušan
PY  - 2016
TI  - FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS
PB  - World Scientific Publishing
CY  - Singapore
SN  - 9789813146983
KW  - Financial Data Forecasting
KW  - Fuzzy neural network
KW  - Statistical modelling
KW  - Combined model
N2  - In this paper, we apply the ARMA/ARCH methodology to develop forecasting models and compare their forecast accuracy with a class of novel hybrid fuzzy logic RBF neural network models. The used novel approach deals with nonlinear estimate of various RBF NN-based ARMA/GARCH methodologies. Our results show that the proposed approach achieves better forecast accuracy on the validation dataset than most available techniques.
ER  -

MARČEK, Dušan. FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS. Online. In ZENG, Xianyi; LU, Jie; KERRE, Etienne E.; MARTINEZ, Luis; KOEHL, Ludovic. \textit{Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference (FLINS 2016)}. Volume 10. Singapore: World Scientific Publishing, 2016, s.~1137-1142. ISBN~978-981-314-698-3. Dostupné z: https://dx.doi.org/10.1142/9789813146976\_{}0175.

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