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Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

This paper evaluates the effectiveness of macroprudential policies when regulations are uneven across mortgage lender types. We look at credit tightening that results from macroprudential regulations and examine how much of it is counteracted by credit shifting to unregulated lenders. We also study the impact of monetary policy tightening when some lenders are unregulated.

We assess whether more central clearing would enhance the resilience of Canadian fixed-income markets. Our analysis estimates the potential benefits of balance sheet netting under scenarios where central clearing is expanded to new participants.

We examine the potential impacts of a severe economic shock on the resilience of major banks in Canada. We find these banks would suffer significant financial losses but nevertheless remain resilient. This underscores the role well-capitalized banks and sound underwriting practices play in supporting economic activity in a downturn.

We provide empirical evidence of effects to the aggregate economy from surprises about financial intermediaries’ net worth based on a high-frequency identification strategy. We estimate that news of a 1% decline in intermediaries’ net worth leads to a 0.2%–0.4% decrease in the market value of nonfinancial firms.

This paper studies how the impact of a cyber attack that paralyzes one or multiple banks' ability to send payments would transmit to other banks through the Canadian wholesale payment system. Based on historical payment data, we simulate a wide range of scenarios and evaluate the total payment disruption in the system.

Could Canadian banks continue to meet their regulatory liquidity requirements after the introduction of a cash-like retail central bank digital currency (CBDC)? We conduct a hypothetical exercise to estimate how a CBDC could affect bank liquidity by increasing the run-off rates of transactional retail deposits under four increasingly severe scenarios.

Chen et al. (2021) show that almost one-third of First Nations band offices in Canada are within 1 kilometre (km) of an automated banking machine (ABM) or financial institution (FI) branch and more than half are within 5 km.

Bank regulation presumes risks spill over more easily from large banks to the banking system than vice versa. Interestingly, we observe this is not the case. We find that the capacity to transmit risk is larger in the system-to-bank direction, leading to an increased default risk.

We create a theoretical model of central bank asset purchases. The model helps explain how, in a crisis, these purchases ease pressures on investment dealers.