A Robust Set-Valued Scenario Approach for Handling Modeling Risk in Portfolio Optimization

A Robust Set-Valued Scenario Approach for Handling Modeling Risk in Portfolio Optimization
复制标题

用于处理投资组合优化中的建模风险的稳健的集值场景方法

DOI:
10.21314/jcf.2015.307
复制
发表时间:
2015-08
影响因子:
0.9
通讯作者:
Li D.
Li D.
中科院分区:
经济学4区
文献类型:
--
作者:
Zhu S. S.;Ji X. D.;Li D.

文献摘要

参考文献

被引文献

相似文献

对于在下行风险度量下的投资组合优化,例如条件风险价值或下偏矩,我们经常调用场景方法来近似计算风险时涉及的高维积分。因此,两种类型的建模风险可能会出现在这个过程中:在确定资产收益率的分布和近似给定的分布与情景所造成的误差的不确定性。为了在一个统一的框架内处理这两种类型的建模风险,我们提出了一个数学上易于处理的集值情景方法。更具体地说,当卖空是不允许的,鲁棒的投资组合选择问题建模的最小-最大决策框架内使用几种类型的集值的情况下,可以转化为线性规划或二阶锥规划。内点法可以有效地解决这些问题。所提出的集值情景方法不仅可以用来作为一种方法,以减轻建模风险,但也作为一个有用的工具,用于评估建模风险的影响。我们的模拟分析和实证研究表明,稳健性并不一定意味着保守性,投资组合的表现在很大程度上受到投资风格的回报-风险权衡和建模风险变得显着时,积极的策略。
For portfolio optimization under downside risk measures, such as conditional value-at-risk or lower partial moments, we often invoke a scenario approach to approximate the high-dimensional integral involved when calculating risk. Consequently, two types of modeling risk may arise from this procedure: uncertainty in determining the distribution of asset returns and the error caused by approximating a given distribution with scenarios. To handle these two types of modeling risk within a unified framework, we propose a mathematically tractable set-valued scenario approach. More specifically, when short selling is not permitted, the robust portfolio selection problems modeled within a minimum-maximum decision framework using several types of set-valued scenarios can be translated into linear programs or second-order cone programs. These can be efficiently solved by the interior point method. The proposed set-valued scenario approach can be used not only as a methodology to alleviate the modeling risk but also as a useful tool for evaluating the impact of modeling risk. Our simulation analysis and empirical study show that robustness does not necessarily imply conservativeness, portfolio performance is affected by the investment style characterized by the return-risk tradeoff to a large degree and modeling risk only becomes significant when an aggressive strategy is adopted.
DOI: 10.1017/s0022109000023346
发表时间: 1977-11
影响因子: 3.9
作者:
V. Bawa;E. Lindenberg
通讯作者: V. Bawa;E. Lindenberg
DOI: --
发表时间: 1977
期刊: The American Economic Review
影响因子: --
作者:
P. Fishburn
通讯作者: P. Fishburn
DOI: 10.1023/a:1022238119491
发表时间: 2002
影响因子: 1.7
作者:
H. Konno;Hayato Waki;Atsushi Yuuki
通讯作者: H. Konno;Hayato Waki;Atsushi Yuuki
DOI: 10.2139/ssrn.563443
发表时间: 2003-02
影响因子: 2.7
作者:
A. d’Aspremont;L. Ghaoui
通讯作者: A. d’Aspremont;L. Ghaoui
DOI: 10.1287/moor.28.1.1.14260
发表时间: 2003-02-01
影响因子: 1.7
作者:
Goldfarb, D;Iyengar, G
通讯作者: Iyengar, G