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http://dx.doi.org/10.5351/KJAS.2020.33.4.483

Prediction of stock prices using deep neural network models including an emotional predictor based on online news by industrial groups  

Lim, Jun Hyeong (Department of Statistics, Chonnam National University)
Son, Young Sook (Department of Statistics, Chonnam National University)
Publication Information
The Korean Journal of Applied Statistics / v.33, no.4, 2020 , pp. 483-497 More about this Journal
Abstract
We used a deep neural network model for the prediction of the stock prices of Kia Motors and Shinsegae as listed in the KOSPI 100. We used an emotional variable derived from online news in addition to the various technical indicators most often used. The emotional variable used as a predictor variable was generated from the average of the emotional scores for companies in the industrial group after building an emotional dictionary specific to each industrial group classified in a social network analysis. The study was conducted with various combinations of predictors and confirmed that good predictive and profitable power could be expected when jointly using technical indicators and an emotional variable based on online news by industrial groups.
Keywords
prediction of stock prices; deep neural network; social network analysis; online news; emotional variable;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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1 Choi, I. J. (2016). Prediction of stock fluctuation using web news text mining, Pukyong National University Master's Thesis.
2 Jeong, J. S., Kim, D. S., and Kim, J. W. (2015). Influence analysis of internet buzz to corporate performance:individual stock price prediction using sentiment analysis of online news, Journal of Intelligence and Information Systems, 21, 37-51.   DOI
3 Kim, D. Y. and Lee, Y. I. (2018). News based Stock Market Sentiment Lexicon Acquisition UsingWord2Vec, The Korean Journal of Bigdata, 3, 13-20.   DOI
4 Kim, J. B. and Kim, H. J. (2017). A domain-specific sentiment lexicon construction method for stock index directionality, Journal of Digital Contents Society, 18, 585-592.   DOI
5 Kim, Y. S. (2012). News big data opinion mining model for predicting KOSPI movement, Kookmin University Master's Thesis.
6 Lee, M. and Lee, H. J. (2017). Stock price prediction by utilizing category neutral terms: text mining approach, Journal of Intelligence and Information Systems, 23, 123-138.   DOI
7 Manning, C. D., Raghavan, P., and Schutze, H. (2009). Introduction to Information Retrieval: Scoring, term weighting, and the vector space model, Cambridge University Press.
8 Seong, N. and Nam, K. (2018). Online news-based stock price forecasting considering homogeneity in the industrial sector, Journal of Intelligence and Information Systems, 24, 1-19.
9 Shynkevich, Y., McGinnity, T. M., Coleman, S. A., and Belatreche, A. (2016). Forecasting movements of health-care stock prices based on different categories of news articles using multiple kernel learning, Decision Support Systems, 85, 74-83.   DOI