Bio

Vladimir Skavysh is the founding leader of the Bank of Canada’s Quantum Lab for Advanced Analytics and a Senior Data Scientist in its Data Science Division. His research spans artificial intelligence, deep learning, quantum computing, big data, large language models and agent-based simulations. He has initiated and led more than ten collaborative research projects with industry partners, central banks and universities—overseeing the entire project lifecycle and mentoring emerging talent. Earlier in his career, Vladimir worked as a physicist specializing in dark energy and neutron interferometry.

Research Field(s): Agent-Based Modelling Applied Econometrics Applied Microeconomics Asset Pricing Banking Business Models Data Science Digital Currency Digital Economy Economic and Financial Networks Financial Economics Financial Institutions Financial Markets Fintech Forecasting Game Theory Macroeconomic Theory Macroeconomics Market Microstructure Money and Banking Payments Economics Quantitative Macroeconomics Risk Management Technological Change Time Series

Staff analytical notes

Market structure of cryptoasset exchanges: Introduction, challenges and emerging trends

Staff Analytical Note 2024-2 Vladimir Skavysh, Jacob Sharples, Sofia Priazhkina, Salman H. Hasham
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.
Content Type(s): Staff research, Staff analytical notes Research Topic(s): Digital currencies and fintech, Payment clearing and settlement systems JEL Code(s): G, G1, G15, L, L1

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Staff working papers

Digital Payments in Firm Networks: Theory of Adoption and Quantum Algorithm

Staff Working Paper 2024-17 Sofia Priazhkina, Samuel Palmer, Pablo Martín-Ramiro, Román Orús, Samuel Mugel, Vladimir Skavysh
We build a network formation game of firms with trade flows to study the adoption and usage of a new digital currency as an alternative to correspondent banking.
Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Digital currencies and fintech, Digitalization, Economic models, Financial institutions, Payment clearing and settlement systems, Sectoral balance sheet JEL Code(s): C, C6, C7, C71, D, D4, D8, D85, G, L, L2, L22

Improving the Efficiency of Payments Systems Using Quantum Computing

Staff Working Paper 2022-53 Christopher McMahon, Donald McGillivray, Ajit Desai, Francisco Rivadeneyra, Jean-Paul Lam, Thomas Lo, Danica Marsden, Vladimir Skavysh
We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays.
Content Type(s): Staff research, Staff working papers Research Topic(s): Digital currencies and fintech, Financial institutions, Financial services, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): C, C6, C61, C63, D, D8, D83, E, E4, E42, E5, E58

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 Research 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

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Journal publications