Analyzing the Time-Frequency Lead-Lag Relationship between Bitcoin and Currencies Markets

This study examines the co-movement and lead-lag casuality relationship between the bitcoin and five currencies using wavelet methods. This study focuses on the dependence and casuality relationships in different time scales (short-term, intermediate-term, and long-term scales). The wavelet method results provide three implications: (1) The continuos wavelet power analysis shows that bitcoin returns has a high power in the short and intermediate-term scales over the period from mid-2011 to 2014. (2) The cross wavelet power transformation indicates the strong covariances between bitcoin and currency returns over the periods from mid-2011 to 2014, and this covariance decayed. (3) The wavelet coherence results identify a high level of co-movement between the bitcoin and currency returns at intermediate and long-term scales and bitcoin leading CNY, JPY, and USDX (as arrows approach to the right and up) over periods 2017-2018. Therefore, we find the co-movement and lead-lag causability relationships between bitcoin and currency markets.