We present key findings of a recent study that evaluates the credit risk that flooding poses to the residential lending activities of Canadian banks and credit unions. Results show that such risk currently appears modest but could become larger with climate change.
Regulators need to provide effective procyclicality guidance, and central counterparties must design and calibrate their margin systems and procyclicality frameworks appropriately. To serve these needs, we provide a novel conceptual tool kit. Further, we highlight that the focus should be on the key margin system parameters in determining procyclicality.
We assess the potential financial risks of current and projected flooding caused by extreme weather events in Canada. We focus on the residential real estate secured lending (RESL) portfolios of Canadian financial institutions (FIs) because RESL portfolios are an important component of FIs’ balance sheets and because the assets used to secure such loans are immobile and susceptible to climate-related extreme weather events.
Senior Deputy Governor Carolyn Rogers talks about why interest rates could settle at a higher level than Canadians are used to and why preparing early for that possible outcome is important.
A regulator would want to restrict dividends to force banks to rebuild capital during a crisis. But such a policy is not time-consistent. A time-consistent policy would let banks gradually rebuild capital and pay dividends even when their equity remains below pre-crisis levels.
We study whether the credit derivatives of firms reflect the risk from climate transition. We find that climate transition risk has asymmetric and significant economic impacts on the credit risk of more vulnerable firms, and negligible effects on other firms.
This paper studies, theoretically and empirically, the unintended consequences of mandatory retention rules in securitization. It proposes a novel model showing that while retention strengthens monitoring, it may also encourage banks to shift risk.
We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.