A Wavelet Analysis of the Bitcoin- Hashrate Nexus Accounting for the Effects of Energy Commodities

This study investigates the relationship between the growth rates of Bitcoin and Bitcoin hashrate while controlling for the effect of energy commodities, specifically two-month futures on Brent crude oil, coal, and natural gas. Based on daily data from January 2013 until December 2022, we utilize the wavelet methodology to analyze dynamics both in time and frequency. Building on the previous work of Rehman and Kang (2021), this study extends the sample period and improves the replicability of their findings. Controlling for the effect of energy commodities, our analysis reveals several interesting results, highlighting the temporal and dynamic nature of these relationships. Our most significant observation that was discovered in both bi- and multivariate forms of the wavelet methodology is the low-frequency in-phase coherence between bitcoin's returns and hashrate growth rates, which persists from the beginning of 2020 until the end of our sample period in 2023, with hashrate growth rates leading bitcoin returns. These findings suggest that the link between the returns on bitcoin and hashrate growth rates while considering the impact of the energy commodities is complex and context-dependent, and further research is needed to fully understand the underlying mechanisms driving these relationships. Our study contributes to the existing literature on the Bitcoin-hashrate nexus by providing a more comprehensive analysis that accounts for the dynamic nature of these relationships, and by improving the replicability of previous research

A Wavelet Analysis of the Bitcoin-Hashrate Nexus Accounting for the Effects of Energy Commodities

This study investigates the relationship between the growth rates of Bitcoin and Bitcoin hashrate while controlling for the effect of energy commodities, specifically two-month futures on Brent crude oil, coal, and natural gas. Based on daily data from January 2013 until December 2022, we utilize the wavelet methodology to analyze dynamics both in time and frequency. Building on the previous work of Rehman and Kang (2021), this study extends the sample period and improves the replicability of their findings. Controlling for the effect of energy commodities, our analysis reveals several interesting results, highlighting the temporal and dynamic nature of these relationships. Our most significant observation that was discovered in both bi- and multivariate forms of the wavelet methodology is the low-frequency in-phase coherence between bitcoin's returns and hashrate growth rates, which persists from the beginning of 2020 until the end of our sample period in 2023, with hashrate growth rates leading bitcoin returns. These findings suggest that the link between the returns on bitcoin and hashrate growth rates while considering the impact of the energy commodities is complex and context-dependent, and further research is needed to fully understand the underlying mechanisms driving these relationships. Our study contributes to the existing literature on the Bitcoin-hashrate nexus by providing a more comprehensive analysis that accounts for the dynamic nature of these relationships, and by improving the replicability of previous research