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首页> 外文期刊>Review of Managerial Science >Analysing the information embedded in the optimal mean-variance weights: CAPM versus Bamberg and Dorfleitner model
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Analysing the information embedded in the optimal mean-variance weights: CAPM versus Bamberg and Dorfleitner model

机译:分析嵌入最佳均方差权重的信息:CAPM与Bamberg和Dorfleitner模型

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This paper is centred on the analysis of the information embedded in the optimal weights of the assets in the CAPM and the Bamberg-Dorfleitner model. On this basis, first we find a functional relationship between the optimal weights of both models. Next, we find a set of performance indicators that express the contribution of each asset to the reward/volatility ratio measured as the Sharpe ratio or through a utility function. For the Bamberg-Dorfleitner model these indicators also lead to identify the contribution of each independent variable to the reward/volatility ratio. Technically, these connections are obtained through the covariance-normalized portfolio that consists of a transformation of the inverted covariance matrix. The additive property of covariances is transmitted to the indicators. These results enable investors and portfolio managers to obtain a precise knowledge of the causes of the value of the reward/volatility ratio. From the corporate point of view, this approach contributes to a better identification of the features of the different types of investors to whom to focus the corporate financial policy.
机译:本文的重点是分析CAPM和Bamberg-Dorfleitner模型中资产的最佳权重所包含的信息。在此基础上,首先我们找到两个模型的最佳权重之间的函数关系。接下来,我们找到一组绩效指标,这些指标表示每种资产对以夏普比率或效用函数衡量的回报/波动率的贡献。对于Bamberg-Dorfleitner模型,这些指标还可以确定每个自变量对奖励/波动率的贡献。从技术上讲,这些连接是通过协方差归一化投资组合获得的,该投资组合由反向协方差矩阵的转换组成。协方差的可加性被传输到指标。这些结果使投资者和投资组合经理能够准确了解奖励/波动率价值的原因。从公司的角度来看,这种方法有助于更好地确定将公司财务政策作为重点的不同类型投资者的特征。

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