IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2311.06621.html
   My bibliography  Save this paper

Quantum Computing for Financial Mathematics

Author

Listed:
  • Antoine Jacquier
  • Oleksiy Kondratyev
  • Gordon Lee
  • Mugad Oumgari

Abstract

Quantum computing has recently appeared in the headlines of many scientific and popular publications. In the context of quantitative finance, we provide here an overview of its potential.

Suggested Citation

  • Antoine Jacquier & Oleksiy Kondratyev & Gordon Lee & Mugad Oumgari, 2023. "Quantum Computing for Financial Mathematics," Papers 2311.06621, arXiv.org.
    • Handle: RePEc:arx:papers:2311.06621
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2311.06621
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Filipe Fontanela & Antoine Jacquier & Mugad Oumgari, 2019. "A Quantum algorithm for linear PDEs arising in Finance," Papers 1912.02753, arXiv.org, revised Feb 2021.
    2. 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.
    3. Samson Wang & Enrico Fontana & M. Cerezo & Kunal Sharma & Akira Sone & Lukasz Cincio & Patrick J. Coles, 2021. "Noise-induced barren plateaus in variational quantum algorithms," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    4. Jianjun Chen & Yongming Li & Ariel Neufeld, 2023. "Quantum Monte Carlo algorithm for solving Black-Scholes PDEs for high-dimensional option pricing in finance and its complexity analysis," Papers 2301.09241, arXiv.org, revised Apr 2024.
    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. Eric R. Anschuetz & Bobak T. Kiani, 2022. "Quantum variational algorithms are swamped with traps," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Junyu Liu & Minzhao Liu & Jin-Peng Liu & Ziyu Ye & Yunfei Wang & Yuri Alexeev & Jens Eisert & Liang Jiang, 2024. "Towards provably efficient quantum algorithms for large-scale machine-learning models," Nature Communications, Nature, vol. 15(1), pages 1-6, December.
    3. Enrico Fontana & Dylan Herman & Shouvanik Chakrabarti & Niraj Kumar & Romina Yalovetzky & Jamie Heredge & Shree Hari Sureshbabu & Marco Pistoia, 2024. "Characterizing barren plateaus in quantum ansätze with the adjoint representation," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. He, Zhimin & Deng, Maijie & Zheng, Shenggen & Li, Lvzhou & Situ, Haozhen, 2023. "GSQAS: Graph Self-supervised Quantum Architecture Search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    5. Wang, Shaoxuan & Shen, Yingtong & Liu, Xinjian & Zhang, Haoying & Wang, Yukun, 2024. "Variational quantum entanglement classification discrimination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    6. Sofiene Jerbi & Lukas J. Fiderer & Hendrik Poulsen Nautrup & Jonas M. Kübler & Hans J. Briegel & Vedran Dunjko, 2023. "Quantum machine learning beyond kernel methods," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    7. Manuel S. Rudolph & Jacob Miller & Danial Motlagh & Jing Chen & Atithi Acharya & Alejandro Perdomo-Ortiz, 2023. "Synergistic pretraining of parametrized quantum circuits via tensor networks," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    8. Michael Ragone & Bojko N. Bakalov & Frédéric Sauvage & Alexander F. Kemper & Carlos Ortiz Marrero & Martín Larocca & M. Cerezo, 2024. "A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    9. Huang, Chenyi & Zhang, Shibin & Chang, Yan & Yan, Lily, 2024. "Quantum metric learning with fuzzy-informed learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    10. 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.
    11. Huang, Fangyu & Tan, Xiaoqing & Huang, Rui & Xu, Qingshan, 2022. "Variational convolutional neural networks classifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    12. Takayuki Sakuma, 2020. "Application of deep quantum neural networks to finance," Papers 2011.07319, arXiv.org, revised May 2022.
    13. 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.
    14. 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).
    15. Elies Gil-Fuster & Jens Eisert & Carlos Bravo-Prieto, 2024. "Understanding quantum machine learning also requires rethinking generalization," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    16. Liang Xiang & Wenjie Jiang & Zehang Bao & Zixuan Song & Shibo Xu & Ke Wang & Jiachen Chen & Feitong Jin & Xuhao Zhu & Zitian Zhu & Fanhao Shen & Ning Wang & Chuanyu Zhang & Yaozu Wu & Yiren Zou & Jiar, 2024. "Long-lived topological time-crystalline order on a quantum processor," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    17. Kurowski, Krzysztof & Pecyna, Tomasz & Slysz, Mateusz & Różycki, Rafał & Waligóra, Grzegorz & Wȩglarz, Jan, 2023. "Application of quantum approximate optimization algorithm to job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 310(2), pages 518-528.
    18. Kamila Zaman & Alberto Marchisio & Muhammad Kashif & Muhammad Shafique, 2024. "PO-QA: A Framework for Portfolio Optimization using Quantum Algorithms," Papers 2407.19857, arXiv.org.
    19. Fangjun Hu & Saeed A. Khan & Nicholas T. Bronn & Gerasimos Angelatos & Graham E. Rowlands & Guilhem J. Ribeill & Hakan E. Türeci, 2024. "Overcoming the coherence time barrier in quantum machine learning on temporal data," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    20. F. H. B. Somhorst & R. Meer & M. Correa Anguita & R. Schadow & H. J. Snijders & M. Goede & B. Kassenberg & P. Venderbosch & C. Taballione & J. P. Epping & H. H. Vlekkert & J. Timmerhuis & J. F. F. Bul, 2023. "Quantum simulation of thermodynamics in an integrated quantum photonic processor," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

    More about this item

    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:arx:papers:2311.06621. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.