Fatemeh Fattahi; Farhad Hosseinzadeh Lotfi; Andrew C. Worthington
Abstract
Data envelopment analysis (DEA) is a methodology widely used for evaluating the relative performance of portfolios under a mean–variance framework. However, there has been little discussion of whether nonlinear models best suit this purpose. Moreover, when ...
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Data envelopment analysis (DEA) is a methodology widely used for evaluating the relative performance of portfolios under a mean–variance framework. However, there has been little discussion of whether nonlinear models best suit this purpose. Moreover, when using DEA linear models, the portfolio efficiency obtained is not comparable to those on the efficient portfolio frontier. This is because a separable piecewise linear boundary usually below the efficient frontier is considered the efficient frontier, so the model does not fully explore the possibility of portfolio benchmarks. In this paper, and with use of the dual-Lagrangian function, we propose a linear model under a mean–variance framework to evaluate better the performance of portfolios relative to those on the efficient frontier.
Hadi Bagherzadeh Valami; Zeinab Sinaei nasab
Abstract
In the process of evaluating the Decision Making Units, two factors of efficiency and production size can be used. When the production size of a unit is not optimal, its Returns To Scale (RTS) determines that changing the resources in anotherdirection would enhance its productivity. In most previous ...
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In the process of evaluating the Decision Making Units, two factors of efficiency and production size can be used. When the production size of a unit is not optimal, its Returns To Scale (RTS) determines that changing the resources in anotherdirection would enhance its productivity. In most previous research, RTS is considered to be increasing or decreasing, and frontier analysis is used to determine it. The concept of RTS in Network Data Envelopment Analysis (DEA) is so interesting. In this paper a method based on Most Productive Scale Size (MPSS) in several steps is developed, in addition to determining that RTS of units for each unit in directional manner, the shortest changes in resources for achieving the right size for network production is also obtained. In this approach, the computational complexity, and the ambiguity in units RTS is not present.
Samaneh Mohammadi Jarchelou; Kianoush Fathi Vajargah; Parvin Azhdari
Abstract
Investment is the selection of assets to hold and earn more pro t for greater prosperity in the future. The selection of a portfolio based on the theory of constraint is classical data covering analysis evaluation and ranking Sample function. The in vestment process is related to how investors act in ...
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Investment is the selection of assets to hold and earn more pro t for greater prosperity in the future. The selection of a portfolio based on the theory of constraint is classical data covering analysis evaluation and ranking Sample function. The in vestment process is related to how investors act in deciding on the types of tradable securities to invest in and the amount and timing. Various methods have been proposed for the investment process, but the lack of rapid computational methods for determining investment policies in securities analysis makes performance appraisal a long term challenge. An approach to the investment process consists of two parts. Major is securities analysis and portfolio management. Securities analysis involvesestimating the bene ts of each investment, while portfolio management involves analyzing the composition of investments and managing and maintaining a set of investments. Classical data envelopment analysis (DEA) models are recognized as accurate for rating and measuring efficient sample performance. Unluckily, this perspective often brings us to get overwhelmed when it's time to start a project. When it comes to limiting theory, the problem of efficient sample selection using a DEA models to test the performance of the PE portfolio is a real discontinuous boundary and concave has not been successful since 2011. In order to solve this problem, we recommend a DEA method divided into business units based on the Markowitz model. A search algorithm is used to introduce to business units and prove their validity. In any business unit, the boundary is continuous and concave. Therefore, DEA models could be applied as PE evaluation. To this end, 25 companies from the companies listed on the Tehran Stock Exchange for the period 1394 to 1399 were selected as the sample size of statistics in data analysis. To analyzethe data, after classi cation and calculations were analysed by MATLAB software, the simulation results show that performance evaluation based on constraint theory based on DEA approach and the Markowitz model presented in this paper is efficient and feasible in evaluating the portfolio of constraint theory.
Hadi Bagherzadeh Valami
Abstract
In this paper, considering risks of a portfolio such as mean return, variance of returns, and moments of higher order as output variables including desirable and undesirable outputs, we introduce a non-radial and slack based score to measure efficiency of portfolios. Using the present measure, ranking ...
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In this paper, considering risks of a portfolio such as mean return, variance of returns, and moments of higher order as output variables including desirable and undesirable outputs, we introduce a non-radial and slack based score to measure efficiency of portfolios. Using the present measure, ranking of portfolios is provided which is consistent with standard risk-return ratios in finance. We provide illustrations to show the effects of this contribution on the measures of technical efficiency and ranking of portfolios on a sample set of daily prices of banks and credit institutions listed on the first stock market of Tehran Securities Exchange (TSE). The advantage of this paper is to present a model based on stock market returns and risk, which is based on the DEA view of the production possibility set. Of course, in making it, the quadratic property of variance and the origin of coordinates have been used as a moderating point.