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US-China Tensions and renewable energy markets: A Dynamic Bayesian Inference Approach

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  • Naysary, Babak
  • Ghafoor, Abdul

Abstract

This paper examines the impact of US-China trade tensions on renewable energy markets from 2010-2024. Using a Dynamic Bayesian Inference approach, we quantify time-varying sensitivities of four NASDAQ renewable energy indices: Solar, Wind, Geothermal, and Green Economy. Our findings reveal significant heterogeneity in market responses. These results suggest that certain renewable sectors have developed effective resilience mechanisms to geopolitical risks.

Suggested Citation

  • Naysary, Babak & Ghafoor, Abdul, 2026. "US-China Tensions and renewable energy markets: A Dynamic Bayesian Inference Approach," CAFE Working Papers 44, Centre for Accountancy, Finance and Economics (CAFE), Birmingham City Business School, Birmingham City University.
    • Handle: RePEc:akf:cafewp:44
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