Stock Prices Prediction using the Title of Newspaper Articles with Korean Natural Language Processing

Hyungbin Yun, Ghudae Sim, Junhee Seok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Non-quantitative data have a significant impact on the financial market as well as quantitative data. In this paper, we propose CNN model of stock price prediction using Korean natural language processing. In the case of Korean natural language processing research was not actively performed compared to English language. We converted Korean sentences into nouns and vectorized them using skip-grams to extract the characteristics of the words. Then, the vectorized word sentence was used as input data of the CNN model to predict the stock price after 5 days of trading day. Most models have more than 50% prediction accuracy for stock price up and down. The highest accuracy of the model was about 53%. Since the result is not considerable but meaningful, it shows the possibility of developing the stock price prediction model through Korean natural language processing in the future.

Original languageEnglish
Title of host publication1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages19-21
Number of pages3
ISBN (Electronic)9781538678220
DOIs
Publication statusPublished - 2019 Mar 18
Event1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019 - Okinawa, Japan
Duration: 2019 Feb 112019 Feb 13

Publication series

Name1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019

Conference

Conference1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019
CountryJapan
CityOkinawa
Period19/2/1119/2/13

Keywords

  • artificial neural network
  • convolution neural network
  • Korean natural language processing
  • skip-gram
  • stock price prediction

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Stock Prices Prediction using the Title of Newspaper Articles with Korean Natural Language Processing'. Together they form a unique fingerprint.

  • Cite this

    Yun, H., Sim, G., & Seok, J. (2019). Stock Prices Prediction using the Title of Newspaper Articles with Korean Natural Language Processing. In 1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019 (pp. 19-21). [8668996] (1st International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIIC.2019.8668996