Ahmed Bossman

Purpose: The authors target the interrelationships between non-fungible tokens (NFTs), decentralized finance (DeFi) and carbon allowances (CA) markets during 2021–2023. The recent shift of crypto and DeFi miners from China (the People's Republic of China, PRC) green hydro energy to dirty fuel energies elsewhere induces investments in carbon offsetting instruments; this is a backdrop to the authors’ investigation.Design/methodology/approach: The quantile vector autoregression (VAR) approach is employed to examine extreme-quantile-connectedness and spillovers among the NFT Index (NFTI), DeFi Pulse Index (DPI), KraneShares Global Carbon Strategy ETF price (KRBN) and the Solactive Carbon Emission Allowances Rolling Futures Total Return Index (SOLCARBT).Findings: At bull markets, DPI is the only consistent net shock transmitter as NFTI transmits innovations only at the most extreme quantile. At bear markets, KRBN and SOLCARBT are net shock transmitters, while NFTI is the only consistent net shock receiver. The receiver-transmitter roles change as a function of the market conditions. The increases in the relative tail dependence correspond to the stress events, which make systemic connectedness augment, turning market-specific idiosyncratic considerations less relevant.Originality/value: The shift of digital asset miners from the PRC has resulted in excessive fuel energy consumption and aggravated environmental consequences regarding NFTs and DeFi mining. Although there exist numerous studies dedicated to CA trading and its role in carbon print reduction, the direct nexus between NFT, DeFi and CA has never been addressed in the literature. The originality of the authors’ research consists in bridging this void. Results are valuable for portfolio managers in bull and bear markets, as the authors show that connectedness is more intense under such conditions.

We study the dynamic connectedness between green bonds and the cryptocurrency environmental attention index (ICEA), using the TVP-VAR methodology. The spillovers increase with the level of environmental attention, suggesting cross-market activism by green investors. Denmark, the Euro area, Hong Kong, Australia, and the US are the source of spillovers, while Japan, the UK, and Switzerland are major recipients. The return spillovers exceed volatility spillovers and rise in strength during COVID-19 and the geopolitics-induced military hostilities in Ukraine. Several imperative implications of the findings are notable for policymakers, market participants, and practitioners.

The purpose of this study is to investigate the asymmetric effects of economic policy uncertainty (EPU), geopolitical risk (GPR), and market sentiment (VIX) on European Union (EU) stocks by sectors of economic activity. The design and methodological approach of our research are rooted in parametric and nonparametric quantile-based techniques. We employ monthly data covering eleven sectors of economic activity in addition to GPR, Global EPU, European Union EPU, United States EPU, and VIX. Our dataset covers the period between February 2013 and September 2022. Our findings show a generally low predictive power of the considered EPU measures on the stock returns of the EU sectors. Notwithstanding, the analysis reveals that EPU from the EU has the highest predictive ability on the EU sectoral stock returns while EPU from the US has no significant predictive ability on the stock returns from the EU. Our findings also highlight the asymmetric effects of various EPUs on EU stocks. Moreover, certain sectoral exposure to EU stocks, found to serve just as diversifiers in normal market conditions, could become a hedge and safe-haven against GPR in extreme economic conditions. Our findings also highlight the role of the VIX as a good gauge to hedge against the downside risks of the EU stocks. The originality of our work is two-fold. First, we extend the study of how global factors influence the EU stock market to the most recent period including the Russia–Ukraine conflict. Second, we perform this study on a sectoral basis. Therefore, the value of our findings is that they provide notable implications for market regulation and portfolio management.