درخت حوزه‌های تخصصی

The stock exchange is considered to be an important establishment to finance long term projects, on one hand, and to collect savings and finance of private section. The stock exchange can be a safe and secure place to invest surplus funds to purchase corporate stocks. As recession and prosperity in this market can have a great role in stockholders` decision-making, it becomes vital to predict these cycles. In this paper, using model MSMH(4)AR(2), we extract the financial cycles of the market. Then, using the ant colony algorithm, we determine the most significant predictors and predict the market financial cycles using neural networks. The results show that the PNN model performs better in predicting the future market with respect to the criteria of mean squared error, the root mean squared error, the model accuracy and kappa coefficient.

Behavioral finance is a new issue raised by some financial intellectuals over the past two decades and has been quickly addressed by professors, experts, and students throughout the world. Investigating the factors affecting investment decisions is carried out in the field of behavioral finance; in other words, the focus of behavioral finance is on the specific charac-teristics of human behavior and applying them in asset pricing. Empirically, pricing models rarely include psychological factors, but the noticeable point is that nowadays, researchers have found behavioral factors influencing empirical asset pricing models that can manipulate returns on asset mispricing. Behavioral asset pricing is the result of applying behavioral finance theories within traditional asset pricing theories. Thus, despite the existence of many asset pricing models, due to their weaknesses and lack of comprehensiveness, as well as the necessity of reviewing behavioral factors, this study aims to model asset pricing through behavioral models. Using the data from 141 listed firms in Tehran Stock Exchange over the years 2008 to 2017 and multivariate regression, this study is an attempts to model asset pric-ing through employing behavioral models and Fama-French approach. Using Fama-French approach, the results showed that accounting information risk, investors’ trading behavior, and investors' sentiment have a direct and significant impact on asset pricing.

Several financial soundness frameworks, such as CAMELS, are currently present in the banking industry, but some evidence suggests that the present frameworks have inefficiencies in an Islamic banking environment. This study is aimed at identifying and prioritizing the adjusted financial soundness indicators in Iranian banks. In this paper, the factors affecting financial soundness in banking industry were investigated and rated based on the viewpoints of 382 banking experts. Data gathering is done by designing a questionnaire. The research method is descriptive-correlation. For data analysis and the testing of the hypotheses, R-test software and confirmatory factor analysis have been used. TOPSIS method is used to rate the indicators from the points of view of senior banking managers. The findings showed capital adequacy, asset quality, profitability, liquidity, management quality, sensitivity to market risk, Islamic banking, corporate governance, and facilities with technical and economic backing affect the financial soundness of banks, while the liquidity and profitability indexes have the most impact.

Strategic management accounting, including systems and processes in the modern era, is characterized by changes in the competitive environment that, Can be achieved through the participation of companies in the management accounting system, Assist financial managers to make decisions in the value chain and develop green accounting functions. Unfortunately, though, over time, strategic management accounting techniques are still unknown to corporate executives, especially in environmental processes, leading to a decline in corporate participation in strategic decision making. The Purpose of this research is Capacity Building Green Accounting Consequences Based on Explanation of Strategic Management Accounting Techniques by analysis of CARD and developed the theory of Rough (ERST). The methodology of this research is developmental, applied and hybrid and two groups of target population participated in this research. In the first part of 15 experts in the field of accounting at the university level an In the second part, 35 executives participated matrix Tehran Stock Exchange through a questionnaire that both the target population, sampling was homogenous. In this research, in the qualitative part, the components and indices related to the research variables were selected based on content analysis and cross-analysis and then based on Delphi analysis and hierarchical analysis in order to achieve theoretical adequacy. Then, in the quantitative section, through the analysis of the Rough Complex analysis, the decision tree determined the most effective green accounting function/outcome and strategic management accounting technique, and finally, the product life cycle costing technique is the most effective strategic management accounting technique for enhancing green accounting functions. In fact, the results showed that product cycle costing technique is a factor for enhancing the cost savings of recycling and waste recycling costs and increasing the competitiveness of the company as a component of green accounting competitive Consequences.

Banked based financial sector of Iran leads us to focus on the banking industry and its components. One of the important aspects of this industry is its coupling structure. In this paper, we have analyzed the collective behavior of Iran banking sector by Random Matrix Approach (RMT). This technique is useful for splitting the information part of the correlation matrix from the random region. This research confirms good compliance with random matrix predictions. By removing the market mode of the system the average of the banking cross-correlation matrix changes. Then, by calculation of the participation ratio, node participation ratio and relative participation ratios of these banks, it is shown that the collective behavior of the system is so fragile. Also, by applying local and global perturbations on the banking sector, it is shown that this system is very sensitive to the global perturbation and the mean value of cross-correlations decreases rapidly that means some banks have crucial effects in the market.