Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F19%3APU135002" target="_blank" >RIV/00216305:26510/19:PU135002 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Conference Proceedings DOKBAT 15th Annual International Bata Conference for Ph.D. Students and Young Researchers

ISBN

978-80-7454-893-2

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

457-465

Název nakladatele

Tomas Bata University of Zlin

Místo vydání

Zlin, Czech Republic

Místo konání akce

Zlín

Datum konání akce

6. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000692876300044