00000nam 2200000zi 4500 9.913466 CaOODSP 20221107182810 m o d f cr |n||||||||| 220715t20222022onc ob f|0| 0 eng d CaOODSP eng rda CaOODSP n-cn--- FB3-5/2022-29E-PDF Skavysh, Vladimir, author. Quantum Monte Carlo for economics : stress testing and macroeconomic deep learning / by Vladimir Skavysh, Sofia Priazhkina, Diego Guala and Thomas R. Bromley. [Ottawa] : Bank of Canada = Banque du Canada, 2022. ©2022 1 online resource (ii, 59 pages). text txt rdacontent computer c rdamedia online resource cr rdacarrier Staff working paper = Document de travail du personnel, 1701-9397 ; 2022-29 "Last updated: June 28, 2022." Includes bibliographical references (pages 39-46). "Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so. We identify a large class of economic problems suitable for improvements. Then, we illustrate how to formulate and encode on quantum circuit two applications: (a) a bank stress testing model with credit shocks and fire sales and (b) a dynamic stochastic general equilibrium (DSGE) model solved with deep learning, and further demonstrate potential efficiency gain. We also present a few innovations in the QMC algorithm itself and in how to benchmark it to classical MC"--Abstract. Quantum computing. Economic forecasting. Informatique quantique. Prévision économique. Bank of Canada, issuing body. Staff working paper (Bank of Canada) 2022-29. (CaOODSP)9.806221 PDF 1.23 MB https://publications.gc.ca/collections/collection_2022/banque-bank-canada/FB3-5-2022-29-eng.pdf