Assessing the spillover association of derivatives trading on cryptocurrency return volatility

This study examines the association between derivatives trading and the spot return volatility of cryptocurrencies, focusing specifically on Bitcoin (BTC) and Ethereum (ETH). It analyzes market connectedness and volatility spillover dynamics, assessing how spot and futures markets co-evolve from the introduction of BTC futures in 2017 through 2022, while reviewing the period overlapping with COVID-19 for BTC. Daily data are used to capture medium-term volatility transmission while avoiding microstructure noise common in high-frequency series. The empirical framework integrates ARIMA models for return dynamics, GARCH models for conditional volatility estimation, and a Time-Varying Parameter Vector Autoregression (TVP-VAR) to capture evolving spillover patterns between spot and futures markets. A Dynamic Conditional Correlation (DCC) extension is applied to trace shifts in the strength of co-movement over time. Together, these models allow for the examination of volatility clustering and dynamic interconnectedness that static models may overlook. The results indicate pronounced, time-varying spillover associations between spot and futures markets. Bitcoin exhibits higher overall connectedness (43%) and stronger conditional correlations (DCC = 0.93) than Ethereum (29% connectedness; DCC = 0.65), reflecting differences in market maturity, liquidity, and sample period. Both BTC and ETH show bidirectional volatility transmission between spot and futures markets, suggesting that derivatives trading is closely intertwined with spot market behavior for these two major cryptocurrencies. By jointly examining BTC and ETH within a unified modeling framework, this study provides updated evidence on volatility transmission in cryptocurrency markets and highlights how spillover dynamics vary across assets with different structural characteristics. The findings offer practical insight for portfolio management, hedging design, and the monitoring of interconnected risk, particularly in settings where spot and futures markets influence one another over time. For investors, the strong spot-futures co-movement implies limited within-asset diversification but supports the use of futures for hedging spot exposure; for risk managers and regulators, the time-varying connectedness signals when cross-market risk monitoring is most warranted.