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.
Adelopo et al. (Sat,) studied this question.