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Stock market movement prediction using LDA-online learning model

  • Tanapon Tantisripreecha
  • , Nuanwan Soonthomphisaj
  • Mahidol University
  • Kasetsart University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE/ACIS 19th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018
EditorsHa Jin Hwang, Lizhi Cai, Gun Huck Yeom, Tokuro Matsuo, Haeng Kon Kim, Hyun Yeo, Chung Sun Hong, Naoki Fukuta, Takayuki Ito, Huaikou Miao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages135-139
Number of pages5
ISBN (Print)9781538658895
DOIs
Publication statusPublished - 20 Aug 2018
Externally publishedYes
Event19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018 - Busan, Korea, Republic of
Duration: 27 Jun 2018 → 29 Jun 2018

Publication series

NameProceedings - 2018 IEEE/ACIS 19th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018

Conference

Conference19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018
Country/TerritoryKorea, Republic of
CityBusan
Period27/06/18 → 29/06/18

Keywords

  • LDA
  • Online learning
  • Stock movement prediction

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