Change theme
Change theme


Content Types


JEL Codes






Published After

Published Before

24 Results

January 15, 2024

Mapping out the implications of climate transition risk for the financial system

We develop a new analytical framework to understand the system-wide implications of climate transition risk. When applying this framework to Canadian data, we find that interconnections within the financial sector could amplify the direct effects of climate transition risk on financial entities.

Understanding the Systemic Implications of Climate Transition Risk: Applying a Framework Using Canadian Financial System Data

Our study aims to gain insight on financial stability and climate transition risk. We develop a methodological framework that captures the direct effects of a stressful climate transition shock as well as the indirect—or systemic—implications of these direct effects. We apply this framework using data from the Canadian financial system.

Simulating Intraday Transactions in the Canadian Retail Batch System

Staff Working Paper 2023-1 Nellie Zhang
This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.

Improving the Efficiency of Payments Systems Using Quantum Computing

We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays.

Comparison of Bayesian and Sample Theory Parametric and Semiparametric Binary Response Models

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.

Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning

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.

Stressed but not Helpless: Strategic Behaviour of Banks Under Adverse Market Conditions

Staff Working Paper 2021-35 Grzegorz Halaj, Sofia Priazhkina
Our stress-testing tool considers banks under stress that can strategically manage their balance sheets. Using confidential Canadian supervisory data, we assess whether bank behaviour to maximize shareholder value can amplify a hypothetical stress scenario.

Interbank Asset-Liability Networks with Fire Sale Management

Staff Working Paper 2020-41 Zachary Feinstein, Grzegorz Halaj
Raising liquidity when funding is stressed creates pressure on the financial market. Liquidating large quantities of assets depresses their prices and may amplify funding shocks. How do banks weathering a funding crisis contribute to contagion risk?
Go To Page