Extreme climate and natural disaster risk in financial markets: A CoES approach

This study examines the financial impact of extreme climate and natural disaster (EC&ND) events on S&P 500 sectors, specifically their contribution to increased market and systemic risk. Utilizing the conditional autoregressive expected shortfall model, the research estimates and forecasts sectorspecific losses by incorporating EC&ND variables. Furthermore, the study introduces an enhanced conditional expected shortfall measure to assess systemic risk by analyzing the dependence between financial sector losses and overall system losses, incorporating EC&ND variables. This method offers a more comprehensive understanding of tail risk under climate stress compared to traditional models such as value-at-risk (VaR) and conditional VaR. The findings reveal that EC&ND variables substantially raise both estimated and forecasted losses and systemic risk, particularly in the energy, real estate, and insurance sectors. The study introduces two new metrics - the disaster market risk ratio and the disaster systemic risk ratio - to quantify these effects. Overall, the research underscores the urgent necessity to integrate EC&ND risk into financial regulation and policy frameworks to enhance systemic resilience. By linking climate risk to financial stability, this study contributes to the sustainable finance literature, providing practical insights for regulators, investors, and academics.