TY - JOUR
T1 - Can Sentiment Analysis and Options Volume Anticipate Future Returns?
AU - Houlihan, Patrick
AU - Creamer, Germán G.
N1 - Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - This paper evaluates the question of whether sentiment extracted from social media and options volume anticipates future asset return. The research utilized both textual based data and a particular market data derived call-put ratio, collected between July 2009 and September 2012. It shows that: (1) features derived from market data and a call-put ratio can improve model performance, (2) sentiment derived from StockTwits, a social media platform for the financial community, further enhances model performance, (3) aggregating all features together also facilitates performance, and (4) sentiment from social media and market data can be used as risk factors in an asset pricing framework.
AB - This paper evaluates the question of whether sentiment extracted from social media and options volume anticipates future asset return. The research utilized both textual based data and a particular market data derived call-put ratio, collected between July 2009 and September 2012. It shows that: (1) features derived from market data and a call-put ratio can improve model performance, (2) sentiment derived from StockTwits, a social media platform for the financial community, further enhances model performance, (3) aggregating all features together also facilitates performance, and (4) sentiment from social media and market data can be used as risk factors in an asset pricing framework.
KW - Behavioral finance
KW - Investor sentiment
KW - Machine learning
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85019544023&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019544023&partnerID=8YFLogxK
U2 - 10.1007/s10614-017-9694-4
DO - 10.1007/s10614-017-9694-4
M3 - Article
AN - SCOPUS:85019544023
SN - 0927-7099
VL - 50
SP - 669
EP - 685
JO - Computational Economics
JF - Computational Economics
IS - 4
ER -