۱.
کلید واژه ها:
Data Envelopment Analysis Interval data Sensitivity Analysis Sustainability radius Cost efficiency
Interval Data Envelopment Analysis (Interval DEA) is a methodology to assess the efficiency of decision-making units (DMUs) in the presence of interval data. Sensitivity analysis and sustainability evaluation of decision- making units are as the most important concerns of Decision Makers (DM). In the past decades, many scholars have been attracted to the sustainability evaluation of DMUs from different perspectives. This study focuses on the sensitivity analysis in DEA and proposes an approach to determine the sustainability radius of the cost efficiency of units with interval data. Potential application of our proposed methods is illustrated by a numerical example from the literature review.
۲.
کلید واژه ها:
Sustainability Supply Chain Management Multi-objective Optimization time and evironemntal based competeion
This paper presents an integrated mathematical model for cost – environmental based competition between sustainable supply chains (SCCs) with heterogeneous customers in four echelon supply with multi product. The main objective of this paper is to provide bi objective mathematical model for designing SSC network economic based competition and optimize by using meta-heuristic algorithms. Assuming the customers are heterogeneous in the above criteria i.e. cost and pol-lution decision making, we integrated mathematical model and formulated objectives and constraints based multi-echelon supply chain network. The main contribution of this research is to a discrete choice model is integrated into the supply chain network economic model and extends the inter supply chain competition to a new dimensions of cost and environmental. The model in this problem is solved using two metaheuristic algorithms NSGAII and MOPSP. Examples of real case study related to Emersan company is presented for model illustration and managerial insights such as profit maximization and minimize cost for Emersan company that participates in this supply chain network. Finally, NSGA-II performs better and has shorter time in terms of computational time, but MOPSO algorithm is more efficient in MID, SM, QM and DM indices. In comparison of these two algorithms, the performance of MOPSO algorithm is generally better than NSGAII by in indices.
۳.
کلید واژه ها:
Stock Price Delay Information Transparency CEO power
News and information reflect on the stock prices rapidly in the capital market. But some factors cause delays in reaching the stock market to its intrinsic value. This study aims to investigate the effect of CEO Power on stock price delay of listed Companies in Tehran Stock Exchange. In order to measure the power of the CEO, six different criteria, based on the research of Lisic et al. have been used. For this purpose, data related to 107 companies in Tehran Stock Exchange from 2011 to 2018 were analyzed. The regression model used in this research has been assessed using panel data with fixed effects approach. The results showed that CEO power has a negative and significant impact on stock price delay. The results also indicate that the powerful executives have more independence and play a more supervisory role over the board of directors; This reduces the infringement of the stakeholder rights and lowers the agency costs. Lower agency costs result in less information asymmetry and lower financial information transparency, and ultimately, reduces the stock price delay.
۴.
کلید واژه ها:
Future Cash Flows Neural Network Model Accruals
Cash flow and profit are two important indicators for measuring the performance of a business unit. The future prediction was always a necessity in everyday life, and one of the subjects in which “The Prediction” has a great importance is economical and financial problems. The purpose of the present study is to predict future cash flows using regression and neural network models. Sub – separated variables of the accruals and operational cash flows were used to investigate this prediction. For this purpose, data of 137 accepted stock exchange companies in Tehran during 2009 to 2017 has been studied. In this study, Eviews9 software for regression model and Matlab13 software for Multi-Layer Artificial Neural Networks (MANN) with Error back propagation algorithm were used to test the hypotheses.The findings of the research show that both regression and neural network models within proposed variables in the present study have the capability of predicting future cash flows. Also, results of neural network models' processes show that a structure with 16 hidden neurons is the best model to predict future cash flows and this proposal neural network model compared with regression model in predicting future cash flows has a better and accurate function. Furthermore, in this study, it was noticed that accruals of assets compared with debt accrual and variables of operating cash flows with accrual components were more predictive for future cash flows.
۵.
کلید واژه ها:
Taxes tax gap Effective Corporate Governance Future Profit Changes
In most countries, taxation plays a very important role as one of the main means of government in the economy. Most of the state's revenue sources are taxed, through which redistribution for the three purposes of allocating economic benefits. Income and economic stability are used. Due to differences in tax laws and regulations and accepted accounting principles and principles, what may be considered from the perspective of income and expense accounting theories may not necessarily be from the perspective of income and expense tax laws. It should be noted, however, that the purpose of determining profits in the preparation of financial statements from an accounting perspective is to Determining the source of tax calculation is different in tax laws (Karbassi Yazdi and Rasekh Saleh, 2013). It accounts for a large share of Iran's GDP, so addressing it can play an important role in achieving the ultimate goals of macro policies (Khajavi et al., 2010). With the formation of agency relations, the conflict of interest between Managers, shareholders on the one hand, and other stakeholders (such as the government) on the other. Yat is not the same as determinate tax (tax gap). Two goals are conceivable. While this gap is expected to affect the quality of reported earnings for investors, the greater the difference, the lower the firm's profitability. And affect future profits of companies.
۶.
کلید واژه ها:
Corporate Governance Banking Failure Logestic model
We analyse the roles of bank Directors’ Effectiveness, Transparency and the Dis-closure, Responsibility and total corporate governance indicator in bank failures during 2006-2019, using Logistic model and Kaplan-Meier method. This study completes other studies to make composite banking failure indicator. Good corpo-rate governance indicator was made. That it is one if corporate governance indica-tors for each bank are more than mean of sample and otherwise, it is zero. Forth we estimate the survival model according corporate governance indicators. Our results suggest that failures are strongly influenced by Corporate governance indicators. High Directors’ Effectiveness, Responsibility and total corporate governance indicator decrease failure risk significantly. In contrast Transparency and the Disclosure increase failure risk. These findings suggest that banks with more transparency are less survival than others. In contrast Responsibility has most effect on survival banks. There are positive relationship between bank size, inflation and banking failure and negative relationship between economic growth and banking failure indicator.
۷.
کلید واژه ها:
Data Envelopment Analysis Industry cost efficiency Interval data
In this paper we extend the concept of "cost minimizing industry structure" and develop two DEA models for dealing with imprecise data. The main aim of this study is to propose an approach to compute the industry cost efficiency measure in the presence of interval data. We will see that the value obtained by the proposed approach is an interval value. The lower bound and upper bound of the interval industry cost efficiency measure are computed and then decomposed into three components to examine the relationship between them and the lower and upper bounds of the individual interval cost efficiency measures. We also define the cost efficient organization of the industry as a set of DMUs, which minimizes the total cost of producing the interval industry output vector. In fact, this paper determines the optimal number of DMUs and the reallocation of the industry observed outputs among them. We hereby determine the effects of the optimal number of DMUs and the reallocation of outputs among them on the interval industry cost efficiency measure. Finally, a numerical example will be presented to illustrate the proposed approach.
۸.
کلید واژه ها:
KKM mapping Set-valued mapping Finite intersection property Upper semicontinuous mapping Generalized Nash equilibrium problem
In this paper, first a brief history of equilibrium problems(EP) and generalized implicit vector equilibrium problems(GIVEP) are given. Then some existence theorems for GIVEP are presented, also some suitable conditions in order the solution set of GIVEP is compact and convex for set-valued mappings whose are a subset of the cartesian product of Hausdorff topological vector space and their range is a subset of a topological space values (not necessarily locally convex or a topological vector space). In almost all of published results for GIVEP the set-valued mappings are considered from a topological vector space(locally convex topological vector space) to a topological vector space while in this paper the range of the set-valued mappings are a subsets of a topological spaces. As applications of our results, we derive some suitable conditions for existing a normalized Nash equilibrium problems when the number of players are finite and the abstract case, that is infinite players. Finally, a numerical result, as an application of the main results, is given. The method used for proving the existence theorems is based on finite intersection theorems and Ky-Fan’s theorem. The results of this paper, can be considered as suitable generalizations of the published paper in this area.
۹.
کلید واژه ها:
smoothing Support vector machine multi-output least-squares vector regression interval forecasting
Given the importance of investment in stock markets as a major source of income for many investors, there is a strong demand for models that estimate the future behavior of stock prices. Interval forecasting is the process of predicting an interval characterized by two random variables acting as its upper and lower bounds. In this study, a hybrid method consisting of Holt’s exponential smoothing and multi-output least squares support vector regression is used to forecast the interval of the lowest and highest prices in a stock market. First, Holt’s smoothing method is used to smooth the two bounds of the interval and then the residuals of the smoothing process are modeled with multi-output vector support regression. The output of the regression step is the error of the two bounds of the interval. The method is implemented on the weekly data of the overall index of the Tehran Stock Exchange from 1992 to 2016, with the interval defined as the distance between the lowest and highest overall index values. The results demonstrate the high accuracy of the hybrid method in producing in-sample and out-of-sample forecasts for the movement of the two bounds of the interval, that is, the weekly highs and lows of the overall index. Also, the hybrid method has achieved a lower mean squared error than the Holt’s smoothing method, indicating that multi-output vector support regression has improved the performance of the smoothing method
۱۰.
کلید واژه ها:
volume of exchanges transaction value bubble price GARCH Copula
Given the importance of the securities market in each country's economy and the adverse effects of the price bubble on the irrational fluctuations of the stock market, it is clear that it must be prevented; therefore, with reference to the ambiguity of the factors causing the price bubble, research is underway. Investigating the relationship between the volume of transactions and the value of transactions with the price bubble in different industries of the Stock Exchange during the years 2006 to 2016 is a step towards recognizing this phenomenon.To investigate these communications, we used DCC-GJR-GARCH, diagonal BEKK and COPULA models. The results of the study of the relationship between the volume of exchanges and the value of exchanges with price bubbles suggest that there is a negative and complete correlation between them. In relation to the study of the relationship between price bubbles and research variables, we found that oil prices have a reverse and significant relationship with bubble prices. Other variables are not meaningful relationships with price bubbles. Also, in the study between variables of research with volume of transactions, it was determined that changes in tax volume and oil price variables have a reverse and significant relationship with the volume of transactions and the value of transactions with the volume of transactions has a direct and significant relationship.
۱۱.
کلید واژه ها:
Genetic Programming Supervised Learning Classification Insurance Claim
In this study we provide insurance companies with a tool to classify the risk level and predict the possibility of future claims. The support vector machine (SVM) and genetic programming (GP) are two approaches used for the analysis. Basically, in Iran insurance industry there is no systematic strategy to evaluate the car body insurance policy. Companies refer mainly to the world experience and employ it to rate the premium. An insurance claim dataset provided by an Iranian insurance company with a sample size of 37904 is considered for programming and analysis. According to the structure of the dataset, a supervised learning algorithm was used to describe the underlying relationships between variables.
۱۲.
کلید واژه ها:
Prediction of Stock Returns Metaheuristic Models Neural Network Regression
Investment in the stock market requires decision-making and access to infor-mation on the future of the stock market. Given the importance of predicting stock returns, the present study aimed to discover the variables and indices that could predict stock returns. The prediction of stock returns has long been a 'hot topic' in advanced countries. While effective steps have been taken in this regard, the accu-rate prediction of stock returns remains a problem due to numerous issues. In this study, an accurate, applicable, and effective model was proposed for the predic-tion of stock returns. The statistical sample included 138 active companies of Tehran Stock Exchange (TSE) during 2008-2017, which were selected by the systematic removal method. In total, 1,380 data years were selected for the re-search to evaluate the questions. Data analysis was performed using an adaptive neuro-fuzzy inference system (ANFIS), multi-gene genetic programming, and regression analysis. In addition, statistical tests were applied to evaluate the accu-racy of the model, implemented by MATLAB and GeneXproTools. According to the results, the hybrid metaheuristic method had a lower error rate compared to artificial neural network and regression analysis in terms of stock return predic-tion. Therefore, the proposed model could provide more accurate data within a shorter time to predict the stock market status since it makes predictions after selecting the most optimal input variables through ANFIS.
۱۳.
کلید واژه ها:
Risk measurement Generalized Co-Lower Partial Moment Portfolio optimization Nonparametric estimation Stock Market
Any investor in stock markets around the world has a deep concern about the shortfalls of allocation wealth to any stock without accurate estimation of related risks. As we review the literature of risk management methods, one of the main pillars for the risk management framework in defining risk measurement approach using historical data is the estimation of the probability distribution function. In this paper, we propose a new measure by using kernel density estimation via diffusion as a nonparametric approach in probability distribution estimation to enhance the accuracy of estimation and consider some distribution characteristics, investor risk aversion and target return which will make it more accurate, compre-hensive and consistent with stock historical performance and investor concerns.
۱۴.
کلید واژه ها:
Golden Sine Algorithm Meta-heuristics Optimization Algorithms Parameter Tuning Support vector regression Time Series Prediction
Stock price prediction is one of the most important concerns of stockholders. This prediction, independent of the method which is used or the assumptions which are applied, is welcomed and trusted if it can guarantee a high fitting. So due to the high performance prediction, using some complicated models as Machine Learning family such as Support Vector Regression (SVR) was recommended instead of older and lower performance approaches such as multiple discriminant technique. SVR model have achieved high performance on forecasting problems, however, its performance is highly dependent on the appropriate selection of SVR parameters. In this study, a novel GSA-SVR model based on Golden Sine Algorithm is presented. The performance of the proposed model is compared with eleven other meta-heuristic algorithms on some stocks from NASDAQ. The results indicate that the given model here is capable of optimizing the SVR parameters very well and indeed is one of the best models judged by both prediction performance accuracy and time consumption.
۱۵.
کلید واژه ها:
Financial Reporting Transparency Financial Health Tehran Stock Exchange
This study aimed to evaluate the effect of industry type on the relationship between financial reporting transparency and financial health in companies listed in Tehran Stock Exchange. The statistical population included companies listed in Tehran Stock Exchange during 2005 to 2016. By systematic elimination, 79 companies from 5 industries were selected as statistical sample and were tested by composite regression of hypotheses. Results of significant coefficients test based on fitted regression equations indicated a significant positive relationship between financial reporting transparency and financial health. The moderating relationship of industry type was also confirmed on the relationship between financial reporting transparency and financial health. Hence, business continuity and profitability (financial health) will be greater by investing in companies that have greater financial reporting transparency. Thus, the relationship between financial reporting transparency and financial health is high in industries of automobile, auto part, basic metals, chemicals, cement, lime and plaster, and pharmaceuticals, respectively.
۱۶.
کلید واژه ها:
Financial Distress Worst-Practice-Frontier DEA Improvement Solutions Securities and Exchange Organization
One of the main concerns of financial institutions for investing in companies is to evaluate financial performance and, most importantly, the financial distress of organizations applying for investment. Therefore, various approaches and tech-niques are used in this evaluation. Financial decision-making has always been associated with the risk of uncertainty. One way to help investors is to provide forecasting models for the overall corporate prospect. It is noteworthy that in all these approaches, various criteria are used to identify corporate financial distress. In this study, a dynamic worst-practice-frontier DEA model was used to identify financially distressed decision-making units over several time-periods. Another feature of the model presented in this study was to provide some improvement solutions for financially distressed decision-making units. Finally, a new ranking approach was introduced to evaluate companies based on the inefficiency trend over several time-periods. The study's approach provides decision-makers with the ability to evaluate the inefficient DMUs during each time-period according to the relationships between these time-periods. The efficiency slope can also be evaluated over time-periods, and companies can be ranked based on this slope. Finally, it is suggested to use this model to dynamically predict financial distress in various industries, including metals, rubber, automobiles, etc., so that compa-nies are informed of their financial distress promptly and take appropriate measures to prevent bankruptcy.
