Quantum walk-based portfolio optimisation

Nicholas Slate, Edric Matwiejew, Samuel Marsh, Jingbo Wang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


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.
Original languageEnglish
Article numberA3
Number of pages17
JournalQuantum: the open journal for quantum science
Publication statusPublished - 31 Jul 2021


Dive into the research topics of 'Quantum walk-based portfolio optimisation'. Together they form a unique fingerprint.

Cite this