• فهرست مقالات Negative data

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        1 - محاسبه‌ی بازه‌ی کارایی واحدهای تصمیم‌گیرنده دارای ورودی و خروجی‌های بازه‌ای با حضور داده‌های منفی
        محسن رستمی مال خلیفه فاطمه سادات سیداسماعیلی
        فرض اساسی در الگوهای تحلیل پوششی داده‌ها (مثل مدل‌های CCR و BCC)، این است که مقدار داده­های مربوط به ورودی­ها و خروجی­ها عددی دقیق و مثبتی می­باشد، ولی بسیاری از اوقات در شرایط واقعی کسب و کار، تعیین مقدار عددی دقیق برای برخی ورودی‌ها و یا خروجی‌ها امکان چکیده کامل
        فرض اساسی در الگوهای تحلیل پوششی داده‌ها (مثل مدل‌های CCR و BCC)، این است که مقدار داده­های مربوط به ورودی­ها و خروجی­ها عددی دقیق و مثبتی می­باشد، ولی بسیاری از اوقات در شرایط واقعی کسب و کار، تعیین مقدار عددی دقیق برای برخی ورودی‌ها و یا خروجی‌ها امکان پذیر نیست. به همین منظور در سال­های اخیر در تحلیل پوششی داده‌ها مدل­های متفاوتی برای داده­های غیر دقیق مطرح شد و همچنین پژوهش­های زیادی در زمینه DEA انجام شده است که قادر به ارزیابی کارایی با داده­های منفی می­باشد، الگوی تحلیل پوششی داده-های بازه­ای منفی که در این تحقیق معرفی و مورد استفاده قرار گرفته است عدم قطعیت را هم در ورودی­ها و هم در خروجی­ها مورد توجه قرار می­دهد و نتایج پایدارتر و قابل اطمینان­تری را برای تصمیم­گیری در اختیار کاربر قرار می­دهد. حال در این مقاله مدلی ارائه می­دهیم که قادر است بازه کارایی واحدها با ورودی و خروجی بازه­ای که بعضی از شاخص­ها می­توانند منفی هم باشند را محاسبه می­کند و در ادامه ثابت می­کنیم بازه کارایی که این مدل به ما می­دهد نسبت به بازه کارایی مدل­های قبلی ارائه شده، دقیق­تر است و در نهایت نیز ده واحد تصمیم­گیری با داده­های غیر دقیق (بازه­ای) منفی با مدل پیشنهادی مورد بررسی قرار می­گیرند و نتایج مدل پیشنهادی با نتایج مدل­های قبلی مورد مقایسه قرار می­گیرد. پرونده مقاله
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        2 - روشی سه مرحله ای برای بهینه سازی سبد سهام با استفاده از سنجه ریسک ارزش در معرض خطر شرطی
        سارا نویدی شکوفه بنی‌هاشمی مسعود صانعی
        برای بهینه­سازی سبد سهام باید از روش­های جامعی استفاده کرد. برای این منظور باید به صورت­های مالی شرکت­ها، متغیرهای ورودی و خروجی، سنجه ریسک مورد استفاده، تمایلات سرمایه­گذار و درجه ریسک­پذیری سرمایه­گذار توجه کرد. در این مقاله ما با در نظر گر چکیده کامل
        برای بهینه­سازی سبد سهام باید از روش­های جامعی استفاده کرد. برای این منظور باید به صورت­های مالی شرکت­ها، متغیرهای ورودی و خروجی، سنجه ریسک مورد استفاده، تمایلات سرمایه­گذار و درجه ریسک­پذیری سرمایه­گذار توجه کرد. در این مقاله ما با در نظر گرفتن این نکات روشی برای بهینه­سازی سبد سهام ارائه می­دهیم. در این راستا، از صورت­های مالی شرکت­های سهامی برای غربال کردن شرکت­ها استفاده می­کنیم. با توجه به برتری سنجه ریسک ارزش در معرض خطر شرطی، از این سنجه ریسک برای بهینه­سازی سبد سهام، استفاده می­کنیم. برای اینکه بتوانیم کارایی شرکت­ها را بدست آوریم، باید از تحلیل پوششی داده­ها استفاده کنیم. اکثر مدل­های تحلیل پوششی داده­ها فقط داده­های مثبت را می­پذیرند، در حالی که اکثر داده­ها (مخصوصاً در بحث مالی) منفی هستند. بنابراین ما مدل­های میانگین شارپ - بتا ارزش در معرض خطر شرطی و میانگین شارپ - بتا ارزش در معرض خطر شرطی چند هدفه را براساس مدل اندازه جهت مبنایی ارائه می­دهیم. این مدل­ها هم داده­های مثبت و هم داده­های منفی را می­پذیرند. با استفاد از مدل تصمیم­گیری چند هدفه به سرمایه­گذاران اختیار می­دهیم آنگونه که ترجیح می­دهند سرمایه­شان را به سهام شرکت­های موجود در سبد اختصاص دهند. در آخر روش ارائه شده را مرحله به مرحله روی بازار بورس ایران اجرا می­کنیم. پرونده مقاله
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        3 - Portfolio Performance Evaluation in a Modified Mean-Variance-Skewness Framework with Negative Data
        Sh. Banihashemi M. Sanei M. Azizi
        The present study is an attempt toward evaluating the performance of portfolios using mean-variance-skewness model with negative data. Mean-variance non-linear framework and mean-variance-skewness non- linear framework had been proposed based on Data Envelopment Analysi چکیده کامل
        The present study is an attempt toward evaluating the performance of portfolios using mean-variance-skewness model with negative data. Mean-variance non-linear framework and mean-variance-skewness non- linear framework had been proposed based on Data Envelopment Analysis, which the variance of the assets had been used as an input to the DEA and expected return and skewness were the output. Conventional DEA models assume non-negative values for inputs and outputs. However, we know that unlike return and skewness, variance is the only variable in the model that takes non-negative values. This paper focuses on the evaluation process of the portfolios in a mean-variance-skewness model with negative data. The problem consists of choosing an optimal set of assets in order to minimize the risk and maximize return and positive skewness. This method is illustrated by application in Iranian stock companies and extremely efficiencies are obtained via mean-variance-skewness non-linear framework with negative data for making the best portfolio. The finding could be used for constructing the best portfolio in stock companies, in various finance organization and public and private sector companies. پرونده مقاله
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        4 - Effect of Relocation and Rotation on Radial Efficiency Scores for a Partially Negative Data Problem
        S .Sarkar
        Negative data handling has gained a remarkable importance in the literature of Data Envelopment Analysis (DEA) to address many real life problems. Various erstwhile applications, in this arena, referred relocation of the origin to a superior (RDM) or to an inferior (Tra چکیده کامل
        Negative data handling has gained a remarkable importance in the literature of Data Envelopment Analysis (DEA) to address many real life problems. Various erstwhile applications, in this arena, referred relocation of the origin to a superior (RDM) or to an inferior (Translated Input Oriented BCC) neighboring point. In this paper, the conditions for Rotation Invariance of various Data Envelopment Analysis models are discussed. Specifically, in presence of partially negative data, a rotation using the Cone Ratio model, beyond a threshold value of the oblique index does not alter the efficient frontier. So, a solution can be obtained without relocating the origin. In this context, two models, termed as Input Oriented BCC model with Relocated Origin (IOBCC-RO) and Input oriented BCC model with Rotated Axis (IOBCC-RA), are applied on a case of "the notional effluent processing system" (from Sharp et al (2006)) to observe their impact on the radial efficiency scores. پرونده مقاله
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        5 - Cross Efficiency Evaluation with Negative Data in Selecting the Best of Portfolio Using OWA Operator Weights
        Sh. Banihashemi M. Sanei
        The present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decisionmaking units (DMUs) in data envelopment analysis (DEA). Conventional چکیده کامل
        The present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decisionmaking units (DMUs) in data envelopment analysis (DEA). Conventional DEA models assume nonnegativevalues for inputs and outputs. However, we know that unlike return and skewness, varianceis the only variable in the model that takes non-negative values. This paper focuses on the evaluationprocess of the efficiencies in the cross-efficiency matrix with negative data and proposes the use ofordered weighted averaging (OWA) operator weights for cross-efficiency evaluation. The problemconsists of choosing an optimal set of assets in order to minimize the risk and maximize return. Thismethod is illustrated by application in Iranian stock companies and extremely weights are obtainedvia OWA operator in cross efficiency for making the best portfolio. The finding could be used forconstructing the best portfolio in stock companies, in various finance organization and public andprivate sector companies. پرونده مقاله
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        6 - Estimating Most Productive Scale Size with Double Frontiers in Data Envelopment Analysis using Negative Data
        F. Roozbeh R. Eslami M. Ahadzadeh Namin
        In this paper, it is assumed that the “Decision Making Units“( ) are consist of positive and negative input and output. Firstly, the optimistic and pessimistic models have been suggested by using negative data and then units with most productive scale size a چکیده کامل
        In this paper, it is assumed that the “Decision Making Units“( ) are consist of positive and negative input and output. Firstly, the optimistic and pessimistic models have been suggested by using negative data and then units with most productive scale size are measured in optimistic and pessimistic models. These productive values are compared with double frontiers and Hurwicz’s Criterion to obtain DMU with MPSS. پرونده مقاله
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        7 - The Effect of Meta-Malmquist Index on Portfolio Optimization
        Z. Taeb SH. Banihashemi
        Since the change of conditional value at risk (CVaR) in different confidence levels is very effective in portfolio optimization, the meta-Malmquist index (MMI) is utilized. For this purpose, mean-CVaR models by MMI in the presence of negative data are introduced. Like M چکیده کامل
        Since the change of conditional value at risk (CVaR) in different confidence levels is very effective in portfolio optimization, the meta-Malmquist index (MMI) is utilized. For this purpose, mean-CVaR models by MMI in the presence of negative data are introduced. Like Markowitz theory in mean-variance framework, we use Conditional Value-at-risk as a risk measure and propose our models without considering the skewness and kurtosis of assets return. In our study there are some negative data, so our models is based on Range Directional Measure (RDM) model that can be taken positive and negative data. In this paper efficiencies are obtained in all confidence levels by mean-CVaR models and MMI is calculated on confidence levels as periods in the presence of negative data. This method could help the investors to construct their profitable portfolio by using MMI index. We, also carry out an empirical study within Iran stock exchange market . پرونده مقاله
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        8 - Evaluating the Efficiency of Firms with Negative Data in Multi-Period Systems: An Application to Bank ‎Data
        S. Kordrostami‎‎ M. Jahani Sayyad ‎Noveiri
        Data Envelopment Analysis (DEA) is a mathematical technique to evaluate the performance of firms with multiple inputs and outputs. In conventional DEA models, the efficiency scores of Decision Making Units (DMUs) with non-negative inputs and outputs are evaluated in a s چکیده کامل
        Data Envelopment Analysis (DEA) is a mathematical technique to evaluate the performance of firms with multiple inputs and outputs. In conventional DEA models, the efficiency scores of Decision Making Units (DMUs) with non-negative inputs and outputs are evaluated in a special period of time. However, in the real world there are situations wherein performance of firms must be evaluated in multiple periods of time while negative data are present; for this matter the current paper proposes an approach for assessing the efficiency of multi-period systems in the presence of positive and negative measures. To illustrate, the average efficiency of firms with some negative measures are calculated in multi-period production systems. The suggested approach utilizes the Semi-Oriented Radial Measure (SORM) model (Emrouznejad et al. \cite{4}) for incorporating some negative factors (inputs and outputs) and determining the efficiency of multi-period production systems. A real world data set related to banking sector is used to illustrate and clarify the proposed approach. پرونده مقاله
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        9 - Estimation of portfolio efficient frontier by different measures of risk via ‎DEA
        M. Sanei S. ‎Banihashemi‎ M. ‎Kaveh‎
        In this paper, linear Data Envelopment Analysis models are used to estimate Markowitz efficient frontier. Conventional DEA models assume non-negative values for inputs and outputs. however, variance is the only variable in these models that takes non-negative values. Th چکیده کامل
        In this paper, linear Data Envelopment Analysis models are used to estimate Markowitz efficient frontier. Conventional DEA models assume non-negative values for inputs and outputs. however, variance is the only variable in these models that takes non-negative values. Therefore, negative data models which the risk of the assets had been used as an input and expected return was the output are utilized . At the beginning variance was considered as a risk measure. However, both theories and practices indicate that variance is not a good measure of risk. Then value at risk is introduced as new risk measure. In this paper,we should prove that with increasing sample size, the frontiers of the linear models with both variance and value at risk , as risk measure, gradually approximate the frontiers of the mean-variance and mean-value at risk models and non-linear model with negative data. Finally, we present a numerical example with variance and value at risk that obtained via historical simulation and variance-covariance method as risk measures to demonstrate the usefulness and effectiveness of our ‎claim.‎ پرونده مقاله
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        10 - Using MODEA and MODM with Different Risk Measures for Portfolio Optimization
        Sarah Navidi Mohsen Rostamy-Malkhalifeh Shokoofeh Banihashemi
        The purpose of this study is to develop portfolio optimization and assets allocation using our proposed models. The study is based on a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Conventional DEA models assume non-negative data for چکیده کامل
        The purpose of this study is to develop portfolio optimization and assets allocation using our proposed models. The study is based on a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Conventional DEA models assume non-negative data for inputs and outputs. However, many of these data take the negative value, therefore we propose the MeanSharp-βRisk (MShβR) model and the Multi-Objective MeanSharp-βRisk (MOMShβR) model base on Range Directional Measure (RDM) that can take positive and negative values. We utilize different risk measures in these models consist of variance, semivariance, Value at Risk (VaR) and Conditional Value at Risk (CVaR) to find the best one as input. After using our proposed models, the efficient stock companies will be selected for making the portfolio. Then, by using Multi-Objective Decision Making (MODM) model we specified the capital allocation to the stock companies that selected for the portfolio. Finally, a numerical example of the Iranian stock companies is presented to demonstrate the usefulness and effectiveness of our models, and compare different risk measures together in our models and allocate assets. پرونده مقاله
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        11 - Efficiency Evaluation in Presence of Undesirable and Negative Factors
        مهناز مقبولی مهدی عینی فرهاد طاهر
        Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA models, it is assumed that the input or output variables ar چکیده کامل
        Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA models, it is assumed that the input or output variables are all non-negative and desirable. However, in some situations, a performance measure can take positive quantity for some DMUs and negative value for others. Also, undesirable (bad) inputs and outputs may be presented in the production process. Hence, the standard model cannot directly reflect the efficiency score. The paper proposes a modified model in which both undesirable and negative data are treated to improve the relative efficiency of the DMU under evaluation. The focus of this paper is on treating the negative data on the definition of the two non-negative variable and the decreasing of undesirable outputs. A real example of 20 bank branches shows applicability of the proposed approach پرونده مقاله
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        12 - A Bounded Additive Model for Efficiency Evaluation in Two-Stage Production Systems With Negative Data
        حمیدرضا بابائی اصیل رضا کاظمی متین محسن خون سیاوش زهره مقدس
        Data Envelopment Analysis (DEA) is a method for assessing the efficiency of Decision Making Units (DMUs). Traditional DEA models do not examine the potential differences between two stages caused by intermediate operations. As a result, DEA has been extended to evaluate چکیده کامل
        Data Envelopment Analysis (DEA) is a method for assessing the efficiency of Decision Making Units (DMUs). Traditional DEA models do not examine the potential differences between two stages caused by intermediate operations. As a result, DEA has been extended to evaluate the efficiency of two-stage processes. In these processes, all outputs of the first stage are intermediate operations that comprise the inputs of the second stage. The input data in real-world applications may have negative values. In this study, considering the importance of network production processes, we deal with the efficiency evaluation of two-stage production units with negative data. Also, we extend CRS (constant returns to scale) bounded additive model for the efficiency evaluation of the two-stage units in the presence of negative data. For illustration, we evaluate the efficiency and ranking of 36 airlines by applying the new model. پرونده مقاله
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        13 - Upgrading inefficient decision making units (with negative data) towards common weights (using DEA)
        حسین عباسیان
        The main purpose of this paper is to upgrade and improve inefficient units by common weights obtained from all units studied. In fact, we consider the common weight vector as the direction in which inefficient units rise. The methodology of this research is to consider چکیده کامل
        The main purpose of this paper is to upgrade and improve inefficient units by common weights obtained from all units studied. In fact, we consider the common weight vector as the direction in which inefficient units rise. The methodology of this research is to consider the semi-essential radial model and we want to use the duality of this model to find the common weights of inputs and outputs, some of which are negative. For this purpose, we present a multi-objective problem of generating common weights and use ideal programming to solve it, which leads to the production of a nonlinear problem, which for this particular problem, by a linearization method, is called We turn a linear programming problem. Since the necessary and sufficient condition for the boundary of the semi-essential radial model in the nature of input (output) is that there is an input (output) with at least one positive value, so we observe this condition here. Finally, we will explain our method with an example and the remarkable thing about the promotion method in the present study is that negative data is promoted and improved as negative data. پرونده مقاله
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        14 - Efficiency Evaluation of Economic Enterprise in Presence of Interval Undesirable and Negative Data
        MAHNAZ MAGHBOULI مهدی عینی فرهاد طاهر FATEMEH GHOMANJANI
        Data envelopment analysis (DEA) as a non-parametric method has covered a wide range of applications in measuring comparative efficiency of decision making units (DMUs) with multiple incommensurate inputs and outputs. The standard DEA method requires that all input and o چکیده کامل
        Data envelopment analysis (DEA) as a non-parametric method has covered a wide range of applications in measuring comparative efficiency of decision making units (DMUs) with multiple incommensurate inputs and outputs. The standard DEA method requires that all input and output variables be known as semi positive. In many real situations, the presence of undesirable and even negative data are inevitable. In DEA literature there have been various approaches to enable DEA to deal with negative data. On the other hand, the structure of interval data has recently attracted considerable attention among DEA researchers. According to importance of interval data, this paper proposes a radial measure which permits the presence of undesirable and negative data with interval structure. The proposed model can evaluate the efficiency of all DMUs and leads to improve the inefficient unit with interval negative and undesirable data. To elucidate the details of the proposed method an illustrative example of a private bank in IRAN explores the applicability of the proposed method. پرونده مقاله
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        15 - Allocation models for DMUs with negative data
        Ghasem Tohidi Maryam Khodadadi
        The formulas of cost and allocative efficiencies of decision making units (DMUs) with positive data cannot be used for DMUs with negative data. On the other hand, these formulas are needed to analyze the productivity and performance of DMUs with negative data. To this چکیده کامل
        The formulas of cost and allocative efficiencies of decision making units (DMUs) with positive data cannot be used for DMUs with negative data. On the other hand, these formulas are needed to analyze the productivity and performance of DMUs with negative data. To this end, this study introduces the cost and allocative efficiencies of DMUs with negative data and demonstrates that the introduced cost efficiency is equal to the product of allocative and range directional measure efficiencies. The study then intends to extend the definition of the above efficiencies to DMUs with negative data and different unit costs. Finally, two numerical examples are given to illustrate the proposed methods. JEL classification: C6, D2 پرونده مقاله
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        16 - سنجش عملکرد مالی 50 شرکت برتر بورس اوراق بهادار با استفاده از مدل های غیر شعاعی تحلیل پوششی داده ها
        سعید رضائی لوا میر فیض فلاح مسعود صانعی شکوفه بنی هاشمی
        هدف از این تحقیق انتخاب بهینه سبد سهام با استفاده از تحلیل پوششی داده ها است و جهت انجام پروژه از اطلاعات بورس اوراق بهادار درباره ۵۰ شرکت فعال برتر در بازه زمانی تابستان سال 1398 و ردیابی تحلیل همین داده ها در بازه زمانی بهار سال 1398 می باشد. برای محاسبه کارایی نسبی و چکیده کامل
        هدف از این تحقیق انتخاب بهینه سبد سهام با استفاده از تحلیل پوششی داده ها است و جهت انجام پروژه از اطلاعات بورس اوراق بهادار درباره ۵۰ شرکت فعال برتر در بازه زمانی تابستان سال 1398 و ردیابی تحلیل همین داده ها در بازه زمانی بهار سال 1398 می باشد. برای محاسبه کارایی نسبی و میزان پیشرفت و پسرفت شرکت ها از مدل توسعه یافته تحلیل پوششی داده ها‌ ( SORM ) استفاده گردیده که ورودی ها فقط در فاصله ای محدود و مشخص شده می توانند تغییر نمایند و با همین فرض، خروجی نیز در فاصله ای محدود شده تغییر می نماید و امکان وجود داده منفی هم قابلیت تحلیل دارد و مدل نهایی با توجه به اطلاعات استخراج شده از جامعه مورد بحث، کارایی و بهینگی انتخاب سبد سهام را تسهیل می نماید. به دلیل عدم وجود تمام اطلاعات مورد نیاز و در دسترس، نتایج این تحلیل نشان می دهد 13 شرکت، کارایی برابر 1 که نشانگر بیشترین سطح کارایی است دست یافته و بانک صادرات با احتساب رقم 1.32 و شرکت پتروشیمی فناوران نیز به احتساب رقم 1.15 به ترتیب دارای بیشترین پیشرفت و نرخ رشد در طبقه اول و دوم بهره وری طبقه بندی گردیده اند. پرونده مقاله
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        17 - A generalized cost Malmquist index to compare the productivities of units with negative data in DEA
        G. Tohidi S. Razavyan S. Tohidnia
        In some data envelopment analysis (DEA) applications, some inputs of DMUshave negative values with positive cost. This paper generalizes the global cost Malmquistproductivity index to compare the productivity of di erent DMUs with negative inputs inany two periods of ti چکیده کامل
        In some data envelopment analysis (DEA) applications, some inputs of DMUshave negative values with positive cost. This paper generalizes the global cost Malmquistproductivity index to compare the productivity of di erent DMUs with negative inputs inany two periods of times under variable returns to scale (VRS) technology, and then thegeneralized index is decomposed to several components. The obtained components are computed using the nonparametric linear programming models, known as DEA. To illustrate thegeneralized index and its components, a numerical example at three successive periods oftime is given. پرونده مقاله