Robust portfolio selection problems
Robust portfolio selection problems
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DOI：
10.1287/moor.28.1.1.14260
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发表时间：
2003-02-01
影响因子：
1.7
通讯作者：
Iyengar, G
中科院分区：
文献类型：
--
作者：
Goldfarb, D;Iyengar, G
在本文中，我们将展示如何制定和解决稳健的投资组合选择问题：这些强大的配方的目标是系统地打击的最优投资组合的相关市场参数的估计的统计和建模误差的敏感性。我们引入“不确定性结构”的市场参数，并表明这些不确定性结构对应的鲁棒投资组合选择问题可以重新制定为二阶锥规划，因此，解决它们所需的计算工作量是可比的，所需的求解凸二次规划。此外，我们表明，这些不确定性结构对应的置信区域与统计过程估计市场参数。最后，我们展示了一个简单的配方，有效地计算强大的投资组合给定的原始市场数据和所需的信心水平。
In this paper we show how to formulate and solve robust portfolio selection problems: The objective of these robust formulations is to systematically combat the sensitivity of the optimal portfolio to statistical and modeling errors in the estimates of the relevant market parameters. We introduce "uncertainty structures" for the market parameters and show that the robust portfolio selection problems corresponding to these uncertainty structures can be reformulated as second-order cone programs and, therefore, the computational effort required to solve them is comparable to that required for solving convex quadratic programs. Moreover, we show that these uncertainty structures correspond to confidence regions associated with the statistical procedures employed to estimate the market parameters. Finally, we demonstrate a simple recipe for efficiently computing robust portfolios given raw market data and a desired level of confidence.