Open AccessWeibo sentiments and stock return: A time-frequency view
Author(s) -
Yingying Xu,
Zhixin Liu,
Jichang Zhao,
ChiWei Su
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0180723
Subject(s) - sadness , social media , microblogging , stock (firearms) , stock market , disgust , economics , abnormal return , sentiment analysis , financial economics , stock exchange , econometrics , business , anger , monetary economics , computer science , psychology , finance , artificial intelligence , social psychology , world wide web , biology , mechanical engineering , paleontology , horse , engineering
This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter’s variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which have both frequency and time-varying features. Five detailed sentiments are positively related to the stock return for certain periods, particularly since October 2014 at medium to high frequencies of less than ten trading days, when the stock return is undergoing significant fluctuations. Sadness appears to have a closer relationship with the stock return than the other four sentiments. As to the lead-lag relationships, the stock return causes Weibo sentiments rather than reverse for most of the periods with significant linkages. Compared with polarity sentiments (negative vs . positive), detailed sentiments provide more information regarding relationships between Weibo sentiments and the stock market. The stock market exerts positive effects on bullishness and agreement of microblogs. Meanwhile, agreement leads the stock return in-phase at the frequency of approximately 40 trading days, indicating that less disagreement improves certainty about the stock market.