درخت حوزه‌های تخصصی

This paper examines monetary and fiscal policy through the estimation of a New-Keynesian dynamic general equilibrium model for Iran’s economy. In this New-Keynesian dynamic general equilibrium model, the consumers encounter the liquidity constraint and the firms face sticky prices, while they are changing them. In the model presented, a role is considered for both government spending and taxation, besides the monetary rule. Then, the model is estimated using Iran's data over the period of 2002-2017, through the method of generalized moments which leads into valuable insight. The results indicate that aggregate demand reacts to changes in interest rates. When inflation occurs, regardless of its source, it is persistent and inertia.The monetary policy has a forward-looking behavior. The output gap with a lag has a negative effect on government spending and the short-term impact of the output gap on government spending is smaller than its impact on taxation (Tax responses to the output gap are stronger and positive).

Customer relationship and recognition of the customer financial behaviour are considered as important strategic factors involved in successful performance of the banks. So, identifying these factors and prioritizing them help to make better decisions to complete the value chain of the banks’ financial services, especially in development banks that tend to have midterm and long-time presence in financial markets. So, the present research aims to identify and prioritize the mentioned factors in Bank of Industry and Mine as one of the main development banks of Iran. The present research has been performed in two phases. In the first stage, or qualitative part, In the first stage, during the review of the literature and the opinions of banking experts, the relevant indicators were identified. In the second stage, or quantitative part, the statistical data of variables in the period of 2012-2017 was collected. Then, the identified factors were prioritized by multi-criteria decision making in TOPSIS solver software. According to the findings, environmental factors are the main indicators affecting the bank customers’ financial behaviour. The most important customer-related factor was the definite profit paid to the customer; the most important bank-related factor was credit risk; and the most important environmental factor was economic growth.

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descriptive and practical and in order to collect data Stock Exchange database software has been used. For data analysis, we used artificial neural network in base form and artificial neural network mix with genetic algorithm. In addition for methods comparison, determination coefficient, Mean squared error and Root-mean square error have been used. The result of study shows that the best artificial neural network is a network with a hidden layer and eight neurons in the layer. This network could predict 97.7 percent of healthy and bankrupt companies correctly for test data. Furthermore the best mixed neural network with genetic algorithm is a network with 400 replications and population size 50, one layer and eight neurons which could correctly predict 100% of healthy and bankrupt companies. Finally, comparison of results of two methods shows that the best method for predicting financial crisis is mixed neural network with genetic algorithm.

Investment in renewable energies especially solar energies is encountered with numerous uncertainties considering the increased dynamism in economic and financial conditions and makes investment in this field irreversible to a large extent, paying attention to modern methods of economic appraisal of such investments is highly important. A framework is provided in the current study in order to employ the real option theory in evaluation of photovoltaic plants comparing with traditional methods. To this end, first, uncertainty factors of these plants in Isfahan province (one of highly susceptible regions in Iran) are identified from the view point of experts and impact factor of each one on interests and expenses of the above plant will be evaluated in order to insert these parameters in the form of fuzzy numbers in the model for better coverage of uncertainty. Then, the project under study is evaluated through both traditional methods and fuzzy real option approach with the help of Black-Scholes model and the results are compared. The results disclosed that investment value in these plants is increased if real expansion and abandonment options are considered. As a result, the real option theory has a higher adequacy than the traditional methods for evaluation of projects.

The purpose of this research is to provide a model for reporting quality of financial information based on behavioral and value accounting of listed companies in Tehran Stock Exchange which is based on Structural Equation Modeling. This research in terms of applied purpose is applied research and in terms of data collection method is post-semi experimental research in the field of proofing accounting research with deductive- inductive approach. The statistical population of this is including the sample of 128 listed companies in the Tehran Stock Exchange between 2007 and 2017. The behavioral characteristics of managers (hidden variables) is measured by observable variables of myopia, opportunistic behavior and over confidence of managers and the value content of accounting information (hidden variable) is evaluated by the observable variables of relevance of profit and relevance of book value. And reporting quality of financial information is also investigated based on the scores accrued to each company and the announcement published by the Tehran Stock Exchange based on the companies' rating in terms of the quality of reporting and proper notification. After insuring the acceptable fitness of the measurement pattern and the structure of research in both approaches; Structural Equations Modeling and regression, the results indicate that there is a significant negative relationship between the behavioral characteristics of managers and the reporting quality financial information. Also, there is a positive and significant relationship between value content of accounting information and reporting quality of financial information.