Dynamic Linkages and Monetary Policy Transmission in the Cryptocurrency Market: A Vector Autoregressive Study of Bitcoin, Ethereum, and The Fed's Interest Rate

Abstract

The cryptocurrency market, characterized by high volatility, has evolved into a significant financial asset class, attracting both retail and institutional investors. Understanding its interconnectedness with macroeconomic factors is crucial for risk management and financial stability. This study empirically analyzes the dynamic relationships between two primary crypto assets, Bitcoin (BTC) and Ethereum (ETH), and the monetary policy shifts of the U.S. Federal Reserve (The Fed). Using a Vector Autoregression (VAR) model on daily time-series data from January 1, 2022, to June 16, 2025, this research investigates the short-term dynamics, Granger causality, and shock transmissions within this system. The findings reveal a significant one-way causal relationship from The Fed's interest rate changes to both Bitcoin and Ethereum returns, challenging the weak-form Efficient Market Hypothesis. Furthermore, Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analyses provide robust evidence of Bitcoin's market leadership, with shocks in Bitcoin explaining nearly 70% of the variance in Ethereum's movements. These results highlight a clear hierarchical structure: The Fed influences broad market sentiment, while Bitcoin leads internal market dynamics, offering critical insights for investors and policymakers navigating the digital asset ecosystem.