Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86094757" target="_blank" >RIV/61989100:27510/15:86094757 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.eswa.2015.08.010" target="_blank" >http://dx.doi.org/10.1016/j.eswa.2015.08.010</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2015.08.010" target="_blank" >10.1016/j.eswa.2015.08.010</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick

Popis výsledku v původním jazyce

Predicting stock prices is an importanto bjective in the financial world. This paper presents a novel forecasting model for stock markets on the basis of the wrapper ANFIS (Adaptive Neural Fuzzy Inference System) -ICA (Imperialist Competitive Algorithm)and technical analysis of Japanese Candlestick. Two approaches of Raw-based and Signal-based are devised to extract the model's input variables with 15 and 24 features, respectively. The correct predictions percentages for periods of 1-6 days with the total number of buy and sell signals are considered as output variables. In proposed model, the ANFIS prediction results are used as a cost function of wrapper model and ICA isused to select the most appropriate features. This novel combination of featureselection not only takes advantage of ICA optimization swiftness, but also the ANFIS prediction accuracy. The emitted buy and sell signals of the model revealed that Signal databases approach gets better results with 87% prediction accura

Název v anglickém jazyce

Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick

Popis výsledku anglicky

Predicting stock prices is an importanto bjective in the financial world. This paper presents a novel forecasting model for stock markets on the basis of the wrapper ANFIS (Adaptive Neural Fuzzy Inference System) -ICA (Imperialist Competitive Algorithm)and technical analysis of Japanese Candlestick. Two approaches of Raw-based and Signal-based are devised to extract the model's input variables with 15 and 24 features, respectively. The correct predictions percentages for periods of 1-6 days with the total number of buy and sell signals are considered as output variables. In proposed model, the ANFIS prediction results are used as a cost function of wrapper model and ICA isused to select the most appropriate features. This novel combination of featureselection not only takes advantage of ICA optimization swiftness, but also the ANFIS prediction accuracy. The emitted buy and sell signals of the model revealed that Signal databases approach gets better results with 87% prediction accura

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Expert Systems with Applications

ISSN

0957-4174

e-ISSN

—

Svazek periodika

42

Číslo periodika v rámci svazku

23

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9235

Strana od-do

9221

Kód UT WoS článku

000362613000013

EID výsledku v databázi Scopus

2-s2.0-84940973455