Active allocation of systematic risk and control of risk sensitivity in portfolio optimization
Active allocation of systematic risk and control of risk sensitivity in portfolio optimization
复制标题
投资组合优化中系统性风险的主动配置和风险敏感性的控制
DOI：
10.1016/j.ejor.2013.02.016
复制
发表时间：
2013-08-01
影响因子：
6.4
通讯作者：
Li, Duan
中科院分区：
文献类型：
--
作者：
Li, Yingjie;Zhu, Shushang;Li, Duan
投资组合风险可以分解为系统性风险和非系统性风险两部分。众所周知，非系统性风险可以通过多元化来消除，而系统性风险却不能。因此，除了单一的小型投资组合之外，投资组合的风险始终以系统性风险为主。本文在均值-方差框架下提出了一种在投资组合优化中主动分配系统风险的模型，也可以理解为在投资组合选择中控制风险敏感性的模型。虽然由此产生的问题一般来说是一个臭名昭著的非凸二次约束二次规划，但由于定义的边际系统风险贡献的特征以及通过因子模型对系统风险进行建模的方式，问题的表述具有一些特殊的结构。通过利用这种特殊的问题特征，我们设计了一种基于二阶锥松弛的高效且全局收敛的分支定界求解算法。虽然实证研究表明，所提出的模型是主动投资组合风险管理的首选工具，但数值实验也表明，与商业软件 BARON 相比，所提出的解决方法更加有效。 (C) 2013 Elsevier B.V. 保留所有权利。
Portfolio risk can be decomposed into two parts, the systematic risk and the nonsystematic risk. It is well known that the nonsystematic risk can be eliminated by diversification, while the systematic risk cannot. Thus, the portfolio risk, except for that of undiversified small portfolios, is always dominated by the systematic risk. In this paper, under the mean-variance framework, we propose a model for actively allocating the systematic risk in portfolio optimization, which can also be interpreted as a model of controlling risk sensitivity in portfolio selection. Although the resulting problem is, in general, a notorious non-convex quadratically constrained quadratic program, the problem formulation is of some special structures due to the features of the defined marginal systematic risk contribution and the way to model the systematic risk via a factor model. By exploiting such special problem characteristics, we design an efficient and globally convergent branch-and-bound solution algorithm, based on a second-order cone relaxation. While empirical study demonstrates that the proposed model is a preferred tool for active portfolio risk management, numerical experiments also show that the proposed solution method is more efficient when compared to the commercial software BARON. (C) 2013 Elsevier B.V. All rights reserved.