论文标题
具有高阶矩的投资组合选择模型的全局优化
Global optimization for the portfolio selection model with high-order moments
论文作者
论文摘要
在本文中，我们研究了多项式投资组合优化（PPO）的全球最优性。 PPO是一种具有高阶矩和灵活风险偏好参数的投资组合选择模型。我们引入了一种扰动样品平均近似方法，该方法可以以线性圆锥优化的形式对PPO的稳健近似。近似问题可以通过力矩SOS弛豫在全球解决。我们总结了一种半决算法，该算法可用于查找PPO的最佳值和优化器集的可靠近似值。给出了数值示例以显示算法的效率。
In this paper, we study the global optimality of polynomial portfolio optimization (PPO). The PPO is a kind of portfolio selection model with high-order moments and flexible risk preference parameters. We introduce a perturbation sample average approximation method, which can give a robust approximation of the PPO in form of linear conic optimization. The approximated problem can be solved globally with Moment-SOS relaxations. We summarize a semidefinite algorithm, which can be used to find reliable approximations of the optimal value and optimizer set of the PPO. Numerical examples are given to show the efficiency of the algorithm.
