Approximating Optimal Asset Allocations using Simulated Bifurcation

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 SP in this particular case, we find an adequate solution within an unrivaled timescale.