In this paper we analyze whether and how a central bank can pursue the objective to lower its exposure to climate-related financial risks in its asset purchase programs while meeting the criteria that define the eligible universe of assets, including market neutrality. Despite focusing on the...

We characterize the evolution over time of a network of credit relations among financial agents as a system of coupled stochastic processes. Each process describes the dynamics of individual financial robustness, while the coupling results from a network of liabilities among agents. The average...

Financial networks have shown to be important in understanding systemic events in credit markets. In this paper, we investigate how the structure of those networks can affect the capacity of regulators to assess the level of systemic risk. We introduce a model to compute the individual and...

We study financial networks and reveal a new kind of systemic risk arising from what we call default ambiguity, i.e., a situation where it is impossible to decide which banks are in default. Specifically, we study the clearing problem: given a network of banks interconnected by financial...

Climate change has been recently recognised as a new source of risk for the financial system. Several financial supervisors with a financial stability mandate have recently recommended that investors and financial institutions need to assess their exposure to climate-related financial risks and...

We characterize the evolution over time of a network of credit relations among financial agents as a system of coupled stochastic processes. Each process describes the dynamics of individual financial robustness, while the coupling results from a network of liabilities among agents. The average...

Aligning finance to sustainability requires methodologies to price forward-looking climate risks and opportunities in financial contracts and in investors' portfolios. Traditional approaches to financial pricing models cannot incorporate the nature of climate risk (i.e. deep uncertainty,...