A MULTIVARIATE INVESTIGATION OF LIQUIDITY, MINING INCENTIVES, AND LONG-RUN EQUILIBRIUM RELATIONSHIPS FOR BITCOIN - Mustapha, Abdulrasaq (J-MACC : journal of management and accounting, 2026)
This study examines the determinants of Bitcoin returns by integrating blockchain network fundamentals and market activity indicators within a multivariate econometric framework. Using a time-series approach grounded in the Efficient Market Hypothesis and cointegration theory, the analysis investigates how trading volume, mining difficulty, hash rate, transaction fees, and confirmed payments jointly influence Bitcoin price dynamics. The study used monthly frequency series from 2014:M1 to 2025:M12. The empirical strategy employs unit root testing, Johansen cointegration analysis, and a Vector Error Correction Model to capture both short-run fluctuations and long-run equilibrium relationships. The findings reveal that Bitcoin returns are significantly driven by trading volume, transaction fees, and network usage, while hash rate exhibits a negative effect due to mining cost pressures. Cointegration results confirm long-run equilibrium among variables, and the error correction term indicates rapid adjustment toward stability. Overall, the study highlights Bitcoin’s hybrid nature, driven by both speculative behavior and structural blockchain fundamentals, offering important implications for investors and policymakers.