Approximating Optimal Asset Allocations using Simulated Bifurcation
Portfolio Management
2021-12-06 v3 Computational Finance
Quantum Physics
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.
Keywords
Cite
@article{arxiv.2108.03092,
title = {Approximating Optimal Asset Allocations using Simulated Bifurcation},
author = {Thomas Bouquet and Mehdi Hmyene and François Porcher and Lorenzo Pugliese and Jad Zeroual},
journal= {arXiv preprint arXiv:2108.03092},
year = {2021}
}