Quantum Monte Carlo for economics : stress testing and macroeconomic deep learning / by Vladimir Skavysh, Sofia Priazhkina, Diego Guala and Thomas R. Bromley.: FB3-5/2022-29E-PDF
"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.
Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.913466&sl=0
| Department/Agency |
|
|---|---|
| Title | Quantum Monte Carlo for economics : stress testing and macroeconomic deep learning / by Vladimir Skavysh, Sofia Priazhkina, Diego Guala and Thomas R. Bromley. |
| Series title |
|
| Publication type | Monograph - View Master Record |
| Language | [English] |
| Format | Digital text |
| Electronic document | |
| Note(s) |
|
| Publishing information |
|
| Author / Contributor |
|
| Description | 1 online resource (ii, 59 pages). |
| Catalogue number |
|
| Subject terms |
Request alternate formats
To request an alternate format of a publication, complete the Government of Canada Publications email form. Use the form’s “question or comment” field to specify the requested publication.Page details
- Date modified: