论文标题
使用凸优化的高斯混合物返回和指数效用的投资组合结构
Portfolio Construction with Gaussian Mixture Returns and Exponential Utility via Convex Optimization
论文作者
论文摘要
假设资产回报具有高斯混合物（GM）分布，我们考虑选择最佳投资组合的问题，目的是最大化预期的指数效用。在本文中，我们表明此问题是凸，并且很容易使用特定于域的语言进行凸优化，而无需采样或方案。然后，我们展示如何将最小化风险熵价值的紧密相关问题作为凸优化问题提出。
We consider the problem of choosing an optimal portfolio, assuming the asset returns have a Gaussian mixture (GM) distribution, with the objective of maximizing expected exponential utility. In this paper we show that this problem is convex, and readily solved exactly using domain-specific languages for convex optimization, without the need for sampling or scenarios. We then show how the closely related problem of minimizing entropic value at risk can also be formulated as a convex optimization problem.
