In times of stress, if the potential demand from asset managers for market liquidity approaches or exceeds dealers' ability to intermediate, it could lead to a precautionary but disruptive dash for cash and may lead central banks to intervene. If the likelihood of such a dash for cash increases...

We propose a flexible machine learning (ML) framework for real-time transaction monitoring in high-value payment systems (HVPS), which are a central piece of a country's financial infrastructure. This framework can be used by system operators and overseers to detect anomalous transactions,...

We provide a theory of fire sales in which potential buyers are subject to liquidity shocks and frictions that limit their ability to resell assets. The model predictions align with some stylized facts about the large sales of corporate bonds and Treasury securities during the COVID-19 economic...

This paper describes the ecology of automated market makers (AMMs), which are the most popular decentralized exchange model for the pricing and trading of crypto assets within decentralized finance. We use blockchain data to identify trends in user adoption and trading volumes of AMMs. Given the...

In many countries, the cost of housing has greatly outpaced income growth, leading to a housing affordability crisis. Leveraging Canadian loan-level data and quasi-experimental variation in payment-to-income constraints, we document an increasing reliance of first-time homebuyers on financial...

We study a government policy that restricts repayment choices with the aim of reducing credit card debt. The policy requires the minimum payment on credit card balances in Quebec to be at least 2% of the statement balance for cards opened before August 2019 and at least 5% for cards opened after...

This paper describes the ecology of automated market makers (AMMs), which are the most popular decentralized exchange model for the pricing and trading of crypto assets within decentralized finance. We use blockchain data to identify trends in user adoption and trading volumes of AMMs. Given the...

We propose a flexible machine learning (ML) framework for real-time transaction monitoring in high-value payment systems (HVPS), which are a central piece of a country's financial infrastructure. This framework can be used by system operators and overseers to detect anomalous transactions,...

We study a government policy that restricts repayment choices with the aim of reducing credit card debt. The policy requires the minimum payment on credit card balances in Quebec to be at least 2% of the statement balance for cards opened before August 2019 and at least 5% for cards opened after...