Related papers: Quantum Machine Learning for Finance

Quantum Machine Learning for Finance

URL: http://arxiv.org/abs/2109.04298v1
Date: Thu, 9 Sep 2021 14:20:10 GMT
Title: Quantum Machine Learning for Finance
Authors: Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur Rattew, Yue Sun, Romina Yalovetzky
Abstract summary: Finance is estimated to be the first industry sector to benefit from Quantum Computing. This review paper presents the state of the art of quantum algorithms for financial applications.
Score: 52.97198108304122
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term. This review paper presents the state of the art of quantum algorithms for financial applications, with particular focus to those use cases that can be solved via Machine Learning.

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