Sofia Priazhkina is a Principal Researcher in the Financial Stability Department at the Bank of Canada. She received her Ph.D. in Economics from Indiana University. She first joined the Financial Stability Department to conduct research and develop stress testing models, and later Banking and Payments Department to work on CBDC research. Sofia's current interests include banking, financial networks, payments, CBDC and fintech. She uses game theory, modern computational methods, and structural estimations as her primary tools for both policy and research.
This paper provides an overview of cryptoasset exchanges. We contrast their design with exchanges in traditional financial markets and discuss emerging regulatory trends and innovations aimed at solving the problems cryptoasset exchanges face.
We use a suite of risk-assessment models to examine the possible impact of a hypothetical house price correction, centred in the Toronto and Vancouver areas. We also assume financial stress significantly amplifies the macroeconomic impact of the house price decline.
This paper explains the nature of interest rates in the U.S. federal funds market after the 2007-09 financial crisis. We build a model of the over-the-counter lending market that incorporates new aspects of the financial system: abundance of liquidity, different regulatory standards for banks, and arbitrage opportunities created by limited access to the facility granting interest on excess reserves.
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.
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.
This paper presents a model of strategic buyer-seller networks with information exchange between sellers. Prior to engaging in bargaining with buyers, sellers can share access to buyers for a negotiated transfer. We study how this information exchange affects overall market prices, volumes and welfare, given different initial market conditions and information sharing rules.
We use models to better understand and assess how risks could affect the financial system. In our hypothetical scenario, a house price correction and elevated financial stress weigh on the economy. An increased number of households and businesses have difficulty repaying loans. Nonetheless, the large banks remain resilient.