These levers affect a wide range of stakeholders: households, through carbon quotas, taxes or subsidies; companies, through standards, climate reporting or permit markets; and investors, through green taxonomies, transparency requirements or risk management tools. At the intersection of mathematics, economics and finance, the project draws on innovative approaches: mean field game theory and dynamic incentive theory.
The aim is to help policymakers anticipate how economic actors will respond, design effective market mechanisms and better manage the financial risks associated with climate change. MIRTE identifies two major types of climate risk. First, there are physical risks—floods, storms and droughts—which can damage infrastructure, disrupt markets and make certain risks uninsurable. Then there are transition risks, arising from rapid changes in public policy, shifts in consumer preferences or technological innovations. These changes can threaten the profitability of entire sectors.
The project also explores how losses in the value of carbon-intensive assets can ripple through the entire financial system, and proposes strategies to limit domino effects. As climate policies become more stringent, certain assets—such as coal-fired power stations, oil fields or shares in high-emitting companies—risk a sudden loss of value: they become unprofitable, unusable or even prohibited.
MIRTE is structured around three strands—the mathematics of collective incentives, the design of market mechanisms for the transition, and financial risk management—and draws on cutting-edge tools: stochastic differential equations, nonlinear Monte Carlo methods, neural networks, and the analysis of data from energy and financial markets.
