A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting
Alexander Vlasenko,
Nataliia Vlasenko,
Olena Vynokurova,
Yevgeniy Bodyanskiy,
Dmytro Peleshko
Affiliations
Alexander Vlasenko
Department of Artificial Intelligence, Faculty of Computer Science, Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
Nataliia Vlasenko
Department of Informatics and Computer Engineering, Faculty of Economic Informatics, Simon Kuznets Kharkiv National University of Economics, 61166 Kharkiv, Ukraine
Olena Vynokurova
Information Technology Department, IT Step University, 79019 Lviv, Ukraine
Yevgeniy Bodyanskiy
Department of Artificial Intelligence, Faculty of Computer Science, Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
Dmytro Peleshko
Information Technology Department, IT Step University, 79019 Lviv, Ukraine
Neuro-fuzzy models have a proven record of successful application in finance. Forecasting future values is a crucial element of successful decision making in trading. In this paper, a novel ensemble neuro-fuzzy model is proposed to overcome limitations and improve the previously successfully applied a five-layer multidimensional Gaussian neuro-fuzzy model and its learning. The proposed solution allows skipping the error-prone hyperparameters selection process and shows better accuracy results in real life financial data.
