Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Stock Market Prediction Using Sentiment on YouTube Channels

유튜브 주식채널의 감성을 활용한 코스피 수익률 등락 예측

  • Su-Ji, Cho (School of Business Administration, Dankook University) ;
  • Cheol-Won Yang (School of Business Administration, Dankook University) ;
  • Ki-Kwang Lee (School of Business Administration, Dankook University)
  • Received : 2023.05.24
  • Accepted : 2023.06.08
  • Published : 2023.06.30
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Abstract

Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

Keywords

Acknowledgement

This paper was supported by the research fund of the National Research Foundation of Korea (NRF-2019S1A5 A2A03038389).

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