Social sentiment and stock trading via mobile phones

• Main Authors: KIM, Kwansoo, LEE, Sang Yong, KAUFFMAN, Robert John
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Econometric analysis; herding behavior; investor reactions; machine learning; mobile channel; socialmedia; social sentiment; stock trading; uninformed traders; value traders.; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/3603; https://ink.library.smu.edu.sg/context/sis_research/article/4604/viewcontent/Social_Sentiment_and_Stock_Trading_via_Mobile_Phones.pdf
• Institution: Singapore Management University

What happens when uninformed investors trade stocks via mobile phones? Do they react to social sentiment differently than more informed traders in traditional trading? Based on 16,817 data observations and econometric analysis for the trading of 251 equities in Korea over 39 days, we present evidence of herding behavior among uninformed traders in the mobile channel. The results indicate that mobile traders seem more easily swayed by changing social sentiment. In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. Mobile traders follow signals in social media suggesting that they engage in less beneficial herding behavior, based on evidence that we obtained for the occurrence of more negative feedback trading. This allows us to offer a new interpretation of how mobile channel stock trading works, and open a new portal for analytics with digital data related to the trading behavior of different investors.