G17 - Financial Forecasting and Simulation - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-29T14:25:15+00:00Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model
https://www.bankofcanada.ca/2022/10/technical-report-122/
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.2022-10-03T16:29:10+00:00enForecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model2022-10-03Economic modelsFinancial institutionsFinancial stabilityFinancial system regulation and policiesTechnical Report 2022-122https://www.bankofcanada.ca/wp-content/uploads/2022/10/tr122.pdfTechnical Report 2022-122Gabriel BruneauThibaut DupreyRuben HippOctober 2022CC2C22C5C52C53GG1G17G2G21G28Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning
https://www.bankofcanada.ca/2022/06/staff-working-paper-2022-29/
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.2022-06-28T15:47:31+00:00enQuantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning2022-06-28Business fluctuations and cyclesCentral bank researchEconometric and statistical methodsEconomic modelsFinancial stabilityStaff Working Paper 2022-29https://www.bankofcanada.ca/wp-content/uploads/2022/06/swp2022-29.pdfStaff Working Paper 2022-29Vladimir SkavyshSofia PriazhkinaDiego GualaThomas BromleyJune 2022CC1C15C6C61C63C68C7EE1E13GG1G17G2G21