Trend prediction of the Belex15 index and its constituents using LS-SVM

Achieving profit through investing in the capital market is based on the ability to successfully predict future movements of the financial asset prices. Thus, the constant interest of investors in this particular field and emerging financial markets comes as no surprise, since these markets have bee...

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Main Authors: Stanković Jelena Z., Marković Ivana, Radović Ognjen
Format: Article
Language:English
Published: University of Novi Sad - Faculty of Economics, Subotica 2015-01-01
Series:Anali Ekonomskog fakulteta u Subotici
Subjects:
Online Access:https://scindeks-clanci.ceon.rs/data/pdf/0350-2120/2015/0350-21201534251S.pdf
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spelling doaj-53cf796a167a4fdc8397d15ac9c161a92021-03-23T13:09:10ZengUniversity of Novi Sad - Faculty of Economics, SuboticaAnali Ekonomskog fakulteta u Subotici0350-21202683-41622015-01-012015342512640350-21201534251STrend prediction of the Belex15 index and its constituents using LS-SVMStanković Jelena Z.0https://orcid.org/0000-0002-9875-9861Marković Ivana1Radović Ognjen2Univerzitet u Nišu, Ekonomski fakultet, SerbiaUniverzitet u Nišu, Ekonomski fakultet, SerbiaUniverzitet u Nišu, Ekonomski fakultet, SerbiaAchieving profit through investing in the capital market is based on the ability to successfully predict future movements of the financial asset prices. Thus, the constant interest of investors in this particular field and emerging financial markets comes as no surprise, since these markets have been a relevant alternative source of investment opportunities for international investors. Our empirical study focuses on such an emerging market, the Belgrade stock exchange. Our main goal was to predict the direction of change of the Belex15 index and its most significant constituents. Firstly, we conducted detailed analysis of the most significant constituents of Belex15 index. Further analysis was realized using the Least Square Support Vector Machine (LS-SVMs) as a trend prediction model whereby feature selection was carried out through the analysis of technical indicators. The test results indicated that the proposed model gives better results for the constituents than for the Belex15 index itself.https://scindeks-clanci.ceon.rs/data/pdf/0350-2120/2015/0350-21201534251S.pdfls-svm classificationemerging marketsbelex15stock market prediction
collection DOAJ
language English
format Article
sources DOAJ
author Stanković Jelena Z.
Marković Ivana
Radović Ognjen
spellingShingle Stanković Jelena Z.
Marković Ivana
Radović Ognjen
Trend prediction of the Belex15 index and its constituents using LS-SVM
Anali Ekonomskog fakulteta u Subotici
ls-svm classification
emerging markets
belex15
stock market prediction
author_facet Stanković Jelena Z.
Marković Ivana
Radović Ognjen
author_sort Stanković Jelena Z.
title Trend prediction of the Belex15 index and its constituents using LS-SVM
title_short Trend prediction of the Belex15 index and its constituents using LS-SVM
title_full Trend prediction of the Belex15 index and its constituents using LS-SVM
title_fullStr Trend prediction of the Belex15 index and its constituents using LS-SVM
title_full_unstemmed Trend prediction of the Belex15 index and its constituents using LS-SVM
title_sort trend prediction of the belex15 index and its constituents using ls-svm
publisher University of Novi Sad - Faculty of Economics, Subotica
series Anali Ekonomskog fakulteta u Subotici
issn 0350-2120
2683-4162
publishDate 2015-01-01
description Achieving profit through investing in the capital market is based on the ability to successfully predict future movements of the financial asset prices. Thus, the constant interest of investors in this particular field and emerging financial markets comes as no surprise, since these markets have been a relevant alternative source of investment opportunities for international investors. Our empirical study focuses on such an emerging market, the Belgrade stock exchange. Our main goal was to predict the direction of change of the Belex15 index and its most significant constituents. Firstly, we conducted detailed analysis of the most significant constituents of Belex15 index. Further analysis was realized using the Least Square Support Vector Machine (LS-SVMs) as a trend prediction model whereby feature selection was carried out through the analysis of technical indicators. The test results indicated that the proposed model gives better results for the constituents than for the Belex15 index itself.
topic ls-svm classification
emerging markets
belex15
stock market prediction
url https://scindeks-clanci.ceon.rs/data/pdf/0350-2120/2015/0350-21201534251S.pdf
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AT markovicivana trendpredictionofthebelex15indexanditsconstituentsusinglssvm
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