FINANCIAL RESEARCH
Year:2016 | Volume:17 | Issue:2 |Papers Count:13

The significance of financial performance of companies makes factors affecting it significant. As a mixed-method research, this paper aimed at investigating the effect of human resources composition in of an organization and the management stability on the financial performance of the organization. First, based on the Grounded Theory, the indices of human resources composition were identified. Then, with a quantitative approach, using Smart PLS software, the relationship between human resources composition and management stability, and financial performance (ROA &ROE) was investigated. The indirect impact of human resources composition on financial performance through its influence on management stability was tested as well. Findings proved that there was a positive correlation between human resources composition and the management stability, and financial performance in 274 companies registered to the Tehran stock exchange market between 2010 and 2013, but there is no significant relationship between X and Y. Finally, based on the findings, a model for improving the financial performance of companies with an emphasis on human resources composition and management stability is introduced.

There is always a considerable difference between the corporate performance and the tax levy that is identified by the taxation authorities which has become a common practice. This fact has led to no fairness among taxpayers, a fact that influences the horizontal and vertical sides of equity. Horizontal equity is created when people feel the benefits of the tax gain that is proportional to the loss of benefits. People with more financial means should also pay more taxes that is equivalent to vertical equity. One reason for the difficulty of attaining the horizontal and vertical equities is to identify the taxpayers based on their previous taxation behavior and to deal with them effectively. The aim of this study is the design of a predictive system that evaluates the corporates taxation behavior based on their previous payments. The predicting system uses key performance variables that are identified during research and it will also help in the classification of companies based on their taxation behavior into three groups of high risk, medium risk and low risk. The system is specifically designed for the taxation authorities who are attempting to effectively assessing the risk of corporate taxes gaining. In this study, the taxation clusters of customers are identified and a decision tree is designed with 80% of accuracy by the utilization of clustering and classification algorithms and effective validation methods. The resulting models of applied algorithms investigate the taxation behavior of each customer and are capable of predicting the tax payment risk of taxpayers in the future with the addition of new corporates to the list.

This paper investigates the forecasting gold coin futures contract price in Iran Mercantile Exchange. this research has presented a hybrid model based on genetic fuzzy systems (GFS) and artificial neural network (ANN) to forecast the gold futures contract, At first, we use stepwise regression analysis (SRA) to determine factors which have most influence on stock prices. At the next stage we divide our raw data into k clusters by means of self-organizing map (SOM) neural networks. Finally, all clusters will be fed into independent GFS models. Finally, the results from the proposed hybrid model was compared with the results from forecasting ARIMA model using mean absolute percentage error (MAPE). Results show that the proposed approach outperforms of ARIMA model, so it can be considered as a suitable tool for forecasting price Gold coin futures contracts problems.

This paper seeks two goals concurrently, at one hand tries to assay the capability of TOPSIS, VIKOR and Similarity-Based Approach as multiple attribute decision making approaches in evaluating mutual funds in Iran Stock Exchange, and at the other hand in this evaluation tries to consider and compare three groups of indices including general evaluating indices (age, net value of mutual fund’s assets, cash assets percentage and net asset value), risk-adjusted evaluation indices(Sharpe, Treynor and Jensen) and risk-adjusted evaluation indices using semivariance (modified Sharpe, modified Treynor and modified Jensen with downside Beta) in a distinctly manner and together in order to assay the capability of mentioned methods with these different indices. At the end the result of this comparison is represented and the decisions of amateur and professional investors has been evaluated.

This study examined the relationship between market monitoring cost consist the business disclosure index, the index of perception of corruption, rule of law and regulations quality, and also pointed out the technology index and exercise price limit rules that are in stock. In this research the relationship between the above indicators to price limit rules applied during the period 2005-2010 in a sample of 37 countries, including members of the World Federation of Exchange, also Tehran Stock Exchange that Complete data in the interval have been investigated. To estimate the model we used of software Stata11, Eviews7, and Excel. The results show that there is a Significant negative relationship between business disclosure index, perception of corruption and technology index with Utilization Price limit rules. Whatever The value of this index is less likelihood used of further legislation. The second part of the study also showed that to be effective each of the five indicators of market monitoring cost price limit on the range.

The purpose of this study was proposing a suitable pattern for evaluating and assessing companies. To reach this important goal, the fuzzy Delphi method (FDM was employed. After the evaluation pattern was created, the fuzzy analytic hierarchy process (FAHP) was used in order to find the weight of all selected factors, and the significance of each of evaluation factor was determined. Next, companies registered in Tehran Stock Exchange that are active in the chemical industries were examined and ranked separately in three financial years using two different techniques: VIKOR and TOPSIS. In order to determine the efficiency and accuracy of the model, three investment portfolios that included shares of the 4 companies ranked highest in each financial year were created. The performance of each investment portfolio was assessed and evaluated in a two months period using the Sortino ratio (SR) and compared with the chemical industry performance during the same period. The results reveal that the proposed pattern does provide investors with high level of accuracy.

index tracking is the process of developing a portfolio that reproduces the performance of an index. The tracker portfolio has relatively good diversity and low turnover and low transaction costs. In this paper we applied a binary programming model for index tracking problem. In this model the number of assets for portfolio construction is defined by portfolio manager. The robust optimization framework is applied for considering data uncertainty of correlation coefficient. The out of sample test demonstrated that considering the data uncertainty by robust optimization framework decrease the tracking error and increase the information ratio of portfolio.

The widespread and unprecedented international sanctions against Iran have affected the different sectors of the Iranian economy, including the banking system as the economic arm of the government. The reaction of the banking system to the challenges posed by the sanctions should be dynamic, sensible and with a consideration of priorities. Therefore it is necessary to identify the presented challenges, rank them and devise a pattern for managing them. In this research we set out by identifying 40 different challenges facing the banking system using the Delphi method, and ranking them by the Friedman test. Next, by conducting interviews with banking experts and analyzing the results, we have offered the proposed solutions as a conceptual model. Finally the validity of the presented model is tested by the Delphi method and the final model is prepared.

The Asian financial crisis in 1997 has awakened the regulators and corporates on the importance of corporate governance. According to agency theory, a good corporate governance system is necessary for more transparent information disclosure about the corporation. Accordingly, the objective of this study is evaluating the level of disclosure in banks and examine the relationship between some features of corporate governance with disclosure level. The level of disclosure is measured by disclosure checklist. Corporate governance variables tested in this study are the board size, institutional investors and independent non-executive directors. Sample data have been collects from 1390 until 1392 for twenty banks. The results reveal that better disclosure level of the annual reports in banking sector can be achieved by having higher institutional investors. Also There was a significant relationship between higher proportion of independent non-executive directors and disclosure level. However There is no significant relationship between board size and level of disclosure.

According to the trade-off theory, firm managers consider the transaction and precautionary motives to determine the optimal level of cash by comparing the benefits and costs of cash holdings. The purpose of this paper is to examine the impact of deviation from expected optimal cash on future stock returns among Irans’s listed companies (Tehran Stock Exchange). The analyses are performed by using data pertaining to 119 firms for the period 1388-1392. The results show that any deviation from the estimated optimal cash holdings is significantly detrimental to future stock return, suggesting that excess or insufficient cash is harmful to stock returns. The adverse influence of deviations above the optimal value is insignificantly stronger than that of deviations below the optimal value.

Insurance industry is one of the most influential economic institutions and is considered to support other economic institutions and families. Insurance industry has been facing changes that lead it to becoming a competitive industry. Therefore, we can say insurance companies that are active in Iran insurance industry must constantly monitor performance of their branches and agencies. Ongoing problems in existing assessing methods of organizations are their emphasis on a single index and subjective judgment. Therefore, the assessment should comprehensively take all aspects into account. Subjective judgment should be reduced as much as possible. Thus, in this study we evaluate the performance of Iran Stock Corporation and its branches by using data envelopment analysis (DEA) technique. Meanwhile, in the classical applications of DEA models typically problems occur such as ignoring undesirable outputs and non-discretionary inputs. Accordingly, in this study undesirable outputs and non-discretionary inputs have been investigated. The results show that 50 and 36 percent of the branches are efficient under variable and constant returns to scale respectively in the presence of non-discretionary inputs and undesirable outputs.