The increasing attention on Bitcoin since 2013 prompts the issue of possible evidence for a causal relationship between the Bitcoin market and internet attention.Taking the Google search volume index as the measure of...The increasing attention on Bitcoin since 2013 prompts the issue of possible evidence for a causal relationship between the Bitcoin market and internet attention.Taking the Google search volume index as the measure of internet attention,time-varying Granger causality between the global Bitcoin market and internet attention is examined.Empirical results show a strong Granger causal relationship between internet attention and trading volume.Moreover,they indicate,beginning in early 2018,an even stronger impact of trading volume on internet attention,which is consistent with the rapid increase in Bitcoin users following the 2017 Bitcoin bubble.Although Bitcoin returns are found to strongly affect internet attention,internet attention only occasionally affects Bitcoin returns.Further investigation reveals that interactions between internet attention and returns can be amplified by extreme changes in prices,and internet attention is more likely to lead to returns during Bitcoin bubbles.These empirical findings shed light on cryptocurrency investor attention theory and imply trading strategy in Bitcoin markets.展开更多
This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of ...This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of lagged explanatory variables to be conditional on past information.Furthermore,a test for constant-parameter DL model is introduced.The model is then applied to examine time-varying causal effect of inventory on crude oil price and forecast weekly crude oil price.Time-varying causal effect of US commercial crude oil inventory on crude oil price return is presented.In particular,the causal effect of inventory is occasionally positive,which is contrary to some previous research.It’s also shown that the proposed model yields the best in and out-of-sample performances compared to seven alternative models including RW,ARMA,VAR,DL,autoregressive-distributed lag(ADL),time-varying parameter ADL(TVP-ADL)and DCB(dynamic conditional beta)models.展开更多
基金The paper received financial support from the National Natural Science Foundation of China(Nos.71422015,71871213)the National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of Sciences.
文摘The increasing attention on Bitcoin since 2013 prompts the issue of possible evidence for a causal relationship between the Bitcoin market and internet attention.Taking the Google search volume index as the measure of internet attention,time-varying Granger causality between the global Bitcoin market and internet attention is examined.Empirical results show a strong Granger causal relationship between internet attention and trading volume.Moreover,they indicate,beginning in early 2018,an even stronger impact of trading volume on internet attention,which is consistent with the rapid increase in Bitcoin users following the 2017 Bitcoin bubble.Although Bitcoin returns are found to strongly affect internet attention,internet attention only occasionally affects Bitcoin returns.Further investigation reveals that interactions between internet attention and returns can be amplified by extreme changes in prices,and internet attention is more likely to lead to returns during Bitcoin bubbles.These empirical findings shed light on cryptocurrency investor attention theory and imply trading strategy in Bitcoin markets.
基金National Natural Science Foundation of China(71871213)。
文摘This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of lagged explanatory variables to be conditional on past information.Furthermore,a test for constant-parameter DL model is introduced.The model is then applied to examine time-varying causal effect of inventory on crude oil price and forecast weekly crude oil price.Time-varying causal effect of US commercial crude oil inventory on crude oil price return is presented.In particular,the causal effect of inventory is occasionally positive,which is contrary to some previous research.It’s also shown that the proposed model yields the best in and out-of-sample performances compared to seven alternative models including RW,ARMA,VAR,DL,autoregressive-distributed lag(ADL),time-varying parameter ADL(TVP-ADL)and DCB(dynamic conditional beta)models.
