In Oil Price and the Bitcoin Market, Afees Salisu et. al. examine whether movements in global oil prices help explain changes in Bitcoin’s market volatility. Using daily data from January 2017 to June 2022, the study finds a statistically significant inverse relationship between oil prices and Bitcoin volatility; periods of higher oil prices tend to coincide with lower volatility in the Bitcoin market.
The study asks whether oil prices contain useful information for predicting the realized volatility of Bitcoin returns. The authors start from the role of energy in Bitcoin mining. Because mining relies on electricity and other energy inputs, changes in energy costs may influence mining activity and broader market behavior. Oil prices are therefore treated as an indicator of shifts in global energy costs that could indirectly affect the Bitcoin market.
This dynamic is particularly relevant in Africa, where Bitcoin mining may benefit from access to low-cost energy sources such as hydropower, solar, geothermal, and other forms of stranded energy. In these environments, energy availability can become a competitive factor shaping the economics of mining operations.
The analysis combines Bitcoin volatility data with two global oil benchmarks—Brent and West Texas Intermediate (WTI). Bitcoin volatility is measured using a 20-day realized volatility metric derived from daily returns. The authors estimate a forecasting model designed to account for common features of financial data such as persistence, volatility clustering, and structural breaks. They then test whether including oil prices improves predictions of Bitcoin volatility both within the sample and in out-of-sample forecasts.
The results show that models incorporating oil price information outperform benchmark models that exclude oil prices when forecasting Bitcoin volatility. For investors and analysts, this suggests that developments in oil markets may provide additional signals when assessing risk in Bitcoin markets.
The paper contributes to research on the relationship between energy markets and cryptocurrencies by focusing on predictability and forecasting, rather than only examining volatility spillovers or hedging relationships.
Some limitations should be noted. The model does not directly measure mining energy use or mining costs, relying instead on oil prices as a proxy for energy inputs. This means the mechanism linking oil prices to Bitcoin volatility is inferred rather than directly tested. The study also covers a limited period of Bitcoin’s market history.
Overall, the study underscores the potential role of energy market dynamics in shaping Bitcoin market behavior. For African mining operators and investors, where energy costs and access vary significantly across countries, these findings add a practical layer to risk assessment as the bitcoin ecosystem matures.