Quantum walk-based portfolio optimisation

N. Slate; E. Matwiejew; S. Marsh; J. B. Wang

doi:10.22331/q-2021-07-28-513

Quantum walk-based portfolio optimisation

N. Slate, E. Matwiejew, S. Marsh, and J. B. Wang

Department of Physics, The University of Western Australia, Perth WA 6009, Australia

Published:	2021-07-28, volume 5, page 513
Eprint:	arXiv:2011.08057v3
Doi:	https://doi.org/10.22331/q-2021-07-28-513
Citation:	Quantum 5, 513 (2021).

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Abstract

This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near-term noisy intermediate-scale quantum computers. Recent work by Hodson et al. (2019) explored potential application of hybrid quantum-classical algorithms to the problem of financial portfolio rebalancing. In particular, they deal with the portfolio optimisation problem using the Quantum Approximate Optimisation Algorithm and the Quantum Alternating Operator Ansatz. In this paper, we demonstrate substantially better performance using a newly developed Quantum Walk Optimisation Algorithm in finding high-quality solutions to the portfolio optimisation problem.

Featured image: The historic and projected expected returns for an optimised financial portfolio using the quantum walk-based optimisation algorithm.

► BibTeX data

@article{Slate2021quantumwalkbased,
  doi = {10.22331/q-2021-07-28-513},
  url = {https://doi.org/10.22331/q-2021-07-28-513},
  title = {Quantum walk-based portfolio optimisation},
  author = {Slate, N. and Matwiejew, E. and Marsh, S. and Wang, J. B.},
  journal = {{Quantum}},
  issn = {2521-327X},
  publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}},
  volume = {5},
  pages = {513},
  month = jul,
  year = {2021}
}

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