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 Topic(s): Business fluctuations and cycles, Central bank research, Econometric and statistical methods, Economic models, Financial stability JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21
Vertical Bargaining and Obfuscation Staff Working Paper 2022-13 Edona Reshidi Is obscuring prices always bad for consumers? The answer depends on the market structure and on the negotiating power between manufacturers and retailers. Content Type(s): Staff research, Staff working papers Topic(s): Economic models, Market structure and pricing JEL Code(s): C, C7, C70, L, L1, L13, L4, L42
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. Content Type(s): Staff research, Staff working papers Topic(s): Central bank research, Economic models, Financial institutions, Financial stability, Financial system regulation and policies JEL Code(s): C, C6, C63, C7, C72, G, G2, G21
Estimating Policy Functions in Payments Systems Using Reinforcement Learning Staff Working Paper 2021-7 Pablo S. Castro, Ajit Desai, Han Du, Rodney J. Garratt, Francisco Rivadeneyra We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information. Content Type(s): Staff research, Staff working papers Topic(s): Digital currencies and fintech, Financial institutions, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): A, A1, A12, C, C7, D, D8, D83, E, E4, E42, E5, E58
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? Content Type(s): Staff research, Staff working papers Topic(s): Financial stability, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): C, C6, C62, C63, C7, C72, G, G0, G01, G1, G11
Monetary Payoff and Utility Function in Adaptive Learning Models Staff Working Paper 2019-50 Erhao Xie When players repeatedly face an identical or similar game (e.g., coordination game, technology adoption game, or product choice game), they may learn through experience to perform better in the future. This learning behaviour has important economic implications. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Economic models JEL Code(s): C, C5, C57, C7, C72, C9, C92
An Application of Shapley Value Cost Allocation to Liquidity Savings Mechanisms Staff Working Paper 2019-26 Rodney J. Garratt Liquidity demands in real-time gross settlement payment systems can be enormous. To reduce the liquidity requirement, central banks around the world have implemented liquidity savings mechanisms (LSMs). Content Type(s): Staff research, Staff working papers Topic(s): Payment clearing and settlement systems JEL Code(s): C, C7, C72, E, E5, E58
The Framework for Risk Identification and Assessment Technical Report No. 113 Cameron MacDonald, Virginie Traclet Risk assessment models are an important component of the Bank’s analytical tool kit for assessing the resilience of the financial system. We describe the Framework for Risk Identification and Assessment (FRIDA), a suite of models developed at the Bank of Canada to quantify the impact of financial stability risks to the broader economy and a range of financial system participants (households, businesses and banks). Content Type(s): Staff research, Technical reports Topic(s): Economic models, Financial institutions, Financial stability, Housing JEL Code(s): C, C3, C5, C6, C7, D, D1, E, E0, E00, E2, E27, E3, E37, E4, E47, G, G0, G2, G21
The MacroFinancial Risk Assessment Framework (MFRAF), Version 2.0 Technical Report No. 111 Jose Fique This report provides a detailed technical description of the updated MacroFinancial Risk Assessment Framework (MFRAF), which replaces the version described in Gauthier, Souissi and Liu (2014) as the Bank of Canada’s stress-testing model for banks with a focus on domestic systemically important banks (D-SIBs). Content Type(s): Staff research, Technical reports Topic(s): Financial stability, Financial system regulation and policies JEL Code(s): C, C7, C72, E, E5, E58, G, G0, G01, G2, G21, G28
Stability and Efficiency in Decentralized Two‐Sided Markets with Weak Preferences Staff Working Paper 2017-4 Radoslav Raykov Many decentralized markets are able to attain a stable outcome despite the absence of a central authority (Roth and Vande Vate, 1990). A stable matching, however, need not be efficient if preferences are weak. This raises the question whether a decentralized market with weak preferences can attain Pareto efficiency in the absence of a central matchmaker. Content Type(s): Staff research, Staff working papers Topic(s): Economic models JEL Code(s): C, C7, C78, D, D6, D61