Detailed Information on Publication Record
2016
FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS
MARČEK, DušanBasic information
Original name
FORECASTING FINANCIAL DATA: A COMBINED MODEL OF FUZZY NEURAL NETWORK AND STATISTICS
Authors
MARČEK, Dušan (703 Slovakia, guarantor, belonging to the institution)
Edition
Volume 10. Singapore, Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference (FLINS 2016), p. 1137-1142, 6 pp. 2016
Publisher
World Scientific Publishing
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
20205 Automation and control systems
Country of publisher
Singapore
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/47813059:19240/16:A0000126
Organization unit
Faculty of Philosophy and Science in Opava
ISBN
978-981-314-698-3
UT WoS
000417158200175
Keywords in English
Financial Data Forecasting; Fuzzy neural network; Statistical modelling; Combined model
Tags
Tags
International impact, Reviewed
Links
LQ1602, research and development project.
Změněno: 7/1/2020 11:14, Mgr. Kamil Matula, Ph.D.
Abstract
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.