IDEAS home Printed from https://ideas.repec.org/p/cnb/wpaper/2023-1.html
   My bibliography  Save this paper

Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer

Author

Listed:
  • Martin Vesely

Abstract

Portfolio optimization is an inseparable part of strategic asset allocation at the Czech National Bank. Quantum computing is a new technology offering algorithms for that problem. The capabilities and limitations of quantum computers with regard to portfolio optimization should therefore be investigated. In this paper, we focus on applications of quantum algorithms to dynamic portfolio optimization based on the Markowitz model. In particular, we compare algorithms for universal gate-based quantum computers (the QAOA, the VQE and Grover adaptive search), single-purpose quantum annealers, the classical exact branch and bound solver and classical heuristic algorithms (simulated annealing and genetic optimization). To run the quantum algorithms we use the IBM QuantumTM gate-based quantum computer. We also employ the quantum annealer offered by D-Wave. We demonstrate portfolio optimization on finding the optimal currency composition of the CNB's FX reserves. A secondary goal of the paper is to provide staff of central banks and other financial market regulators with literature on quantum optimization algorithms, because financial firms are active in finding possible applications of quantum computing.

Suggested Citation

  • Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Working Papers 2023/1, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2023/1
    as

    Download full text from publisher

    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2023_01.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alberto Peruzzo & Jarrod McClean & Peter Shadbolt & Man-Hong Yung & Xiao-Qi Zhou & Peter J. Love & Alán Aspuru-Guzik & Jeremy L. O’Brien, 2014. "A variational eigenvalue solver on a photonic quantum processor," Nature Communications, Nature, vol. 5(1), pages 1-7, September.
    2. John D. C. Little & Katta G. Murty & Dura W. Sweeney & Caroline Karel, 1963. "An Algorithm for the Traveling Salesman Problem," Operations Research, INFORMS, vol. 11(6), pages 972-989, December.
    3. Martin Vesel'y, 2022. "Application of Quantum Computers in Foreign Exchange Reserves Management," Papers 2203.15716, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abha Naik & Esra Yeniaras & Gerhard Hellstern & Grishma Prasad & Sanjay Kumar Lalta Prasad Vishwakarma, 2023. "From Portfolio Optimization to Quantum Blockchain and Security: A Systematic Review of Quantum Computing in Finance," Papers 2307.01155, arXiv.org.
    2. Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Papers 2303.01909, arXiv.org.
    3. José Berenguel & L. Casado & I. García & Eligius Hendrix, 2013. "On estimating workload in interval branch-and-bound global optimization algorithms," Journal of Global Optimization, Springer, vol. 56(3), pages 821-844, July.
    4. Xinbiao Wang & Yuxuan Du & Zhuozhuo Tu & Yong Luo & Xiao Yuan & Dacheng Tao, 2024. "Transition role of entangled data in quantum machine learning," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    5. N. Kazazakis & C. S. Adjiman, 2018. "Arbitrarily tight $$\alpha $$ α BB underestimators of general non-linear functions over sub-optimal domains," Journal of Global Optimization, Springer, vol. 71(4), pages 815-844, August.
    6. Joaquín Antonio Pacheco Bonrostro, 1995. "Problemas de rutas con carga y descarga en sistemas lifo: soluciones exactas," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 3, pages 69-86, Junio.
    7. Tomáš Režnar & Jan Martinovič & Kateřina Slaninová & Ekaterina Grakova & Vít Vondrák, 2017. "Probabilistic time-dependent vehicle routing problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 545-560, September.
    8. Bogna MRÓWCZYŃSKA, 2015. "Multicriteria vehicle routing problem solved by artificial immune system," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 10(3), pages 141-152, September.
    9. Ye, Zi & Yu, Kai & Guo, Gong-De & Lin, Song, 2024. "Quantum self-organizing feature mapping neural network algorithm based on Grover search algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    10. Michael Windham & J. Hutchinson & Shizuhiko Nishisato & Ludovic Lebart & George Furnas & Richard Dubes & Frank Critchley & A. Gordon & Fionn Murtagh & Ulf Bockenholt & Philip Hopke & Daniel Wartenberg, 1988. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 5(1), pages 105-154, March.
    11. Nikolakopoulos, Athanassios & Sarimveis, Haralambos, 2007. "A threshold accepting heuristic with intense local search for the solution of special instances of the traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1911-1929, March.
    12. Schulz, Arne & Pfeiffer, Christian, 2024. "Using fixed paths to improve branch-and-cut algorithms for precedence-constrained routing problems," European Journal of Operational Research, Elsevier, vol. 312(2), pages 456-472.
    13. Zhang Yang & Jiacheng Li & Lei Li, 2020. "Time-Dependent Theme Park Routing Problem by Partheno-Genetic Algorithm," Mathematics, MDPI, vol. 8(12), pages 1-20, December.
    14. Lawrence Hubert & Frank Baker, 1978. "Applications of combinatorial programming to data analysis: The traveling salesman and related problems," Psychometrika, Springer;The Psychometric Society, vol. 43(1), pages 81-91, March.
    15. A. S. Santos & A. M. Madureira & M. L. R. Varela, 2018. "The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance," Journal of Mathematics, Hindawi, vol. 2018, pages 1-14, July.
    16. Kamila Zaman & Alberto Marchisio & Muhammad Kashif & Muhammad Shafique, 2024. "PO-QA: A Framework for Portfolio Optimization using Quantum Algorithms," Papers 2407.19857, arXiv.org.
    17. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    18. Ohashi, Kazumasa, 1999. "Dynamic process planning system for a machining center in an FMS environment," International Journal of Production Economics, Elsevier, vol. 60(1), pages 457-464, April.
    19. Luminiţa Nicolescu & Cristina Galalae & Alexandru Voicu, 2013. "Solving a Supply Chain Management Problem to Near Optimality Using Ant Colony Optimization, in an International Context," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 15(33), pages 8-26, February.
    20. Eric R. Anschuetz & Bobak T. Kiani, 2022. "Quantum variational algorithms are swamped with traps," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    More about this item

    Keywords

    Foreign exchange reserves; portfolio optimization; quadratic unconstrained binary optimization; quantum computing;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cnb:wpaper:2023/1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jan Babecky (email available below). General contact details of provider: https://edirc.repec.org/data/cnbgvcz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.