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Approximating Optimal Asset Allocations using Simulated Bifurcation

arXiv
Authors: Thomas Bouquet, Mehdi Hmyene, François Porcher, Lorenzo Pugliese, Jad Zeroual

Year

2021

Paper ID

62548

Status

Preprint

Abstract Read

~2 min

Abstract Words

72

Citations

N/A

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.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2021 reference point for readers tracking recent quantum research.
  • This paper investigates the application of Simulated Bifurcation algorithms to approximate optimal asset allocations.

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