Stock market movement prediction using LDA-online learning model
© 2018 IEEE. In this paper, an online learning method namely LDA-Online algorithm is proposed to predict the stock movement. The feature set which are the opening price, the closing price, the highest price and the lowest price are applied to fit the Linear Discriminant Analysis (LDA). Experiments o...
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th-mahidol.456002019-08-23T18:29:54Z Stock market movement prediction using LDA-online learning model Tanapon Tantisripreecha Nuanwan Soonthomphisaj Kasetsart University Mahidol University Computer Science Decision Sciences Mathematics © 2018 IEEE. In this paper, an online learning method namely LDA-Online algorithm is proposed to predict the stock movement. The feature set which are the opening price, the closing price, the highest price and the lowest price are applied to fit the Linear Discriminant Analysis (LDA). Experiments on the four well known NASDAQ stocks (APPLE, FACBOOK GOOGLE, and AMAZON) show that our model provide the best performance in stock prediction. We compare LDA-online to ANN, KNN and Decision Tree in both Batch and Online learning scheme. We found that LDA-Online provided the best performance. The highest performances measured on GOOGLE, AMAZON, APPLE FACEBOOK stocks are 97.81%, 97.64%, 95.58% and 95.18% respectively. 2019-08-23T10:55:42Z 2019-08-23T10:55:42Z 2018-08-20 Conference Paper Proceedings - 2018 IEEE/ACIS 19th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018. (2018), 135-139 10.1109/SNPD.2018.8441038 2-s2.0-85053526710 https://repository.li.mahidol.ac.th/handle/123456789/45600 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053526710&origin=inward |
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Mahidol University Library |
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Asia |
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Computer Science Decision Sciences Mathematics |
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Computer Science Decision Sciences Mathematics Tanapon Tantisripreecha Nuanwan Soonthomphisaj Stock market movement prediction using LDA-online learning model |
| description |
© 2018 IEEE. In this paper, an online learning method namely LDA-Online algorithm is proposed to predict the stock movement. The feature set which are the opening price, the closing price, the highest price and the lowest price are applied to fit the Linear Discriminant Analysis (LDA). Experiments on the four well known NASDAQ stocks (APPLE, FACBOOK GOOGLE, and AMAZON) show that our model provide the best performance in stock prediction. We compare LDA-online to ANN, KNN and Decision Tree in both Batch and Online learning scheme. We found that LDA-Online provided the best performance. The highest performances measured on GOOGLE, AMAZON, APPLE FACEBOOK stocks are 97.81%, 97.64%, 95.58% and 95.18% respectively. |
| author2 |
Kasetsart University |
| author_facet |
Kasetsart University Tanapon Tantisripreecha Nuanwan Soonthomphisaj |
| format |
Conference or Workshop Item |
| author |
Tanapon Tantisripreecha Nuanwan Soonthomphisaj |
| author_sort |
Tanapon Tantisripreecha |
| title |
Stock market movement prediction using LDA-online learning model |
| title_short |
Stock market movement prediction using LDA-online learning model |
| title_full |
Stock market movement prediction using LDA-online learning model |
| title_fullStr |
Stock market movement prediction using LDA-online learning model |
| title_full_unstemmed |
Stock market movement prediction using LDA-online learning model |
| title_sort |
stock market movement prediction using lda-online learning model |
| publishDate |
2019 |
| url |
https://repository.li.mahidol.ac.th/handle/123456789/45600 |
| _version_ |
1763495156329218048 |