Publication: Predict the stock exchange of Thailand-Set
dc.contributor.author | Warut Sirijunyapong | en_US |
dc.contributor.author | Adisorn Leelasantitham | en_US |
dc.contributor.author | Supapogrn Kiattisin | en_US |
dc.contributor.author | Waranyu Wongseree | en_US |
dc.contributor.other | Mahidol University | en_US |
dc.contributor.other | King Mongkut's University of Technology North Bangkok | en_US |
dc.date.accessioned | 2018-11-09T02:16:20Z | |
dc.date.available | 2018-11-09T02:16:20Z | |
dc.date.issued | 2014-01-01 | en_US |
dc.description.abstract | This paper proposes an investment in the stock exchange of Thailand (SET) using ARIMA model and support vector machine. Today, the investors are interesting to invest the stock market because it provides for higher profits than ones from deposit banking. Although the stock market can provide a high benefit for investors, it comes with a high risk too. Thus, this is a reason why we are proposing ARIMA model and Support vector machine. ARIMA model is one of the most popular approaches to forecast. Support vector machine is the structure of minimization of risk and supports high dimension data. Both of them can be reduced a risk to investors before their decisions to invest on stocks. © 2014 IEEE. | en_US |
dc.identifier.citation | JICTEE 2014 - 4th Joint International Conference on Information and Communication Technology, Electronic and Electrical Engineering. (2014) | en_US |
dc.identifier.doi | 10.1109/JICTEE.2014.6804126 | en_US |
dc.identifier.other | 2-s2.0-84901020613 | en_US |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/33877 | |
dc.rights | Mahidol University | en_US |
dc.rights.holder | SCOPUS | en_US |
dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901020613&origin=inward | en_US |
dc.subject | Engineering | en_US |
dc.title | Predict the stock exchange of Thailand-Set | en_US |
dc.type | Conference Paper | en_US |
dspace.entity.type | Publication | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901020613&origin=inward | en_US |