Quantum computing for finance: Overview and prospects

We discuss how quantum computation can be applied to financial problems, providing an overview of current approaches and potential prospects. We review quantum optimization algorithms , and expose how quantum annealers can be used to optimize portfolios, find arbitrage opportunities, and perform credit scoring. We also discuss deep-learning in finance, and suggestions to improve these methods through quantum machine learning . Finally, we consider quantum amplitude estimation , and how it can result in a quantum speed-up for Monte Carlo sampling. This has direct applications to many current financial methods, including pricing of derivatives and risk analysis . Perspectives are also discussed.

# Quantum Computing Algorithms and Architecture # Computer Science # Stochastic processes and financial applications # Economics, Econometrics and Finance # Quantum Information and Cryptography # Physics and Astronomy

Román Orús, Samuel Mugel, Enrique Lizaso (2019). "Quantum computing for finance: Overview and prospects". Reviews in Physics. https://doi.org/10.1016/j.revip.2019.100028