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ISSN : 2005-0461(Print)
ISSN : 2287-7975(Online)
Journal of Society of Korea Industrial and Systems Engineering Vol.41 No.3 pp.154-161
DOI : https://doi.org/10.11627/jkise.2018.41.3.154

A Prediction of Stock Price Through the Big-data Analysis

Ji Don Yu*, Ik Sun Lee**†
*Entrepreneurship Education Center, Gwangju Institute of Science and Technology
**Dept. of Business Administration, Dong-A University
Corresponding Author : lis1007@dau.ac.kr

Abstract

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model ① is low, and so the prediction performance of the model ① is relatively better than that of the prediction model ②. As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

인터넷 뉴스 빅데이터를 활용한 기업 주가지수 예측

유지돈*, 이익선**†
*광주과학기술원 혁신기업가교육센터
**동아대학교 경영학과

초록

 

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