IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2410.05932.html
   My bibliography  Save this paper

Quantum-Inspired Portfolio Optimization In The QUBO Framework

Author

Listed:
  • Ying-Chang Lu
  • Yen-Jui Chang
  • Lien-Po Yu
  • Chao-Ming Fu

Abstract

A quantum-inspired optimization approach is proposed to study the portfolio optimization aimed at maximizing the returns of investment portfolio while minimizing its risk by diversifying investment across different asset classes. By integrating conventional approaches with quantum-inspired methods and simulation techniques for penalty coefficient estimation, this approach enables faster solutions to portfolio optimization. The proposed two-stage search strategy further enhances the method by starting with a broad search to quickly identify potential solutions and then refining these results to increase accuracy. The effectiveness of our approach is validated through experiments using a real-world dataset of quarterly financial data spanning ten years. Moreover, the effectiveness of various portfolio strategies under volatile market conditions is also investigated with emphasis on the robustness and predictive capacity of our methodology. This research contributes to the growing body of literature on quantum-inspired techniques in finance, demonstrating its potential as a powerful tool for asset allocation and portfolio management.

Suggested Citation

  • Ying-Chang Lu & Yen-Jui Chang & Lien-Po Yu & Chao-Ming Fu, 2024. "Quantum-Inspired Portfolio Optimization In The QUBO Framework," Papers 2410.05932, arXiv.org.
    • Handle: RePEc:arx:papers:2410.05932
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2410.05932
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Samuel Palmer & Serkan Sahin & Rodrigo Hernandez & Samuel Mugel & Roman Orus, 2021. "Quantum Portfolio Optimization with Investment Bands and Target Volatility," Papers 2106.06735, arXiv.org, revised Aug 2021.
    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. Martin Vesely, 2022. "Application of Quantum Computers in Foreign Exchange Reserves Management," Working Papers 2022/2, Czech National Bank.
    2. Martin Vesel'y, 2022. "Application of Quantum Computers in Foreign Exchange Reserves Management," Papers 2203.15716, arXiv.org.
    3. 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.

    More about this item

    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:2410.05932. 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.