Research Article

Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness

Volume: 8 Number: 2 October 30, 2026
EN TR

Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness

Abstract

This study examines the dynamic relationships among geopolitical risk, artificial intelligence (AI), and clean energy markets. The Geopolitical Risk Index (GPR) is used to represent geopolitical risk; the STOXX Global Artificial Intelligence Index, Indxx Global Robotics & Artificial Intelligence Index, and Nasdaq CTA Artificial Intelligence & Robotics Index represent AI markets; and the FTSE Environmental Opportunities Renewable & Alternative Energy Index, NASDAQ Clean Edge Green Energy Index, and S&P Global Clean Energy Index represent clean energy markets. Using daily data from December 18, 2017 to May 1, 2026, the study employs Wavelet Quantile-on-Quantile Regression (WQQR), Quantile-on-Quantile Connectedness (QQCON), and Frequency Quantile Connectedness (FQCON) approaches. The findings reveal that the effects of geopolitical risk on AI and clean energy markets are nonlinear, heterogeneous, and dependent on market regimes and time horizons. Moreover, AI and clean energy markets exhibit asymmetric connectedness, while their net transmitter and receiver roles vary across quantiles and over time. These findings provide important implications for investors, portfolio managers, and policymakers regarding risk management, portfolio diversification, and the coordination of green and digital transformation policies.

Keywords

Supporting Institution

This study received no financial support from any institution or organization.

Ethical Statement

This study which does not require ethics committee approval and/or legal/specific permission complies with the Research and Publication Ethics.

References

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  5. Al-Maadid, A., Ali, M. S. B., & Mohammed, K. S. (2026). Driving the energy transition in the GCC: The role of artificial intelligence, technology and energy prices. Energy Strategy Reviews, 63, 102029. https://doi.org/10.1016/j.esr.2025.102029
  6. Almeida, D., Ferreira, P., Dionísio, A., & Aslam, F. (2025). Exploring the connection between geopolitical risks and energy markets. Energy Economics, 141, 108113. https://doi.org/10.1016/j.eneco.2024.108113
  7. Ando, T., Greenwood-Nimmo, M., & Shin, Y. (2022). Quantile connectedness: Modeling tail behavior in the topology of financial networks. Management Science, 68(4), 2401-2431. https://doi.org/10.1287/mnsc.2021.3984
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Details

Primary Language

English

Subjects

Financial Markets and Institutions

Journal Section

Research Article

Publication Date

October 30, 2026

Submission Date

August 31, 2026

Acceptance Date

October 29, 2026

Published in Issue

Year 2026 Volume: 8 Number: 2

APA
Erben Yavuz, A. (2026). Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness. International Journal of Business and Economic Studies, 8(2). https://doi.org/10.54821/bes.2029368
AMA
1.Erben Yavuz A. Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness. BES JOURNAL. 2026;8(2). doi:10.54821/bes.2029368
Chicago
Erben Yavuz, Asuman. 2026. “Geopolitical Risk, Artificial Intelligence, and Clean Energy Markets: Nonlinear Effects and Dynamic Connectedness”. International Journal of Business and Economic Studies 8 (2). https://doi.org/10.54821/bes.2029368.
EndNote
Erben Yavuz A (October 1, 2026) Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness. International Journal of Business and Economic Studies 8 2
IEEE
[1]A. Erben Yavuz, “Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness”, BES JOURNAL, vol. 8, no. 2, Oct. 2026, doi: 10.54821/bes.2029368.
ISNAD
Erben Yavuz, Asuman. “Geopolitical Risk, Artificial Intelligence, and Clean Energy Markets: Nonlinear Effects and Dynamic Connectedness”. International Journal of Business and Economic Studies 8/2 (October 1, 2026). https://doi.org/10.54821/bes.2029368.
JAMA
1.Erben Yavuz A. Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness. BES JOURNAL. 2026;8. doi:10.54821/bes.2029368.
MLA
Erben Yavuz, Asuman. “Geopolitical Risk, Artificial Intelligence, and Clean Energy Markets: Nonlinear Effects and Dynamic Connectedness”. International Journal of Business and Economic Studies, vol. 8, no. 2, Oct. 2026, doi:10.54821/bes.2029368.
Vancouver
1.Asuman Erben Yavuz. Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness. BES JOURNAL. 2026 Oct. 1;8(2). doi:10.54821/bes.2029368


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