Dependence of green energy markets on big data and other fourth industrial revolution technologies

Abstract

This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.