Quantum mechanics

Quantile regression

Statistics

Multivariate statistics

Quantile

Granger causality

Economics

Computer science

Tail dependence

Computer network

Social connectedness

Physics

Psychology

Mathematics

Psychotherapist

Econometrics

Causality (physics)

Energy

This paper analyzes the cross-quantile dependence and causality between non-ferrous metals and clean energy indices by employing data from November 2003 to May 2019. Specifically, we utilize the time-varying copulas to examine the asymmetric connectedness among the assets. Based on the assessed dependence, we utilize the time-static and time-varying cross-quantilogram approach to evaluate the asymmetric dependence across different quantiles. Finally, we employ a Granger-causality in quantiles analysis to assess the causal relationship across different quantiles of the return distributions of the underlying assets. By utilizing time-varying copulas, we report that the conditional dependence between the assets is time-varying and asymmetric with the potential for tail dependence. Our results from the cross-quantilogram analysis provide further evidence that the interconnectedness is asymmetric across quantiles, and it increases with the increase in lags. In addition, we report that extreme market conditions positively influence the dependence structure. Finally, our findings from Granger-causality in quantiles indicate bidirectional causality among assets that intensifies with the increase in lag order. These findings are important for governmental policies that aim at mitigating the impact of climate change by transforming the global energy landscape towards clean and renewable energy sources.

Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes