This study examines how different dimensions of climate change risk relate to insurance sector equity performance in an environment of increasing climate-related events. It adopts a multidimensional framework covering U.S. climate policy, international climate summits, global warming, and natural disasters to assess whether climate risks affect insurance stock returns asymmetrically across market conditions.
Using daily data from 2003 to 2023, the study applies quantile-on-quantile connectedness and wavelet coherence methods to capture nonlinear, state-dependent, and time-varying linkages between climate risk indicators and insurance stock returns.
The results indicate that climate risks exhibit asymmetric and horizon-dependent relationships with insurance equities. Transition-related risks, particularly those linked to climate policy developments and international summits, are more influential during adverse market conditions, while physical risks associated with natural disasters display more persistent effects over longer horizons. Insurance stocks generally act as net receivers of climate-related shocks, especially during periods of intensified climate-related news and elevated uncertainty.
The findings indicate that climate risk indicators can support downside-risk monitoring and stress-testing frameworks for insurance markets. The results also underline the importance of incorporating climate-related risk considerations into regulatory oversight and policy design to reduce potential spillovers to the insurance sector during periods of heightened transition risk.
This paper provides a multidimensional analysis of climate–finance linkages in the insurance sector. By jointly examining multiple climate risk dimensions and combining quantile-based and time–frequency methods, it documents asymmetric and nonlinear transmission mechanisms that are not captured by conventional empirical approaches.
