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【FAJ】提高最优投资组合的风险预测能力

[发布日期]:2018-10-24  [浏览次数]:

Financial Analyst Journal, Volume 68, Issue3, 2012

提高最优投资组合的风险预测能力

作者:Jose Menchero (executive director at MSCI),

Jun Wang (vice president at MSCI),

D.J. Orr (vice president at MSCI)

摘要:样本的协方差矩阵往往低估最优投资组合的风险。在这篇文章中,我们识别出一种特殊的投资组合,称为“特征投资组合”,用于捕捉这些系统性偏差。此外,我们提出了估计特征组合偏差和调整协方差矩阵来消除这些偏差的方法。我们发现该方法有效地消除了最优投资组合的偏误。本文证明了调整后的协方差矩阵对于降低最优投资组合的样本外波动性是有效的。

Improving Risk Forecasts for Optimized Portfolios

Jose Menchero (executive director at MSCI), Jun Wang (vice president at MSCI), D.J. Orr (vice president at MSCI)

ABSTRACT

Sample covariance matrices tend to underestimate the risk of optimized portfolios. In this article, we identify special portfolios, termed “eigenportfolios,” that capture these systematic biases. Further, we present a methodology for estimating eigenportfolio biases and for adjusting the covariance matrix to remove these biases. We show that this procedure effectively removes the biases of optimized portfolios. We demonstrate that the adjusted covariance matrices are effective at reducing the out-of-sample volatilities of optimized portfolios.

原文链接:

https://www.cfapubs.org/doi/abs/10.2469/faj.v68.n3.5

翻译:秦秀婷



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