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Quantum Machine Learning for Finance

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arxiv 2109.04298 v1 pith:3UMXPJDQ submitted 2021-09-09 quant-ph cs.LG

Marco Pistoia , Syed Farhan Ahmad , Akshay Ajagekar , Alexander Buts , Shouvanik Chakrabarti , Dylan Herman , Shaohan Hu , Andrew Jena
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Pierre Minssen Pradeep Niroula Arthur Rattew Yue Sun Romina Yalovetzky
This is my paper · ORCID
classification quant-phcs.LG
keywords quantumfinancecomputersindustrylearningmachineachievealgorithms
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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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