Feature-conditioned co-movements between cryptocurrencies and sustainability indices

The impacts of the COVID-19 pandemic on finance remain inexhaustive, just as our knowledge of cryptocurrencies’ (henceforth “cryptos”) behavior is still emergent. We investigate the dynamic co-movements between cryptos and sustainable investment indices and how these relations evolve during the COVID-19 pandemic, and explore when and why cryptos co-move with sustainability-oriented investments. We especially focus on which crypto features and functionalities drive those links and how they change across COVID-19 regimes. Using daily data for the top 100 cryptos (from 1st January 2010 till 15th May 2024) and 14 sustainable investment indices covering environmental, social, and governance-related practices, sustainability screens, green technology, and renewable energy, we adopt a two-stage empirical design. In Stage 1 (detection), we use Granger causality and Dynamic Conditional Correlation-GARCH models to examine dynamic co-movements for each crypto-index pair. In Stage 2 (attribution), we use logistic regression to explain the incidence of co-movement using explicitly coded crypto characteristics and functions (consensus mechanism, smart contract capability, coin offering status, supply cap, stablecoin status, privacy status), estimated separately for pre-COVID, COVID and post-COVID periods. Three findings emerge. First, fewer than half of cryptos co-move with sustainability indices at any point. Second, among co-moving pairs, the share falls during COVID-19 and remains lower post-COVID than pre-COVID. Third, consensus mechanism and stablecoin status are robust, cross-regime drivers of co-movements, whereas other features are regime-dependent. Our contribution is to identify and quantify the feature-level drivers of co-movement between cryptos and sustainability indices at scale, across a broad asset universe and distinct market regimes, closing a scope gap in prior work focused on a few coins or composite indices. The results clarify when feature choices translate into stronger linkages with sustainability benchmarks, informing portfolio diversification, risk management, and regulatory assessment.