Dynamics of the Crypto Volatility Index: empirical evidence from market interactions and advanced predictive modeling

Given their growing relevance in the global financial market, the dynamics of cryptocurrencies have attracted extensive attention. In particular, the connections between cryptocurrencies and traditional financial assets are becoming increasingly significant. In this work, we focus on the Crypto Volatility Index (CVI), which measures the market’s expectation of future volatility of major cryptocurrencies, Bitcoin and Ethereum, and explore its relation with traditional volatility indicators, namely Gold Volatility Index (GVZ), Crude Oil Volatility Index (OVX), S&P500 Volatility Index (VIX), and macro-financial variables, as the Dollar to Euro exchange rate (USDEUR), the FED interest rate (FED) and the NASDAQ index. After assessing the stationarity of the considered time series in order to obtain reliable regression estimates and avoid spurious inference, traditional regression models and machine learning approaches are applied to provide a comprehensive assessment of the determinants of the CVI. Our findings indicate that CVI dynamics are driven primarily by persistence and macro-financial shocks, rather than by contemporaneous fluctuations in traditional asset-class volatility or equity-market indices. The analysis enriches the understanding of the role of cryptocurrencies within the broader financial system and offers a solid foundation for future forecasting and risk management applications.