From risk to resilience: Wavelet–quantile evidence on geopolitical shocks and clean energy markets

DOĞAN M.

Journal of Environmental Management, cilt.394, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 394
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.jenvman.2025.127577
  • Dergi Adı: Journal of Environmental Management
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, International Bibliography of Social Sciences, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Communication Abstracts, Environment Index, Geobase, Greenfile, Index Islamicus, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Clean energy indices, Geopolitical risk index, Wavelet kernel-based regularized least squares, Wavelet quantile correlation, Wavelet quantile regression
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

Geopolitical risks have emerged as a critical determinant of global energy dynamics, influencing both traditional and renewable energy markets. The primary objective of this study is to comprehensively analyze the relationship between the Geopolitical Risk Index (GPR) and clean energy indices. Going beyond average effects, the study examines how this relationship varies across different quantiles and time horizons, thereby revealing the short-, medium-, and long-term dynamics of geopolitical risks on clean energy markets. Using data covering the period from February 8, 2014, to June 2, 2025, four indices were employed to represent clean energy markets: the NASDAQ Clean Edge Green Energy Index (EDGE), the S&P Global Clean Energy Transition Index (SPG), the WilderHill Clean Energy Index (WILDER), and the S&P Kensho Clean Energy Index (EU). Methodologically, the study applies Wavelet Quantile Correlation (WQC), Wavelet Kernel-Based Regularized Least Squares (WKRLS), and Wavelet Quantile Regression (WQR) techniques. The findings indicate that the relationship between GPR and clean energy markets is negative in the short run, partially recovering and becoming neutral in the medium run, and positive in the long run. These results suggest that while geopolitical risks weaken investor confidence and exert downward pressure on markets in the short term, in the long term, energy security concerns stimulate clean energy investments, thereby supporting market growth. The results provide important insights that should be taken into account in risk management strategies for investors and in regulatory frameworks aimed at accelerating the energy transition for policymakers.