Clean Energy Action Index Efficiency: An Analysis in Global Uncertainty Contexts

Climate change, the scarcity of fossil fuels, advances in clean energy, and volatility of crude oil prices have led to the recognition of clean energy as a viable alternative to dirty energy. This paper investigates the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets such as gold, crude oil, and natural gas between 1 January 2018, and 9 March 2023. To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings showed that returns data series exhibit signs of (in)efficiency. Additionally, there is a negative autocorrelation among the crude oil market, the Clean Energy Fuels Index, the Global Clean Energy Index, the gold market, and the natural gas market. Arbitration strategies can be used to obtain abnormal returns, but caution should be exercised as prices may increase above their actual market value and reduce the profitability of trading. This work contributes to the body of knowledge on sustainable finance by teaching investors how to use predictive strategies on the future values of their investments.

COVID-19 and the quantile connectedness between energy and metal markets.

This study analyzes the relationship between clean and dirty energy sources and energy metals during the COVID-19 pandemic. We document a sharp increase in connectedness after the COVID-19 pandemic, that is asymmetric at the lower and upper quantiles, with stronger dependence among the variables at the upper quantiles. Among the energy metals, cobalt is the least connected to the energy markets. Finally, our empirical results show a switch in the net connectedness indexes of energy metals and clean energy after January 2021. Our results have implication for investors and policy makers for energy and metal under various market conditions.

Co-movement between dirty and clean energy: A time-frequency perspective

In the backdrop of the recent covid-19 pandemic there is a renewed interest to understand the interlinkages between dirty and clean energies. In this regard, the study examines the co-movement structure between clean energy stocks and dirty energies before and during the covid-19 outbreak. The study analyses the interlinkages between the underlying markets by utilizing a vast sample of dirty energies namely crude oil, heating oil, gas oil, gasoline and natural gas, whereas clean energy sector is proxied by S&P Global clean energy index and Wilder Hill clean energy index. We make use of rolling window wavelet approach and wavelet coherence analysis to identify interdependencies between the clean energy stocks and dirty energies. The results exhibit weak linkages between clean energy equities and dirty energies in the short-run, while;we also record few occasions of high co-movements among dirty and clean energy markets in the long-run. Noticeably, a distinct decoupling effect persisted between dirty and clean energy markets. In addition, the findings also illustrate that clean energy market is relatively isolated from dirty energies during the recent pandemic crisis, amplifying portfolio diversification benefits across clean and dirty energy markets. The findings of the study hold meaningful insights for investors, policy makers and other market participants in energy financial markets.