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Portfolio Optimisation Using the D-Wave Quantum Annealer

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  • Frank Phillipson
  • Harshil Singh Bhatia

Abstract

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.

Suggested Citation

  • Frank Phillipson & Harshil Singh Bhatia, 2020. "Portfolio Optimisation Using the D-Wave Quantum Annealer," Papers 2012.01121, arXiv.org.
    • Handle: RePEc:arx:papers:2012.01121
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    References listed on IDEAS

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    1. Duan Li & Xiaoling Sun & Shenshen Gu & Jianjun Gao & Chunli Liu, 2010. "Polynomially Solvable Cases of Binary Quadratic Programs," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Rentsen Enkhbat & Ider Tseveendorj (ed.), Optimization and Optimal Control, pages 199-225, Springer.
    2. Tao Pang & Katherine Varga, 2019. "Portfolio Optimization for Assets with Stochastic Yields and Stochastic Volatility," Journal of Optimization Theory and Applications, Springer, vol. 182(2), pages 691-729, August.
    3. Jeffrey Cohen & Alex Khan & Clark Alexander, 2020. "Portfolio Optimization of 40 Stocks Using the DWave Quantum Annealer," Papers 2007.01430, arXiv.org.
    4. Xidonas, Panos & Mavrotas, George & Hassapis, Christis & Zopounidis, Constantin, 2017. "Robust multiobjective portfolio optimization: A minimax regret approach," European Journal of Operational Research, Elsevier, vol. 262(1), pages 299-305.
    5. Iordanis Kerenidis & Anupam Prakash & D'aniel Szil'agyi, 2019. "Quantum Algorithms for Portfolio Optimization," Papers 1908.08040, arXiv.org.
    6. Jeffrey Cohen & Alex Khan & Clark Alexander, 2020. "Portfolio Optimization of 60 Stocks Using Classical and Quantum Algorithms," Papers 2008.08669, arXiv.org.
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    Cited by:

    1. Fred Glover & Gary Kochenberger & Rick Hennig & Yu Du, 2022. "Quantum bridge analytics I: a tutorial on formulating and using QUBO models," Annals of Operations Research, Springer, vol. 314(1), pages 141-183, July.
    2. A. Ege Yilmaz & Stefan Stettler & Thomas Ankenbrand & Urs Rhyner, 2023. "Grover Search for Portfolio Selection," Papers 2308.13063, arXiv.org.

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