Quantum walk-based portfolio optimisation

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.

Automated summary

This paper introduces a highly efficient quantum algorithm for portfolio optimization on near-term noisy intermediate-scale quantum computers. By utilizing the newly developed Quantum Walk Optimization Algorithm, it demonstrates significantly improved performance in finding high-quality solutions to the portfolio optimization problem compared to previous research.