The author also bringsforward multi-factor asset pricing model based on risk-metric indices, such as coefficient of beta, standard variance, standard semi-variance, average absolute deviation, value at risk, and factor variables, such as circulated market equity, exchange ratio, short-term historical return.
Besides traditional Mean-Variance model, many portfolio models can be found in literatures. For example, Mean-Absolute Deviation model, Mean-Semi Absolute Deviation model, Logarithm Utility model, Geometry Expected Earnings model, Safety-First model, and so on.
This paper, based on the basic analysis of drawbacks of Markowitz's portfolio model and portfolio models on the absolute deviation risk measure and E-Sh risk measure, develops a portfolio optimization model based on the new risk measure. The paper also provides methods for determing the optimal portfolio investment weights and portfolio efficient frontier. In addition, the paper presents comparative analysis about these models, and illustrates the effectiveness of our model with a practical example.
The empirical result shows that the absolute values of risk elasticity are more than 1 under various returns and it also indicates that the proposed model based on mean absolute deviation is better than mean variance model based on variance both in theory and in practice.
The author also bringsforward multi-factor asset pricing model based on risk-metric indices, such as coefficient of beta, standard variance, standard semi-variance, average absolute deviation, value at risk, and factor variables, such as circulated market equity, exchange ratio, short-term historical return.
Besides traditional Mean-Variance model, many portfolio models can be found in literatures. For example, Mean-Absolute Deviation model, Mean-Semi Absolute Deviation model, Logarithm Utility model, Geometry Expected Earnings model, Safety-First model, and so on.
This paper, based on the basic analysis of drawbacks of Markowitz's portfolio model and portfolio models on the absolute deviation risk measure and E-Sh risk measure, develops a portfolio optimization model based on the new risk measure. The paper also provides methods for determing the optimal portfolio investment weights and portfolio efficient frontier. In addition, the paper presents comparative analysis about these models, and illustrates the effectiveness of our model with a practical example.
In the empirical study,we apply the new model to Shanghai stock market,and compare the new model with the semi-variance model and the absolute-deviation model in quantitative and qualitative way. It can be drawn from comparison with the other two portfolio models that the semi-deviation portfolio model is better and practical.
The overall average absolute deviation was less than 1.0%.
Within the whole range of mixtures, mean absolute deviations between the determined and the actual milk fat content were below 0.5% and the maximum absolute deviation was not more than 1.0% when using the reference sample.
The overall mean absolute deviation was 0.04% for milk fat contents of 1 to 10% and 0.28% for milk fat contents of 10 to 90%.
The objective is to minimize the total absolute deviation of job completion times about the common due date.
The objective is the minimization of the mean weighted absolute deviation of job completion times from due dates.
The overall mean absolute deviation was 0.04% for milk fat contents of 1 to 10% and 0.28% for milk fat contents of 10 to 90%.
Approximation of expected returns and optimal decisions under uncertainty using mean and mean absolute deviation
The mean absolute deviation between theory and experiment (where available) for heats of hydrogenation of closed shell species with two non-hydrogen atoms is 4 kcal/mole for the basis set with full polarization.
Although the theoretical vertical transition energies correspond only approximately to experimental absorption band maxima, the mean absolute deviation was calculated to be 0.21?eV (1600?cm-1).
The new methodology (CBS-4MB) applied to a set of 114 molecules of different size significantly decreases the mean absolute deviation from 3.78 to 2.06?kcal/mol.
The overall average absolute deviation was less than 1.0%.
Within the whole range of mixtures, mean absolute deviations between the determined and the actual milk fat content were below 0.5% and the maximum absolute deviation was not more than 1.0% when using the reference sample.
The overall mean absolute deviation was 0.04% for milk fat contents of 1 to 10% and 0.28% for milk fat contents of 10 to 90%.
The objective is to minimize the total absolute deviation of job completion times about the common due date.
The objective is the minimization of the mean weighted absolute deviation of job completion times from due dates.
This paper, based on the basic analysis of drawbacks of Markowitz's portfolio model and portfolio models on the absolute deviation risk measure and E-Sh risk measure, develops a portfolio optimization model based on the new risk measure. The paper also provides methods for determing the optimal portfolio investment weights and portfolio efficient frontier. In addition, the paper presents comparative analysis about these models, and illustrates the effectiveness of our model with a practical example.
The paper raises a mean—absolute deviation porfolio optimal selection model on account of the historical return data. The model uses mean absolute deviation of return as measure of the risk and gains a optimal portfolio by solving the linear programming. If the securitys returns are multivariate normally distributed, its solution is similar to the one of mean—variance models and the computative complication of solving the quadratic programming problom of mean—variance model is avoided. Finally, this paper also...
The paper raises a mean—absolute deviation porfolio optimal selection model on account of the historical return data. The model uses mean absolute deviation of return as measure of the risk and gains a optimal portfolio by solving the linear programming. If the securitys returns are multivariate normally distributed, its solution is similar to the one of mean—variance models and the computative complication of solving the quadratic programming problom of mean—variance model is avoided. Finally, this paper also raises a portfolio optimal selection model in condition of the trode cost exists.
We propose a new risk measure, which is called Semi-Deviation. This new measure is superior to the exist measures,such as semi-variance and absolute-deviation etc,because it only focuses on the risk that less than the expected return,and using this measure doesn't need to consider whether the variance of asset retuens is existent. Based on this new measure, we also setup the portfolio optimization model which integrates the advantage of downside risk of semi-variance and the existence of first rank moment. In...
We propose a new risk measure, which is called Semi-Deviation. This new measure is superior to the exist measures,such as semi-variance and absolute-deviation etc,because it only focuses on the risk that less than the expected return,and using this measure doesn't need to consider whether the variance of asset retuens is existent. Based on this new measure, we also setup the portfolio optimization model which integrates the advantage of downside risk of semi-variance and the existence of first rank moment. In the empirical study,we apply the new model to Shanghai stock market,and compare the new model with the semi-variance model and the absolute-deviation model in quantitative and qualitative way. It can be drawn from comparison with the other two portfolio models that the semi-deviation portfolio model is better and practical.