Micro-blog social moods and Chinese stock market: the influence of emotional valence and arousal on Shanghai Composite Index volume

被引：18

作者：

Dong, Ying-hong ^{[1
]}

Chen, Hao ^{[2
]}

Qian, Wei-ning ^{[3
]}

Zhou, Ao-ying ^{[3
]}

机构：

[1] Ludong Univ, Sch Educ Sci, Dept Psychol, Yantai 264025, Shandong, Peoples R China

[2] Nankai Univ, Zhou Enlai Sch Govt, Dept Social Psychol, 94 Weijin Rd, Tianjin 300071, Peoples R China

[3] East China Normal Univ, Software Engn Inst, 500 Dongchuan Rd, Shanghai 200241, Peoples R China

来源：

INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS | 2015年 / 7卷 / 02期

关键词：

micro-blog; social mood; emotion lexicon; SSEC; sadness; arousal; risk decision making; granger causality analysis; linear regression model; emotional maintenance hypothesis; China;

D O I：

10.1504/IJES.2015.069987

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Previous psychological researches prove that emotion is of importance in individual risk decision making. So could the public emotion (social moods) influence the collective risk decision making such as the stock market? We obtained the five basic social moods including happiness, sadness, fear, anger and disgust by analysing the text content of daily Sina Weibo using our emotion lexicon. Then we investigated the correlation between the daily social moods and Shanghai Composite Index volume by means of Granger causality analysis and linear regression model. We found sadness can significantly improve the predictive accuracy of the trading volume by 2.4% and reduce the MAPE by 8. The analyses for the five social moods indicated the arousal of sadness is the lowest, and the lowest 25% terms of sadness can predict the total trading amounts of SSEC too. The result indicated the negative emotion with lower arousal can improve the tendency of risk taking, which confirms emotional maintenance hypothesis in psychological discipline.

引用

页码：148 / 155

页数：8