The volatility spillover between digital currencies and stock markets:evidence from DCC-GARCH R2 decomposed connectedness measures

Abstract Based on weekly data from December 2018 to October 2025, this study employs the DCC-GARCH R² decomposed connectedness approach to investigate volatility spillovers between four major digital currencies (Bitcoin, Ethereum, Tether USD, USD Coin) and five key stock markets (China, the U.S., Germany, Japan, and the UK). Empirical findings reveal three core insights. First, dynamic conditional correlations exhibit distinct patterns across digital currency subtypes and stock markets: public chain coins (BTC and ETH) are strongly correlated with each other, stablecoins show negative correlations with other assets, and China’s stock market remains largely insulated from global markets. Second, R² decomposed connectedness analysis reveals substantial cross-market linkages, with China’s stock market displaying the weakest connectedness and the U.S. market acting as the primary risk transmitter. Third, the dynamic total connectedness index exhibits three distinct peaks in early 2019, the first half of 2020, and mid-2023, before entering a current downward trajectory. These peak periods may be associated with possible explanations, including the 2019 crypto crash, the 2020 COVID-19 pandemic, and the 2023 regulatory changes. Net connectedness analysis identifies BTC, the U.S., and German markets as net transmitters of shocks, while China, Japan, and the UK are net receivers. These findings underscore the heterogeneous spillover dynamics across digital currency subtypes, offering actionable insights for cross-market risk management and asset allocation.