Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. We present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modeling, optimization, and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle.
@article{arxiv.2307.11230,
title = {Quantum computing for finance},
author = {Dylan Herman and Cody Googin and Xiaoyuan Liu and Yue Sun and Alexey Galda and Ilya Safro and Marco Pistoia and Yuri Alexeev},
journal= {arXiv preprint arXiv:2307.11230},
year = {2023}
}