Multivariate GARCH analysis of return spillovers between Fed Rate changes, decentralized finance (DeFi) assets, and stock indices

Abstract

This study examined the dynamic interrelationships and volatility spillovers among decentralized finance (DeFi) assets, traditional stock indices, commodities, and macroeconomic policy through the lens of multivariate GARCH models. Using daily time series data spanning from January 10, 2023, to December 31, 2024, the study applied both DCC-GARCH(1,1) and BEKK-GARCH models to a diversified 15-asset portfolio comprising stablecoins (USDC, USDT, BUSD, TUSD, DAI, GUSD), cryptocurrencies (Bitcoin, Ethereum), commodities (gold, crude oil), U.S. equity indices (Dow Jones, S\&P 500, Nasdaq, NYSE), and the Federal Funds Rate. The findings revealed significant return and volatility spillovers, particularly from Federal Reserve interest rate changes to both digital and traditional markets. Bitcoin and Ethereum showed strong co-movements with major stock indices, highlighting their increased integration into global financial systems. In contrast, stablecoins exhibited lower volatility and weaker interlinkages, confirming their role as volatility dampeners. Gold continued to function as a safe-haven asset, while oil’s influence was episodic and context-dependent. The time-varying and asymmetric nature of these relationships, especially during macroeconomic stress, underscores the need for adaptive investment strategies and greater regulatory coordination. This paper contributes to the literature by offering a comprehensive multivariate volatility modeling framework that bridges digital finance and macroeconomic dynamics.