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Portfolio Optimisation Using the D-Wave Quantum Annealer

arXiv 2012.01121 ↗First posted 13 Nov 2020q-fin.PM math.OC quant-phcited by 10

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Abstract (arXiv)

The first quantum computers are expected to perform well at quadratic optimisation problems. In this paper a quadratic problem in finance is taken, the Portfolio Optimisation problem. Here, a set of assets is chosen for investment, such that the total risk is minimised, a minimum return is realised and a budget constraint is met. This problem is solved for several instances in two main indices, the Nikkei225 and the S&P500 index, using the state-of-the-art implementation of D-Wave's quantum annealer and its hybrid solvers. The results are benchmarked against conventional, state-of-the-art, commercially available tooling. Results show that for problems of the size of the used instances, the D-Wave solution, in its current, still limited size, comes already close to the performance of commercial solvers.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Nov 2020.

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Citing papers per year: 2022: 2; 2023: 1; 2024: 2; 2025: 3; 2026: 2.

10 papers.