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Quantum Finance - an Overview

EasyChair Preprint no. 6071

8 pagesDate: July 13, 2021


With the advent of emerging technologies, it has become possible to have a road-map which tackles really difficult real world challenges. From the past decade, there has been significant development in the field of Quantum Computing. The advantages that it provides can take an industry decades ahead of where it stands right now. One of the fields with rigorous implementation of the same technology is, Financial Markets. Quantum Finance has been one of the most promising field of application and development with significantly improved results. The implementation of various algorithms such as Variational Quantum Eigensolver(VQE) and Quantum Approximate Optimization Algorithm(QAOA) to map and solve problem statements pertaining to Financial use cases have proven to be immensely beneficial for the industry. The paper intends to scratch the tip of the field and have an overlook on how the industry giants like Goldman Sachs, JP Morgan Chase & Co. and Consulting giants like McKinsey & Co. are working towards the development of solutions to tackle such problems. The paper tries to give an overview of the financial market history and specifically look into a Mean Variance Portfolio Optimization(PO) Problem using existing Cloud Quantum Computational Frameworks and analyze the results.

Keyphrases: PO, QAOA, VQE

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {C H Renumadhavi and Archit Srivastava and Ashutosh Kumar Singh and Anushka Mittal},
  title = {Quantum Finance - an Overview},
  howpublished = {EasyChair Preprint no. 6071},

  year = {EasyChair, 2021}}
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