Abstract
This study examines the impact of geopolitical uncertainty on clean energy equity returns across different market conditions. Specifically, it analyses how geopolitical uncertainty, measured by the geopolitical oil price risk index (GOPRX), influences the returns of clean energy exchange-traded funds (ETFs), namely the Invesco Global Clean Energy ETF (PBD), Invesco Solar ETF (TAN), and First Trust Global Wind Energy ETF (FAN). The objective is to investigate “How does geopolitical uncertainty affect clean energy equities across different market conditions?”.
The analysis is based on monthly data from May 2008 to September 2020. Augmented Dickey-Fuller (ADF) and Brock, Dechert, Scheinkman (BDS) tests confirm stationarity and nonlinearity of the series, justifying the use of nonparametric econometric methods. The study employs a quantile‐Granger framework to uncover asymmetric, regime-dependent causality, corroborated by an all-quantiles joint test of the quantile regression process (using wild-bootstrap inference), together with lead/placebo timing checks and pre/post stability splits to verify robustness across the return distribution.
Our results indicate that GOPRX significantly Granger-causes clean energy ETF returns during bearish (quantiles 0.1–0.3) and normal (quantiles 0.4–0.6) market conditions; causality in this case is unidirectional. This suggests that rising geopolitical oil price risk is associated with declines in clean energy ETF performance during periods of market stress and moderation. In bullish conditions (quantiles 0.7–0.9), no significant causality is found, implying that optimistic investor sentiment may dampen the impact of geopolitical uncertainty. Sectoral differences are also observed, with TAN and FAN showing stronger sensitivity than PBD.
These findings challenge the blanket assumption that clean energy equities function as hedges against geopolitical risk. Instead, their vulnerability under specific market conditions highlights the importance of incorporating regime-dependent analysis. For policymakers, this underscores the need for robust policy frameworks, such as subsidies and investment incentives, to bolster clean energy resilience. For investors and portfolio managers, the results advocate for dynamic risk management strategies that consider quantile-dependent exposures. Overall, the study contributes to the energy finance literature by demonstrating the utility of nonparametric and distributional methods in capturing the complex interplay between geopolitical uncertainty and clean energy asset returns.