TY - JOUR
T1 - Does Twitter Happiness Sentiment predict cryptocurrency?
AU - Naeem, Muhammad Abubakr
AU - Mbarki, Imen
AU - Suleman, Muhammed Tahir
AU - Vo, Xuan Vinh
AU - Shahzad, Syed Jawad Hussain
N1 - Publisher Copyright:
© 2020 International Review of Finance Ltd. 2020
PY - 2021/12
Y1 - 2021/12
N2 - We examine the predictive ability of Twitter Happiness Sentiment for six major cryptocurrencies using daily data from August 7, 2015 to December 31, 2019. At first instance, our results conclude a significant nonlinear relationship between Twitter Happiness Sentiment and cryptocurrencies. The nonlinear dependence structure is further enhanced when using the quantile-on-quantile (QQ) analysis, which indicates that high and low sentiment predicts returns of five cryptocurrencies. These findings are statistically and economically significant.
AB - We examine the predictive ability of Twitter Happiness Sentiment for six major cryptocurrencies using daily data from August 7, 2015 to December 31, 2019. At first instance, our results conclude a significant nonlinear relationship between Twitter Happiness Sentiment and cryptocurrencies. The nonlinear dependence structure is further enhanced when using the quantile-on-quantile (QQ) analysis, which indicates that high and low sentiment predicts returns of five cryptocurrencies. These findings are statistically and economically significant.
KW - cryptocurrencies
KW - linear and nonlinear Granger causality
KW - quantile-on-quantile
KW - Twitter Happiness Sentiment
UR - http://www.scopus.com/inward/record.url?scp=85097621299&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097621299&partnerID=8YFLogxK
U2 - 10.1111/irfi.12339
DO - 10.1111/irfi.12339
M3 - Article
AN - SCOPUS:85097621299
SN - 1369-412X
VL - 21
SP - 1529
EP - 1538
JO - International Review of Finance
JF - International Review of Finance
IS - 4
ER -