Optimal portfolio choice with benchmarks
提出一种数值算法，能在一般偏好下求解投资者最优投资组合，尤其适用于目标函数和风险约束受基准影响的情况，并通过经典问题验证了算法的可靠性。
We construct an algorithm that makes it possible to numerically obtain an investor’s optimal portfolio under general preferences. In particular, the objective function and risks constraints may be driven by benchmarks (reflecting state-dependent preferences). We apply the algorithm to various classic optimal portfolio problems for which explicit solutions are available and show that our numerical solutions are compatible with them. This observation allows us to conclude that the algorithm can be trusted as a viable way to deal with portfolio optimisation problems for which explicit solutions are not in reach.