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Funding structures affected the amount of financial stress different countries and sectors experienced during the spread of COVID-19 in early 2020. Policy responses targeting specific vulnerabilities were more effective at mitigating this stress than those supporting banks or the economy more broadly.

The Risk Amplification Macro Model (RAMM) is a new nonlinear two-country dynamic model that captures rare but severe adverse shocks. The RAMM can be used to assess the financial stability implications of both domestic and foreign-originated risk scenarios.

Cryptoassets that reference a national currency (commonly known as stablecoins) aim to peg their value to the reference currency and typically use a reserve of traditional financial assets to maintain the peg. The market value of these fiat-referenced cryptoassets has grown more than thirtyfold between early 2020 and mid-2022. We explore some of their potential benefits and key risks.

What risks could stablecoins pose to the financial system? We argue that the stabilization mechanisms of stablecoins give rise to the risk of confidence runs, which can propagate to broader cryptoasset markets and the traditional financial sector. We also argue that stablecoins can contribute to financial stability risks by facilitating the buildup of leverage and liquidity mismatch in decentralized finance. Such risks cannot be addressed by ensuring the price stability of stablecoins alone. Finally, we explore the potential implications of stablecoins for the current system of bank-intermediated credit and for monetary policy.

We estimate the share of variable-rate mortgages with fixed payments that reached the so-called trigger rate—the interest rate at which mortgage payments no longer cover the principal. Amid rising interest rates, this share was close to 50% at the end of October 2022 and could potentially reach 65% in 2023.

Unregulated capital flows are likely excessive during a stagflation episode, owing to a macroeconomic externality operating through the economy’s supply side. Inflows raise domestic wages and cause unwelcome upward pressure on firm costs, yet market forces likely generate such inflows. Optimal capital flow management instead requires net outflows.

The COVID-19 pandemic has caused an atypical recession in which some sectors of the economy boomed and others collapsed. This required a unique fiscal policy reaction to both support firms and stimulate activity in sectors with slack. Was fiscal policy able to get where it was needed? Mostly, yes.

Non-default losses of financial market infrastructures (FMIs) have gained attention due to their potential impacts on FMIs and FMI participants, and the lack of a common approach to address them. A key question is, who should absorb these losses?

We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.

We examine how changes in the Bank of Canada’s balance sheet impact the banking system. Quantitative easing contributed to an increase in the size of the banking system’s balance sheet and an improvement in bank liquidity coverage ratios. Quantitative tightening is expected to partially reverse these impacts. The banking system will have to adjust its liquidity management strategy in response.