This paper addresses the methodological challenges in quantifying physical risks associated with climate change, proposing a novel top-down stochastic approach focused on modeling financial losses from extreme events. Unlike existing studies limited to specific events, our approach utilizes predefined climate sensitivity parameters, enabling a broader application across various extreme events using the example of tropical cyclones. We have also conducted an extended review of the literature on the modeling of indirect shocks to cover the full scope of the damage modeling from cost-push Leontief price model to Adaptive Regional Input-Output approaches (ARIO, Hallegatte, 2013). Building on Desnos et al. (2023)’s adaptation of the value-at-risk concept for transition risk analysis, we extend the framework to incorporate direct physical shock impacts with co-occurrence, cascading effects through input-output mechanisms (indirect damages to the economy), and temporal considerations (forward projection, capacity for a sector to rebuild itself). By bridging the gap between these two approaches, we provide a comprehensive assessment of climate risks, considering uncertainties associated with transition scenarios and offering insights into the amplification of impacts through time and across global economies.


Quantitative Modeling at Amundi Technology
Quantitative Project Manager at Amundi Technology
Quantitative Research, Amundi Technology