This study is an extension of recent studies concentrated on the interconnectedness of energy markets as they relate to various sources of uncertainty. The purpose of this study is to achieve an understanding of the non-linear, asymmetric and multi-scale dependencies between various energy products and geopolitical risk (GPR), climate and economic uncertainty.
The author use the wavelet quantile-on-quantile methodology that combines wavelet decomposition with quantile regression analysis to assess oil market time-frequency dynamics and the different responses exhibited between uncertainty shocks over a variety of quantiles.
The empirical results show a time- and quantile-dependent response heterogeneity of oil markets to uncertainty shocks. Short-run effects are generally negative, with increased volatility and risk aversion of investors. Medium-run effects experience stabilization in markets as gradual adjustment of expectations takes place, whereas long-run effects are mostly favorable, reflecting structural adjustment to economic, political and GPRs. The detailed results indicate that crude oil retains its resilience in the face of climatic and geopolitical uncertainties, while gasoline and heating oil appear more vulnerable in the immediate run, but show increased resilience over extended horizons.
The resulting data helps investors, portfolio managers and policymakers demonstrate how energy markets react to uncertainty at different times and thus enable better risk management, hedge fund strategies and policy development for stabilizing the market.
By using a wavelet quantile-on-quantile methodology for analyzing nonlinearities, asymmetries and multi-scale dependence relationships between uncertainties indexes and energy markets, this research advances the existing knowledge on the topic.
