Change theme
Change theme

Search

Content Types

Topics

JEL Codes

Locations

Departments

Authors

Sources

Statuses

Published After

Published Before

404 Results

On the Fragility of DeFi Lending

Staff Working Paper 2023-14 Jonathan Chiu, Emre Ozdenoren, Kathy Yuan, Shengxing Zhang
We develop a dynamic model to capture key features of decentralized finance lending. We identify a price-liquidity feedback: the market outcome in any given period depends on agents' expectations about lending activities in future periods, with higher future price expectations leading to more lending and higher prices in that period.

Learning in a Complex World: Insights from an OLG Lab Experiment

Staff Working Paper 2023-13 Cars Hommes, Stefanie J. Huber, Daria Minina, Isabelle Salle
This paper brings novel insights into group coordination and price dynamics in complex environments. We implement a chaotic overlapping-generation model in the lab and find that group coordination is always on the steady state or on the two-cycle and that behavior is non-monotonic.
Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Economic models JEL Code(s): C, C6, C62, C68, C9, C91, C92, E, E1, E13, E7, E70, G, G1, G12, G4, G41

Introducing the Bank of Canada’s Market Participants Survey

Staff Analytical Note 2023-1 Annick Demers, Tamara Gomes, Stephane Gignac
The Market Participants Survey (MPS) gathers financial market participants’ expectations for key macroeconomic and financial variables and for monetary policy. This staff analytical note describes the MPS’s objectives and main features, its process and design, and how Bank of Canada staff use the results.

Stress Relief? Funding Structures and Resilience to the Covid Shock

Staff Working Paper 2023-7 Kristin Forbes, Christian Friedrich, Dennis Reinhardt
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.

Financial Constraints and Corporate Investment in China

Staff Discussion Paper 2022-22 Kun Mo, Michel Soudan
Financial constraints deter firms from pursuing optimal investment plans. In China, we find privately owned firms face greater financial constraints than state-owned enterprises (SOEs). This can be explained by our finding that lenders appear less concerned about the credit risk of SOEs, which causes distortions in the allocation of credit.
Content Type(s): Staff research, Staff discussion papers Topic(s): Financial markets, Firm dynamics JEL Code(s): E, E2, E22, G, G1, G3

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.

BoC–BoE Sovereign Default Database: What’s new in 2022?

Staff Analytical Note 2022-11 David Beers, Elliot Jones, Karim McDaniels, Zacharie Quiviger
The BoC–BoE database of sovereign debt defaults, published and updated annually by the Bank of Canada and the Bank of England, provides comprehensive estimates of stocks of government obligations in default.

Cyber Risk and Security Investment

Staff Working Paper 2022-32 Toni Ahnert, Michael Brolley, David Cimon, Ryan Riordan
We develop a principal-agent model of cyber-attacking with fee-paying clients who delegate security decisions to financial platforms. We derive testable implications about clients’ vulnerability to cyber attacks and about the fees charged.

Fixed-income dealing and central bank interventions

Staff Analytical Note 2022-9 David Cimon, Adrian Walton
We summarize the theoretical model of central bank asset purchases developed in Cimon and Walton (2022). The model helps us understand how asset purchases ease pressures on investment dealers to restore market conditions in a crisis.

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.
Go To Page