英文标题：
《Generalized Information Ratio》
---
作者：
Zhongzhi Lawrence He
---
最新提交年份：
2018
---
英文摘要：
  Alpha-based performance evaluation may fail to capture correlated residuals due to model errors. This paper proposes using the Generalized Information Ratio (GIR) to measure performance under misspecified benchmarks. Motivated by the theoretical link between abnormal returns and residual covariance matrix, GIR is derived as alphas scaled by the inverse square root of residual covariance matrix. GIR nests alphas and Information Ratio as special cases, depending on the amount of information used in the residual covariance matrix. We show that GIR is robust to various degrees of model misspecification and produces stable out-of-sample returns. Incorporating residual correlations leads to substantial gains that alleviate model error concerns of active management.
---
中文摘要：
由于模型错误，基于Alpha的性能评估可能无法捕获相关残差。本文建议使用广义信息比（GIR）来衡量错误基准下的性能。基于异常收益率与残差协方差矩阵之间的理论联系，GIR被导出为残差协方差矩阵平方根反比的α。GIR根据残差协方差矩阵中使用的信息量，将字母和信息比率嵌套为特例。我们表明，GIR对不同程度的模型错误具有鲁棒性，并产生稳定的样本外回报。引入残差相关性可以带来实质性的收益，从而缓解主动管理的模型误差问题。
---
分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Portfolio Management        项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
--
一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
--

---
PDF下载：
-->