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Approximating Optimal Asset Allocations using Simulated Bifurcation

Author

Listed:
  • Thomas Bouquet
  • Mehdi Hmyene
  • Franc{c}ois Porcher
  • Lorenzo Pugliese
  • Jad Zeroual

Abstract

This paper investigates the application of Simulated Bifurcation algorithms to approximate optimal asset allocations. It will provide the reader with an explanation of the physical principles underlying the method and a Python implementation of the latter applied to 441 assets belonging to the S&P500 index. In addition, the paper tackles the problem of the selection of an optimal sub-allocation; in this particular case, we find an adequate solution in an unrivaled timescale.

Suggested Citation

  • Thomas Bouquet & Mehdi Hmyene & Franc{c}ois Porcher & Lorenzo Pugliese & Jad Zeroual, 2021. "Approximating Optimal Asset Allocations using Simulated Bifurcation," Papers 2108.03092, arXiv.org, revised Dec 2021.
    • Handle: RePEc:arx:papers:2108.03092
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Kyle Steinhauer & Takahisa Fukadai & Sho Yoshida, 2020. "Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation," Papers 2009.08412, arXiv.org.
    3. Galluccio, Stefano & Bouchaud, Jean-Philippe & Potters, Marc, 1998. "Rational decisions, random matrices and spin glasses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 259(3), pages 449-456.
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