Approximating Optimal Asset Allocations using Simulated Bifurcation

Thomas Bouquet, Mehdi Hmyene, Fran\c{c}ois Porcher, Lorenzo Pugliese and Jad Zeroual

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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.

Date: 2021-08, Revised 2021-12
New Economics Papers: this item is included in nep-isf and nep-ore
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