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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University of Novi Sad - Faculty of Economics, Subotica
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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 |
work_keys_str_mv |
AT stankovicjelenaz trendpredictionofthebelex15indexanditsconstituentsusinglssvm AT markovicivana trendpredictionofthebelex15indexanditsconstituentsusinglssvm AT radovicognjen trendpredictionofthebelex15indexanditsconstituentsusinglssvm |
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