Quantum walk-based portfolio optimisation

TL;DR

This paper introduces a quantum walk-based algorithm that significantly improves the efficiency of portfolio optimisation on near-term quantum computers, outperforming previous hybrid quantum-classical approaches.

Contribution

It presents a novel Quantum Walk Optimisation Algorithm that achieves better performance than existing quantum algorithms for portfolio optimisation.

Findings

Quantum Walk Algorithm finds higher quality solutions

Performance surpasses hybrid quantum-classical methods

Suitable for near-term noisy quantum devices

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.