Evaluation Of The Degree Of Uncertainty In The Type-2 Fuzzy Logic System For Forecasting Stock Index

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F22%3APU146749" target="_blank" >RIV/00216305:26510/22:PU146749 - isvavai.cz</a>

Výsledek na webu

<a href="https://ipe.ro/rjef.htm" target="_blank" >https://ipe.ro/rjef.htm</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Evaluation Of The Degree Of Uncertainty In The Type-2 Fuzzy Logic System For Forecasting Stock Index

Popis výsledku v původním jazyce

The paper deals with investment analysis based on a new fuzzy methodology. Specifically, the interval type-2 fuzzy logic model is created to support decision-making for investors, financial analysts and brokers. The model is demonstrated on the time series of the leading stock index S&P 500 of the US market. Type-2 fuzzy logic membership features are able to include additional uncertainty resulting from unclear, uncertain or inaccurate financial data that are selected as inputs to the model.The paper deals mainly with the evaluation and comparison of different degrees of uncertainty of the functions of the membership of input variables. Several model situations with different levels of inaccuracy are created. Based on the results of the comparison, it can be said that the type-2 fuzzy logic with dual membership functions is able to better describe data from financial time series.

Název v anglickém jazyce

Evaluation Of The Degree Of Uncertainty In The Type-2 Fuzzy Logic System For Forecasting Stock Index

Popis výsledku anglicky

The paper deals with investment analysis based on a new fuzzy methodology. Specifically, the interval type-2 fuzzy logic model is created to support decision-making for investors, financial analysts and brokers. The model is demonstrated on the time series of the leading stock index S&P 500 of the US market. Type-2 fuzzy logic membership features are able to include additional uncertainty resulting from unclear, uncertain or inaccurate financial data that are selected as inputs to the model.The paper deals mainly with the evaluation and comparison of different degrees of uncertainty of the functions of the membership of input variables. Several model situations with different levels of inaccuracy are created. Based on the results of the comparison, it can be said that the type-2 fuzzy logic with dual membership functions is able to better describe data from financial time series.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50204 - Business and management

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Romanian Journal of Economic Forecasting

ISSN

1582-6163

e-ISSN

2537-6071

Svazek periodika

25

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

RO - Rumunsko

Počet stran výsledku

17

Strana od-do

41-57

Kód UT WoS článku

000920228000003

EID výsledku v databázi Scopus

2-s2.0-85146382154