ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) FOR FORECASTING: THE CASE OF THE CZECH STOCK MARKET

被引：0
|
作者：
Jankova, Zuzana [1 ]
机构：
[1] Brno Univ Technol, Fac Business & Management, Kolejni 2906-4, Brno 61200, Czech Republic
来源：
15TH ANNUAL INTERNATIONAL BATA CONFERENCE FOR PH.D. STUDENTS AND YOUNG RESEARCHERS (DOKBAT) | 2019年
关键词：
ANFIS; financial market; fuzzy logic; neural networks; soft computing; PREDICTION;
D O I：
10.7441/dokbat.2019.045
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
The paper discusses the use of an adaptive neuro-fuzzy inference system (ANFIS) for modelling and forecasting the return of stock index in a typical financial market. Artificial intelligence models are suitable for modelling systems of complex, dynamic and non-linear relationships common in financial markets. Forecasting is performed for the PX stock index listed on the exchange of the Czech Republic with five selected variables demonstrating high interdependence with the selected index. Based on the research results it can be stated that the proposed ANFIS model is an effective system for forecasting financial time series even in a market with limited liquidity and effectiveness such as the Czech stock market.
引用
收藏
页码：457 / 465
页数：9
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