Modelling the Sovereign Debt Strategy: A Practical Primer Staff discussion paper 2025-16 Nicolas Audet, Adam Epp, Jeffrey Gao, Joe Ning We provide a primer on the role of debt modelling in informing the sovereign debt issuance strategy and discuss how specific challenges faced by debt managers can influence model design decisions. These insights are supported by our experiences using the Canadian Debt Strategy Model to guide policy decisions. Content Type(s): Staff research, Staff discussion papers JEL Code(s): G, G1, G11, G17, H, H6, H63, H68 Research Theme(s): Financial markets and funds management, Funds management, Models and tools, Economic models
Simulating the Resilience of the Canadian Banking Sector Under Stress: An Update of the Bank of Canada’s Top-Down Solvency Assessment Tool Technical report No. 128 Omar Abdelrahman, David Xiao Chen, Cameron MacDonald, Adi Mordel, Guillaume Ouellet Leblanc We present a technical description of the Top-Down Solvency Assessment (TDSA) tool. As a solvency stress-testing tool, TDSA is used to assess the banking sector’s capital resilience to hypothetical future risk scenarios. Content Type(s): Staff research, Technical reports JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28 Research Theme(s): Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Models and tools, Economic models
The Dynamic Canadian Debt Strategy Model Technical report No. 127 Nicolas Audet, Joe Ning, Adam Epp, Jeffrey Gao We present a dynamic debt strategy model framework designed to assist sovereign debt portfolio managers in choosing an optimal debt issuance strategy. The main innovation of this framework is the introduction of dynamic issuance strategies, which allow issuance decisions to vary over time based on the model’s simulated state variables. Content Type(s): Staff research, Technical reports JEL Code(s): C, C6, C61, G, G1, G11, G17, H, H6, H63, H68 Research Theme(s): Financial markets and funds management, Funds management, Models and tools, Econometric, statistical and computational methods
Stress testing central counterparties for resolution planning Staff analytical note 2025-11 Katherine Brennan, Bo Young Chang, Alper Odabasioglu, Radoslav Raykov The Bank of Canada completed its first resolution plan for the Canadian Derivatives and Clearing Corporation (CDCC) in 2024. To estimate the resolution costs, we apply the extreme value theory method to simulate the credit losses that would result from extreme scenarios where multiple clearing members default at the same time. Content Type(s): Staff research, Staff analytical notes JEL Code(s): G, G1, G17, G2, G23, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Financial system regulation and oversight, Money and payments, Payment and financial market infrastructures
Finding the balance—measuring risks to inflation and to GDP growth Staff analytical note 2023-18 Bruno Feunou, James Kyeong Using our new quantitative tool, we show how the risks to the inflation and growth outlooks have evolved over the course of 2023. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Monetary policy framework and transmission, Real economy and forecasting
Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency Staff discussion paper 2023-19 Chinara Azizova, Bruno Feunou, James Kyeong This paper quantifies tail risks in the outlooks for Canadian inflation and real GDP growth by estimating their conditional distributions at a daily frequency. We show that the tail risk probabilities derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model Technical report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp 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. Content Type(s): Staff research, Technical reports JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models
Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning Staff working paper 2022-29 Vladimir Skavysh, Sofia Priazhkina, Diego Guala, Thomas Bromley 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. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models
The potential effect of a central bank digital currency on deposit funding in Canada Staff analytical note 2020-15 Alejandro García, Bena Lands, Xuezhi Liu, Joshua Slive A retail central bank digital currency denominated in Canadian dollars could, in theory, create competition for bank deposit funding. Content Type(s): Staff research, Staff analytical notes JEL Code(s): E, E4, E41, E44, E5, G, G1, G10, G17, G2, G21, G3, G32, O Research Theme(s): Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Money and payments, Digital assets and fintech
A Counterfactual Valuation of the Stock Index as a Predictor of Crashes Staff working paper 2017-38 Tom Roberts Stock market fundamentals would not seem to meaningfully predict returns over a shorter-term horizon—instead, I shift focus to severe downside risk (i.e., crashes). Content Type(s): Staff research, Staff working papers JEL Code(s): G, G0, G01, G1, G12, G17, G19 Research Theme(s): Financial markets and funds management, Market functioning, Financial system, Financial stability and systemic risk