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Although theoretical and empirical literature regarding the stylized facts shows evidence of their correlations to herding behavior in financial markets, the causes of such phenomena are still unknown. Using an agent-based model strengthened by the competition co-evolution algorithm (STGP) technique, this study provides laboratory evidence on capital market dynamics and analyses the behavioral foundations of stylized facts such as fat tails, leverage effects, and volatility clustering. The simulated stock markets consist of two groups; the “Best agents”, which are a small portion of artificial agents, and the “Residual agents”, which are the main group of artificial agents. The best performance in terms of breeding fitness returns is the main feature of the “Best agents”. More, the size of the “Best Agents” group is specified as 2.5%, 5%, 10% &20% of the total population size. An agent-based model consists of two portions, a two thousand population of trader agents that each has its decision-making strategy, and a virtual market that creates the trading strategies. Then the model evolved step by step using a feed with real quotes of the financial instruments by Adaptive Modeler. A training period is considered 2500 bars (started in November 2003), and the test period started in December 2013. The observation shows that the herding behavior in the price series created by the “Residual agents” is less than the “Best agents” series. Therefore, the greater diversity of trade strategies as the genetic differences of artificial agents leads to less herding. The observations exhibit that the volatility clustering, leverage effects, and nonlinear dependence are more likely to experience in the price series generated by “Best gents”. Furthermore, observations indicate that if the population is well diversified in terms of trading strategies, the efficiency of the market increases.

Presenting an audit report is the basis for developing competitive strategies that, in the form of operational transparency, are able to guide stakeholders in financial decisions and inform them of operational information and facts. Because auditors have a crucial role to play in reporting these reports, they need to be more balanced, both professionally and on the basis of psychological functions, in finding performance gaps with the functional realities of companies. Therefore, knowing the individual characteristics in this area can help to develop the functions of the audit report. This is because auditors, like any person in charge of a profession, may face disruptions and negative performance characteristics that make it difficult for them to disclose corporate performance facts. Hence this study was to analyze the causes of alienation of conduct in a professional career path for a more comprehensive understanding of the auditor's job is frustration. This research is a mix of methods because through the analysis of grounded theory and with the participation of 17 auditing experts, it seeks to identify the components and statements related to the causes of behavioral alienation in the professional career path of trusted auditors of the Stock Exchange Organization. Then, through the link analysis method and with the participation of trusted auditors of the stock exchange organization, it tries to examine the stimuli and consequences of behavioral alienation in the professional career path of auditors in the form of a systematic representation model. The results obtained from the qualitative part of the existence of three cultural; Social and structural dimensions in the form of 7 categories. The results in the quantitative part also showed that the lack of symbols of professional behavior in the auditors of the stock exchange organization under the component of cultural dimension is the most important functional stimulus in auditors' professional frustrations as causes of professional behavior alienation that can result from this cultural disorder. Cause social conflicts in the professional work of certified auditors of the stock exchange organization.

The purpose of this paper is to focus on examining the impact of conservatism on IPOs underpricing and then examine the role of audit quality as a moderating variable in the relationship between conservatism and IPOs. Based on financial-behavioral theories, analyses are conducted of data from a sample of Tehran Stock Exchange (TSE) listed companies for the fiscal years 2008–2017 (i.e. 230 firm-year observations). Correlation and regression analyses are performed to evaluate possible associations between conservatism and initial public offerings (IPOs) underpricing with regard to audit quality. There is a negative significant relationship between conservatism and IPOs underpricing, i.e., it reduces IPOs underpricing. Also, the research results indicated that the auditing quality cannot moderate the relationship between conservatism and IPOs underpricing in Iran’s stock market. This conclusion may be explained under the winner’s curse theory. Accordingly, informed investors do not request to purchase unattractive stocks, and uninformed investors demand and obtain all the unattractive stocks since there is no competition between informed and uninformed investors. A limitation of this paper is the number of firms, which for future studies needs to be considered. This research is expected to contribute comprehensively to expanding the theoretical foundations and increase audience knowledge of the underpricing of initial public offerings (IPOs). It is also expected that the results of the study will: 1. determine the underpricing of IPOs in Iran during the research period; 2. document the role of conservatism in reducing underpricing of IPOs; 3. potentially prevent inappropriate pricing of new stocks. Furthermore, the findings of this study suggest that the application of financial-behavioral theories calls for more inquiry.

While travelers' desire to visit the world's most remote places has grown, the inefficiency of global payments indicates a significant barrier to tourism growth. As an emerging, decentralized, and borderless digital innovation, Bitcoin technology seems to have the ability to serve as a payment alternative and address such fundamental inefficiencies. On the other hand, bitcoin adoption can only happen when tourists and business owners choose to operate bitcoin simultaneously. The study has developed a novel Bitcoin Collaborative Network and Tourism Collaborative Network model to examine Bitcoin adoption factors. Then a fuzzy DEMATEL method was applied to the factors influencing the adoption domain, as identified based on an extensive literature review, in-depth interviews, and an international Delphi process. The study offered a model for the heterogeneous collaborative network of Bitcoin and Tourism (BCN and TCN), revealing that Perceived Usefulness is the most influencing criterion and the most prominent variable in Bitcoin Adoption. Bitcoin Technological Complexity, Government Regulatory, and Bitcoin Awareness are the factors that give the highest impacts. Also, Bitcoin's Technological Complexity is the most significant factor in bitcoin adoption. The findings might assist businesses in adopting a new market expansion strategy and benefiting from technological spillover, while government officials can explore new supporting legislation.

The ability to predict the stock market and analyze market trends is invaluable to researchers and anyone interested in investing. However, this task is a challenging problem due to a large number of parameters and unpredictable noise that may affect the stock price. To overcome this issue, researchers have employed numerous approaches such as Moving Average (MA), Support Vector Machine (SVM), and Neural Networks. With technological advances, deep learning methods have become popular in processing time-series data. In this paper, we compare two recently introduced deep learning models, namely a Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in forecasting daily movements of the Standard & Poor (S&P 500) index using the daily closing price of this index from 14/5/1991 to 14/5/2021. Results show that both models are effective and accurate in stock market prediction. In this case study, the mean squared error (MSE) and mean absolute error (MAE) for the GRU model are slightly lower than the LSTM model; hence, GRU outperformed the LSTM model despite its simpler structure. The results of this study are applicable in various instances where it is challenging to identify patterns among large volumes of unstructured data, such as medical data analysis, text mining, and financial time series modeling.

Data mining is known as one of the powerful tools in generating information and knowledge from raw data, and Clustering as one of the standard methods in data mining is a suitable method for grouping data in different clusters that helps to understand and analyze relationships. It is one of the essential issues in the field of investment, so by using stock market clustering, helpful information can be obtained to predict changes in stock prices of different companies and then on how to decide the correct number and shares in the portfolio to private investors and financial professionals' help. The purpose of this study is to cluster the companies listed on the Tehran stock exchange using three methods of K-means Clustering, Hierarchical clustering, and Affinity propagation clustering and compare these three methods with each other. To conduct this research, the adjusted price of 50 listed companies for the period 2019-07-01 to 2020-09-29 has been used. The evaluation results show that the obtained silhouette coefficient for K-means Clustering is higher and, therefore, better than other methods for stock exchange data. In the continuation of the research, calculating the co-integration of stock pairs that have the same co-movement with each other were identified, and finally, clusters were compiled using the t-SNE method.

The main purpose of this study is to identify the determinants of banking crisis losses for 49 sample countries over the period 1980-2019. In this regard, two sub-purposes are pursued. In the first preliminary step, we identify and date episodes of banking crises for 49 countries. The graphical analysis of crises showed that about half of the crises were occurred between 2008-2012 in which the share of high-income countries was higher than other country groups. Then, in the second preliminary step, we used the Hodrick-Prescott filter to extract different trends from countries' GDPs to calculate four alternative measures of real output losses. The investigated output losses showed that Angola and Greece had the highest and lowest losses among the four types of losses, respectively. Finally, to achieve the main purpose, we use the Poisson quasi-maximum likelihood (PPML) method to estimate model. The model was estimated without and with currency crisis variable. Our findings show the occurrence of a currency crisis is effective in intensifying output losses following banking crises. Also, the variables of inflation, bank credit to GDP, credit-to-GDP gap, public debt/GDP, with a positive effect and variables of financial openness, discretionary government spending and central bank assets with a negative impact, are important factors in output losses of banking crisis. Therefore, we recommend that the mentioned variables be considered in banking crisis management.

The purpose of the study is to portray the effect of exchange rates, its uncertainty and covid-19 pandemic on house prices in Tehran using the monthly data from Mar, 2016 to Mar, 2021. In order to calculate the uncertainty, IGARCH model and to estimate the mean equation, the ARDL method have been used. According to research results, the effect of exchange rate and exchange rate uncertainty index on housing prices as the objectives of this study, are positive and significant. Accordingly, a 100% increase in the exchange rate and the exchange rate uncertainty index will cause a 14% and 6% increase in housing prices in Tehran, respectively. Therefore, any action that reduces uncertainty in the future situation of the foreign exchange market can be effective in reducing the negative effects on housing supply and demand. Also, the results of model estimation show that the outbreak of Corona virus has acted as a shock and increased housing prices in Tehran.

The main purpose of this paper is to calculate the entropy of money in the space of Gross domestic product with the approach of econophysics and investigating the effect of stock market development on it. In this regard, by using annual data in the period of 1370-1398 in the framework of Smooth Transition Autoregressive Model (STAR), the asymmetric behavior of monetary irregularities around a threshold at different levels of stock market value as a variable of analysis is investigated. The results show that at low levels of current value of the stock market (the first regime), net capital inventory and budget deficit of governments have positive effects and the number of companies admitted to the stock exchange organization have a negative effect on monetary entropy. At high levels of current value of the stock market (Second Regime), net capital inventory has negative effect and government budget deficit continued to have a positive effect on monetary entropy. Based on the results of this study, it is clear that the dynamics of the stock market will reduce monetary entropy, which is itself an indicator of wasting and lacking of access to the resources.

Studies conducted on the relationship between central bank independence and inflation show heterogeneity in the results. Some of these studies have concluded a negative relationship, while others have concluded a positive or insignificant relationship between central bank independence and inflation. The purpose of this study is to conduct a multilevel meta-analysis to examine the effect of central bank independence on inflation. For this purpose, all full-text articles that examined the relationship between central bank independence and inflation were reviewed. After reviewing the content and results, 58 studies were selected to enter the meta-analysis based on the meta-analysis protocol. Data from 58 selected studies included 619 regressions and 913 coefficients that were extracted and coded. In the first level of meta-analysis, the regression coefficients of each study were combined and the effect size of each study was calculated. In the second level of meta-analysis, to calculate the total effect size, the effect size of 58 studies was determined according to the weight of each study. The result of the combination and conclusion of individual studies shows that the independence of the central bank has a small negative and significant effect on inflation. The results also showed that the type of index used to calculate the degree of central bank independence affects the relationship under meta-analysis. In addition, the negative effect of central bank independence on inflation is greater in developed countries than in other countries.

This paper investigates the effectiveness of monetary policy in recession and expansion periods of business cycles in Iran. It uses the distribution of price changes over time using micro-data of producer and consumer price indices from March 2004 to March 2007 and March 1990 to March 2017. Results show that the observed distribution price changes at the producer and consumer levels change significantly over time. Whereas price flexibility (or, similarly, price stickiness) is closely related to the impact of monetary policy, the variable distribution of price changes over time suggests that the effectiveness of monetary policy should also change over time. We estimated the related parameters using the Ss model and the observed facts from the distribution of price changes, the price flexibility index, which shows how prices react to a monetary policy shock. The correlation coefficient and regression analysis results showed that the price flexibility index is counter-cyclical; this means that during periods of economic recession, the index of price flexibility increases. Therefore, the impact of monetary policy on real output decreases. However, during periods of economic expansion, the impact of monetary policy increases.

One of the basic needs of human society, which is related to the issue of development in all its aspects and is now considered as one of the signs of civilization, is the issue of economic infrastructure. In addition to affecting development, this infrastructure is also changing. Therefore, in the present study, the rate of economic infrastructure development in Mazandaran province has been measured using the model of Analytical Hierarchy Process (AHP), FUZZY Logic and Geographic Information System (GIS). The research method is descriptive-analytical and it can be used in the regional planning system. Accordingly, spatial layers of transportation, energy and information and communication technology (ICT) were obtained through the statistical yearbook Mazandaran province in 1398. In the following, three economic infrastructure development evaluation indicators along with related sub-criteria were rated by the participants through a questionnaire and they were integrated in the Geographic Information System (GIS). Finally, the research maps show that 49.01% of the cities in the province are in a very high category of economic infrastructure. 27% of cities are in the middle and upper middle level and 23% suffer from low and very low in economic infrastructure facilities. On the other hand, 39% of Mazandaran villages are situated in the best zone of infrastructure.

Poverty is a global issue of high importance for both developing and developed countries. The first step in tackling poverty is to identify the impact of economic policies on poverty indicators. In this direction, the purpose of this study is to measure the effect of foreign tourism development on poverty reduction using SAM fixed price multiplier approach. For this purpose, 2011 SAM, 2018 foreign tourist receipts, and three poverty indicators: head count ratio, poverty gap, and (FGT) have been considered. The results indicate that the arrival of foreign tourists through the production growth channel reduces poverty in Iran and reducing poverty of rural households is greater than urban households. Results also show that the highest share in sectoral poverty reduction based on the three poverty indicators is related to the agricultural sector (based on the census poverty index), hotels and restaurants, and manufacturing, and transportation (based on the poverty gap index and the FGT indices). Whereas the least reduction in poverty occurs in the financial, insurance and education activities. Any policy making in the direction of tourism development is considered as a suitable socio-economic achievement.

Stock returns forecasting is very crucial for investors, share-holders and arbiters. Different methods have been developed for this purpose. In general, there are four methods of forecasting in stock markets, which are; Technical Analysis, Fundamental Analysis, Traditional Time Series and Machine Learning. This study is classified in the third category that is a time series prediction in which the values of a variable are predicted over time. Studies which have been done so far indicate that most of them concentrate on Neural Networks and Genetic Algorithm which are in Machine Learning class and none of them uses Bayesian approach or Exponential Smoothing and Box Jenkins techniques placed in the group of time series forecasting. This paper focuses on forecasting with time series methodology for predicting and comparing the results of the Bayesian, Exponential Smoothing and Box Jenkins methods together. In fact, the difference between this study and others is the comparison of the mentioned methods for stock return forecasting. The period of investigation was 2018- 2020, which covers daily frequency structure. Results, indicated that Bayesian method, based on the Root Mean Square Error (RMSE) criterion is the best technique for the prediction of stock returns. This is because, in addition to information derived from data, this method also uses other sources of information such as non-sample information or vague prior density as well for forecasting. Results illustrate the importance of considering the Bayesian approach in predicting stock market returns.

Given the importance of Rawls and Nozick as two prominent philosophers from left and right wing of liberalism, in this paper a comparative root-seeking evaluation about their distributive justice theories is presented. By using the idea of explanation of expectations from a distributive justice theory based on a problem-oriented approach, through a step by step root-seeking process, philosophical foundations of distributive justice theories of these two philosophers were identified. Then on the basis of internal and external consistency criteria, these foundations and theories were evaluated. The results of study are as follows: while Rawls founded his theory and particularly difference principle on the Kantian foundations which was the target of Nozick’ criticism; Nozick Which besides Kant, was under influence of Locke, founded his theory on the existence of a kind of natural law. Also while Kant and Locke, each in some way, harmonized their own value foundations with divine anthropological and epistemological foundations, Rawls harmonized it with this anthropological foundation that there exists a common sense of justice in humans, without mentioning the material or divine source of this moral sense. In contrast, Nozick harmonized value foundation of his theory with a kind of natural law; a godlike natural law that by determining the initial distribution of natural endowments, was determinant factor of entitlement of each individual; a distribution that Rawls even didn’t permit the use of just or unjust adjective about it.

The effect of exchange rate changes on the general level of prices is one of the major issues in macroeconomics and has important results for the monetary policy maker. With respect to these two variables in Iran's economy, modern econometric approaches can provide new insights. In this regard, using the threshold vector autoregressive model, the present study attempts to investigate the nonlinear exchange rate pass-through in Iran during 1369:1 – 1397:4. The results show that pass trough of exchange rate to the general price levels depends on the amount of inflation (inflationary conditions and its threshold). If seasonal inflation exceeds from 5.48%, the exchange rate shocks has lower effect on inflation. The results show that, exchange rate shocks have a severe effect. Due to the lack of inflation targeting policy in the Iran’s economy, the impact of exchange rate shocks on inflation is lower in values below the level of 5.48%. Accordingly, in inflation rates below the threshold, monetary policy has less freedom of action and the goals of reducing inflation and exchange rate policies need to be taken into account simultaneously.

In this paper, the effect of population aging on economic growth in a closed economy in which the element of human capital is endogenously formed is simulated. For this purpose the computable generalized Diamond overlapping generation’s model are used for a period of 50 years. First, the dynamic effect of aging on macroeconomic variables, especially economic growth, are simulated in the baseline scenario (current state of the Iranian economy).Then the dynamic effects of public policies under different scenarios of human capital and pensions ratios on economic growth for a period of 50 years are simulated. The results of the model showed that the government's general policies to increase human capital increase the share of skilled labor (effective labor) and therefore have a growth effect. At values ​​of public policy tools above the baseline scenario​​(industrial status), the effect of productivity on aging prevails and long-term growth increases.In addition, the results showed that increasing the ratio of pensions to the level of developed countries encourages demand-based economic growth, but has a level effect and does not change long-term growth. The results show that increasing aging, if combined with government policies to promote human capital, can potentially offset the negative impact of aging on growth.

Macroeconomic policy analysis and risk management require taking account of the increasing interdependencies across markets and economies. National economic issues need to be considered from global as well as domestic perspectives. This invariably means that many different channels of transmission must be taken into account. This paper investigates the effect of global economic shocks on Iran’s economy. The Global Vector Autoregressive (GVAR) model for the first quarter of 1990 to the fourth quarter of 2019 is used for 34 countries, which cover about 90% of world gross domestic products. According to previous studies and the results of this study, it is found that only the shocks of the United States, China and the global shock affect the macroeconomic variables of other countries and oil prices, and as a result, the effect of these three shocks on the Iranian economy is investigated. Ceteris paribus, the results show that China's shock affects the variables of GDP and Iran's inflation: with a 1 percent increase in China's GDP, Iran's GDP increases by 0.08 percent and inflation by 1.2 percent and has no effect on interest rates. The US shock has an indirect effect on oil prices. Due to the isolation of the economy, foreign variables do not have significant effects on the Iranian macroeconomic variables. In general, Iran's economy, due to the size of the economy and the volume of trade shocks of other trading partners through the foreign trade channel do not affect the Iranian economy.

Economic complexity means the ability to produce a variety of products at the level of global competition. The importance of economic complexity in increasing the wealth and development of countries has been confirmed by studies and empirical evidence. The present study examines the relationship between social technologies (ST) and economic complexity among 137 countries from 1998 to 2019. Social technology (ST) refers to all the methods, designs, and elements necessary (including institutions, structures, maps, processes, and cultural norms) for organizing individuals to achieve a specific goal or goals. The health and maturity of social technologies make it possible for economies to produce complex goods by integrating large amounts of knowledge, skills, capacity, and experience into complex networks of interactions. To investigate the possibility of a simultaneous relationship between the two variables, the PVAR model was used. The results of this study confirm the existence of a simultaneous and two-way relationship between the rule of law and economic complexity.

The purpose of this paper is to specify an early warning system for currency crisis and to investigate the role of capital control together with other warning indicators in the crisis. Increasing mobility of capital and liberalization in international financial flows is one of important dimensions of globalization, which has significant benefits to many countries worldwide. However, due to negative impacts on exchange rates as well as currency crises, financial liberalizations followed by some Latin American and Southeast Asian countries raised concerns in the last decade of the twentieth century. Hence the question: can capital control play a role in preventing or exacerbating the currency crisis? This study evaluates the relationship between capital control index and currency crisis and also examines the role of this variable as a warning indicator. Since the main application of the early warning systems is crisis forecasting, the purpose is to model the early warning indicators of currency crisis using Bayesian averaging method. To achieve this, 70 variables were examined for 60 countries during the period 1975-2019, both in floating and non-floating exchange rate systems. The results showed that capital control has a significant effect on reducing the occurrence of currency crisis, also different capital control indicators do not have the same warning power. In addition, different currency systems are effective in changing the power and rank of warning variables, especially for the use of capital control index.

The present study aimed to explore the impact of banking crisis on income distribution among various income classes in 60 world countries during 1990–2020. In this line, the Generalized Method of Moments (GMM) was used to estimate the six models with different dependent variables that depicted income percentiles for the wealthy, middle, and poor classes. The findings indicated that during a banking crisis, the income share of the wealthy class decreases, while the middle class and the bottom 20% experience an increase in their income share. Consequently, banking crisis could contribute to income equality in the countries under study. In addition to the variable of banking crisis, other variables such as financial development and financial openness could lead to income inequality, while the variables like the ratio of public expenditure to GDP, trade openness, GDP, and GDP squared would cause income distribution equality in the countries. The results suggest that governments support lower-income percentiles through subsidies, support packages, more job opportunities, and provision of low-interest loans, in a bid to mitigate the detrimental effects of banking crisis and reduce income inequality. Furthermore, governments should levy taxes, such as capital gains tax, on higher-income percentiles.IntroductionThe literature offers various definitions for banking crisis. For instance, Liana et al. (2015) define banking crisis as the occurrence of simultaneous bankruptcies within the banking sector, resulting in substantial damage to the capital of the entire banking system, significant economic repercussions, and government intervention. According to Laeven and Valencia (2020), banking crisis occurs when two conditions are met: 1) “significant signs of financial distress within the banking system (indicated by significant bank runs, losses in the banking sector, and/or bank liquidations)” and 2) “significant intervention measures in banking policy in response to significant losses in the banking system.” The year in which both criteria are met is the year when crisis becomes systemic. Banking crisis exerts a myriad of effects, with one notable consequence being the issue of income inequality. There are two points of debate in this respect: the impact of banking crisis on income inequality and the reciprocal influence of income inequality on banking crisis. This research focused on the former. There are various channels through which banking crisis can adversely impact households and their income, including:(a) Loss of deposits in a failed banking institution(b) Loss of employment or earnings directly due to (i) disruption of the payments process, (ii) the bankruptcy of financial institutions (for employees and other stakeholders of these institutions) or (iii) the interruption of credit flows (for borrowing clients with information capital invested in the failed financial institutions)(c) Tax increases or curtailment of public spending due to fiscal cost of bail-outs of financial firms or their customers(d) Temporary or permanent changes in relative prices of (i) consumption goods, (ii) wage rates, (iii) production goods (iv) asset prices, that arise through knock-on effects on the rest of the economy(e) Involuntary unemployment if the crisis leads to a generalized economic downturn. (Honohan, 2005, pp. 6–7)In this context, the present study tried to answer the following questions: How does a banking crisis influence the income distribution of households and contribute to income inequality? Is the presumed impact the same across different income classes (i.e., wealthy, middle, and poor)?Materials and MethodsIn line with El Herradi and Leroy (2022), the present study used the following economic model:(1) In the model, refers to the income share of six different percentiles (p) including Top1%, Top10%, Top20%, Middle-class (21–79 percentile), Bottom20% and Bottom10% in the country i at the time t. is a dummy variable of the banking crisis (1 if a country i faces a banking crisis, otherwise 0). indicates the dependent variable of income distribution, with two lags to show the dynamics of the model. Finally, is a vector of lagged control variables, including GDP and GDP squared, financial development, trade openness, financial openness, the ratio of government public expenditures to GDP and political governance. Also, , and refer to country fixed effects, time fixed effects and an error term, respectively. , and k are model coefficients. The study sample comprised 60 countries worldwide, with annual data spanning the years 1990 to 2020.Results and DiscussionThe occurrence of a banking crisis is linked to significant yet varied effects across the income distribution. Consequently, during a banking crisis, the income shares of the top 1%, top 10%, top 20%, and bottom 10% experienced a decrease. Moreover, a banking crisis resulted in an increase in the income share of the middle-class population (21–79 percentiles) as well as the bottom 20% of individuals. Notably, the rise in the middle class was more substantial. Conversely, the lowest income group (the bottom 10%) exhibited a negative correlation between banking crisis and income share, mirroring the trend observed in the upper percentiles. However, the reduction in the income shares of the lowest income group (the bottom 10%) is considerably less than the losses suffered by higher income groups. According to the findings, the adverse impacts of banking crisis are more pronounced at the right end of income distribution. Therefore, the crisis could contribute to a reduction in income inequality.ConclusionThe findings indicated that a banking crisis adversely affects the income shares of the top 1%, top 10%, and top 20%. In simpler terms, a banking crisis diminishes the income share of these groups in the overall income of society. Notably, the reduction in the income shares of the top 10% (-0.426) is more pronounced compared to the top 1% and top 20% percentiles. Conversely, a banking crisis can increase the income share of the middle class (21–79 percentiles) and of the bottom 20% (i.e., the poor class), with a particularly substantial increase observed in the middle class. Turning to the lowest income group (the bottom 10%), a negative correlation exists between banking crisis and income share. Despite facing a decrease in income similar to the top income percentiles, the decline in their income share is considerably less than the losses experienced by the wealthy percentiles.In summary, a banking crisis could diminish the income share of the wealthy class and increase the income share of the middle and lower classes, contributing to a reduction in income inequality in the studied countries. Consequently, to mitigate the adverse effects of a banking crisis, governments can provide support to low-income percentiles through subsidies, support packages, more job opportunities, and low-interest loans. Additionally, taxes on high-income percentiles, such as capital gains tax, can be helpful. The measures can ultimately lead to a reduction in the income share of the wealthy percentiles and an increase in the share of the lower percentiles, improving income distribution and reducing income inequality.

Earning is one of the most important items of financial statements. Sometimes managers manipulate and distort earning reports to maximize their own benefits, reach a certain profitability level, or achieve a certain corporate objective. Firms with a low level of debt tend to have few or no restrictive clauses in their debt contracts, which allow them to operate with less concern about breaching these contracts and give less incentive to managers to engage in earning management reports through accrual manipulation. However, when firms accumulate large amounts of debt, the relationship between debt and accrual-based earnings management tends to get reversed. In firms with large debts, managers are incentivized to report good earnings as they are under pressure to avoid the penalties of violating the restrictive clauses in their debt contracts. In the absence of scientific and empirical evidence regarding this issue, the present study examined the nonlinear relationship between debt structure and real and accrual-based earnings management. For this purpose, the data pertaining to a sample of 130 firms listed on the Tehran stock exchange from 2014 to 2019 were collected and analyzed. The results of multivariate regression analysis showed a nonlinear relationship between debt structure and accrual-based earnings management. A non-linear relationship was also found between current debt structure and real earnings management. However, the results could not confirm the presence of a non-linear relationship between total debt structure and real earnings management

The scholars of social responsibility have focused on identifying the factors affecting corporate social responsibility disclosure (CSRD). Corporate social responsibility is a key factor in the survival of any organization. The purpose of the study was to examine the relationship between the size of the company, ownership structure, and governance structure to explain the determinants of Corporate social responsibility in Iran. Regarding this, the data of 127 companies listed on the Tehran Stock Exchange from 2009 to 2018 were collected and analyzed. Multiple regression model as panel data and fixed effects method was used to test the hypotheses. The results from the study tests indicated that the size of the company is an effective factor in Corporate social responsibility in Iran. The role of this factor is positive. Larger companies have been more successful in Corporate social responsibility. Moreover, the ownership structure is a determining factor and has improved the disclosure of social responsibility. The presence of major owners in the company potentially enhances the dissemination of information and protects the interests of minority shareholders, and the corporate governance structure has not been a determining factor in Corporate social responsibility in Iran. Indeed, the board's ability to perform its duties decreases when its size is large.

Rising inflation in recent years has caused financial distress and many problems for companies. Most of these problems are affected by life cycle stages. One way out of these problems is to increase corporate social responsibility (CSR) performance. Therefore, our aim in this study is to investigate the effect of CSR performance on financial distress over the life cycle of the company for a period of 10 years. Data collection was done through the website of the Tehran Stock Exchange and related software for a sample of 112 companies during the period 2009 to 2019. The mathematical method (directional distance function) is used to evaluate the CSR performance, and the models of Berger et al., Almida, Campello, and Altman are used to measure financial distress. The research hypotheses are tested using panel data and fixed effects by multivariate regression statistical method. The results show that CSR performance alone does not affect financial distress. The combination of CSR and life cycle in the growth and maturity phases has a significant and negative effect on financial distress. The CSR performance and life cycle together reduce financial distress. The combination of CSR performance and life cycle in the recession phase has a positive and significant effect on financial distress and in the fall phase, does not affect it. Given that companies compete more in the phase of growth and maturity than other phases of the life cycle, they also pay more attention to CSR. Therefore, according to these results, it can be concluded that the life cycle of the company and the CSR performance together, reduce financial distress.

The efforts of the developers of capital market laws and regulations over the past years have been aimed at increasing the level of information transparency to create more symmetry between companies and shareholders so that they can be more attractive to investors to invest in the stock market. But given the interplay of individual characteristics of corporate decision-makers with the interests of shareholders and investors, it seems that focusing on behavioral functions in the area of promoting managerial ability can more effectively lead to increased protection of shareholder interests. The purpose of this study is to investigate the effect of management ability on the protection of investors based on the development of the theory of the devil's advocate. Therefore, the present study, using the structural equation modeling approach and partial least squares analysis (PLS), while fitting the model's desirability, examined the impact of management ability on protecting investors. In this study, in order to measure the in-field variable, ie protection of shareholders' interests, a researcher-made questionnaire was created through meta-analysis with the participation of 15 research experts. Then the criterion of Demirjan et al (2013) was used to measure managerial ability as an exogenous variable in partial least squares analysis. The researcher-made questionnaire was sent to 142 CEOs of companies listed on the Tehran Stock Exchange, and finally, after many follow-ups, 105 questionnaires were completed and returned and used as a final sample for analysis. After ensuring the acceptable fit of the measurement and structural models of the research, according to the theory of the devil's advocate, the results showed that the ability of management has a positive and significant effect on protecting the investors. Managerial ability, as one of the specialized decision-making capacities, puts the company on the path of effective interaction with stakeholders and provides the ground for investors to Protect in companies' priorities to gain their trust.

The primary purpose of this study is to investigate the relationship between Political Communication and Information Asymmetry with the efficiency of investment in companies listed on the Tehran Stock Exchange. To achieve the above goal, two hypotheses were formulated. To test research hypotheses, a sample consisting of 109 companies listed on the Tehran Stock Exchange in the period 2014 to 2019 was selected. And a panel regression model based on composite data was used which has independent and dependent variables. The results of this study show that Political Communication has a negative and significant impact on Investment Efficiency, In contrast, Information Asymmetry has a positive and significant impact on Investment Efficiency, and this means that with increasing information asymmetry, investment efficiency increases. Therefore, political communications prefer corporate resources to pursue profitable investment options, thus altering corporate investment behaviors and reducing corporate investment efficiency. The results also show that Information asymmetry prevents investors from commenting on investment opportunities, thus allowing local managers to take advantage of profitable investment options.

The impact of personal judgment on the assessment of an individual’s financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant’s total score which is a combination of several factors and indicators. Over the past few decades, credit scoring has been considered an essential tool for evaluation in various institutions and has also been able to transform the industry as a whole. Most of the research conducted in the field has taken into account traditional credit scoring, but considering the ever-evolving technological world that we live in and the increasing emergence of new social media networks, such research has now become obsolete. Such technological advancements have not only paved the way for far more sophisticated credit scoring systems but also essentially rendered the previous generations useless. It should be noted that credit scoring and its features have widely been discussed across the globe but, considering the various aspects and models that have to be taken into account, no one best method has been designed or suggested for it so far. This study shows that social media channels tend to perform relatively well in predicting stock market trends when the overall index is growing positively. The research also illustrates that a higher number of days of activity and a large number of signals released do not necessarily mean that the channels can or have credited their offered stock return on a one-month time frame. The methodology used is "CRISP-DM," which consists of six steps. The main variables include social and financial variables that are examined for six months. In the research, we seek to identify, analyze and categorize active telegram channels in stock signals using the data mining model and the RFM method. The k-means algorithm is selected for this category. Then, in each cluster, the importance of social variables and the performance of the channels are extracted by the EXTRATREECLASSIFIER algorithm, and channel performance is measured by considering the changes in the total index.

Financial constraints are one of the influencing factors on investment decisions. Financial constraints put firms under pressure to forgo investment opportunities to finance their working capital needs. Moreover, some variables like working capital needs and liquidity of a firm are likely to affect the relationship between these two variables. Hence, this study seeks to examine the effect of short-term credit constraints on the investment of small and medium-sized enterprises (SMEs), firms with different characteristics in comparison with large-sized firms. In addition, this correlation is tested by considering the effect of mentioned moderating variables (working capital and liquidity). The sample of this study includes the firms listed in Tehran Stock Exchange from 2011 to 2018, which are considered as SMEs based on some criteria. Multivariate regression models and E-views software are used to test the research hypotheses. The results indicated that short-term credit constraints negatively affect corporate investment. It means that constrained firms invest in fewer investment opportunities because of facing source shortages. Moreover, in companies requiring more working capital, the inverse effect of short-term credit constraints on corporate investment is stronger. Such firms suffer from financial problems and are not able to use their investment opportunities. Additionally, this hypothesis that companies with high liquidity can offset u effects of short-term financial constraints on fixed investment, is not confirmed

There are many factors affecting Foreign Direct Investment inflows into the countries. One of them is Special Economic Zones that encourage Foreign Direct Investment inflows and achieve remarkable results in the world. Special Economic Zones are defined in the United Nations Conference on Trade and Development as the regions where production, trade and storage are not limited to time and are exempt from customs and taxes. This study analyzed the relationship between the Foreign Direct Investment inflows of Turkey, the Foreign Direct Investment inflows of the World and the number of the Special Economic Zone types analyzed using the Autoregressive Distributed Lag Method from 1980 to 2019. The results show that Foreign Direct Investment inflows of the World have a positive and significant effect on Foreign Direct Investment inflows Turkey in the long term and the short term. Also, the number of total Special Economic Zone has a positive and significant on the Foreign Direct Investment inflows of Turkey. Foreign Direct Investment inflows of Turkey increase 1.01% and 2.58% in long term and short term, respectively when the increase is 1% in the number of total Special Economic Zone. Moreover in this study, a number of the Special Economic Zone types such as OIZ, TDZ, FZ have been analyzed.

Given the lack of a specific approach to the explanation of values of optimal portfolio weights in the portfolio optimization, the present study aimed to examine large-scale portfolio optimization according to both stock weighting and utilization of SCAD function to minimize the portfolio risk based on the "weight-modified conditional value at risk (CVaR)" and its comparison with the "conditional value at risk (CVaR)" method in the Tehran Stock Exchange. Therefore, the price information of companies listed in the Tehran Stock Exchange and Over-the-counter (OTC) from 2012 to the end of September 2020 was collected, screened, and analyzed daily, and then the risk and return of the portfolios were examined by forming optimal portfolios. The results indicated that the efficiency limit of the stock portfolio and also the ranks of different companies were different according to the types of the optimization method. Based on the behavior of the TEDPIX, the investors' degrees of risk-taking, and the risk management, diversification, and computational complexity of each method, the weight-modified CVaR had a better performance due to better diversification and risk management. Furthermore, the SCAD function added computational complexity to this method.

Sustainability reporting is an important tool for decreasing information asymmetry, according to the stakeholders' demands for transparency. On the other hand, increasing transparency allows investors to have more appropriate evaluations of firms' activities and direct their investments to companies with more enthusiasm. In the organizational context, information asymmetry creates conflict between owners and managers. Managers tend to reduce the gap between themselves and stakeholders, particularly shareholders, by producing and delivering reports. Companies use sustainability reports to connect with their society and environment, as well as a way to manage interactions with various stakeholders for societal approval and activity continuation. The primary purpose of this study is to provide a model for measuring the quality of sustainability reporting and the determinants. In terms of methodology, the current study is qualitative, deductive, cross-sectional, applied, and exploratory. The criteria were identified and extracted, then evaluated and prioritized using Multi-Criteria Decision-Making approaches including Fuzzy Analytic Hierarchy Process and Fuzzy Decision-Making Trial and Evaluation Laboratory Analytic Network Process-based. The FAHP test revealed that of the six indicators, the GRI's reporting guidelines for sustainability Checklist were placed highest. Internal Controls Reporting, Sustainability Innovation Performance, and Earnings Quality rated first to third, respectively, among the 25 criteria affecting the quality of sustainability reporting, according to the FDANP.

Asset allocation has always been a challenging issue / for individuals and businesses to survive in our competitive world. One of the famous businesses, which has an enormous impact on people's lives worldwide, is the pension industry. Pension funds- as Defined Benefit, Defined Contribution, or others- accept reserves from contributors and try to invest them in a way to keep up with their obligations in the future or even pay more than that. The equity market has been one of the good choices for investment as pension funds try to reach a particular rate of return to maximize their wealth while considering not crossing red lines in taking risks. This paper will detail the new mathematical model for finding optimal stock portfolios using Generalized Co-Lower Partial Moment as a risk measure to minimize portfolio optimization. On the other hand, it introduces new tailored Expected Utility as a performance metric to maximize in this model. The proposed model's issue against previous studies is considering risk aversion and target rate of investment return as two significant investor characteristics. This is based on price returns' simulation of candidate stocks in TSE while using accurate and nonparametric Probability Density Function in historical data analysis.

The growth and complexity of society justify the need for relevant economic information, information systems, and information-generating processes, and the need for auditing as part of the information reporting process increases. This has affected the professional functions of auditors. The purpose of this research is to choose the influential dimension of mindfulness of auditors' professional judgments based on social pressure analysis based on Rough Theory. The methodology of this research is mixed and it has been used by Meta-synthesis, Delphi and Rough Theory. The target population was the qualitative, similar research and academic experts in the field of accounting. However, the target population in a small number of 19 audit partners had more than 5 years of work experience, which is acceptable from the statistical population due to the requirement of Ruff theory analysis. In this study, based on the Meta-synthesis analysis of selected researches, 4 propositions of pressures based on social compliance and 3 components of auditors' professional judgment were determined. The results in this section show that the most effective proposition of social compliance pressures was the market pressure proposition, which affects the inferential consciousness of auditors in their professional judgment and violates the auditors' mental functions such as skepticism and objectivity.

Improving the quality of institutions with development of the country's economic infrastructure can reduce the degree of fiscal policy cycles in developing countries. Therefore, the purpose of this study is to analyze the effects of good governance and political cycles on the liquidity and budget deficit changes during 1978-2018. The research method is descriptive analytical by using econometric method of the GMM. Data are from the Central Bank of Iran and World Bank site for Iranian Economy. The research results show the effect of good governance on the variables of liquidity and budget deficit changes are negative and significant. Also the interactive effects of good governance and the election dummy variables on the liquidity and budget deficit changes are negative and significant. These results indicate that good governance during the elections can control the budget deficit and liquidity changes, hence to control the business-political cycles, suggest to improve the good governance in Iran.

The primary purpose of this study is to explain an extended concept of human development called human flourishing using the link between economic and psychological approaches. Also, the paper explains why non-cognitive skills are essential. The first approach is based on the technology of skill formation, and the second approach is based on the theory of hierarchy of needs. The Human Development Index (HFI) is calculated using the Human Development Index (HDI) calculation method and adding an index under the title Crime Index (CI). Accordingly, in this study, 30 selected countries in the form of two groups of in the mentioned indicators are examined. The countries of the first group are in the list of countries with the best education system, and the countries of the second group are not in this list. In the first group, there is no significant gap between the two charts, HDI and HFI, and they have a similar trend. The CI chart also shows the low level of crime and risky behaviors and confirms the higher level of non-cognitive and personality skills in this group of countries. In the second country group, due to higher CI than the first country group, the HDI graph is higher than the HFI graph. Both charts have a similar trend but have a greater downward slope than the first group. The CI chart is also for the second group, with a steeper slope than the first group. Thus, the first group of countries has a higher capacity to meet their self-fulfillment needs due to the high quality of the education system and more attention to cultivating a wide range of skills. As we move to countries with lower quality education systems, this capacity decreases.

This article considers the effect of fiscal policy on inclusive development. Inclusive development is one of the concepts that has been introduced in the development economics literature in the last decade and especially with emphasis on the social and political aspects of development, the distribution of development achievements among different sections of society is in focus. Since fiscal policies are one of the main instruments of the government to eliminate deprivation and imbalances, it is important to understand the effectiveness of these policies in this regard. In this study, the components of fiscal policy include the combination of expenditures and revenues and its effect on inclusive development in the period 1981-2018 in the form of two models of structural vector auto-regression has been studied. Findings show that most components of government fiscal policy except economic expenditures do not have a significant effect on the index of inclusive development and these economic expenditures have a negative impact on inclusive development. The results show that the government's fiscal policies have failed to achieve or accelerate inclusive development, and despite its legal mission, the government has not been successful in comprehensive expanding welfare and extending it to all social groups. Historical analysis also shows that since the beginning of the 2010s and with the intensification of sanctions and currency fluctuations, the relationship between fiscal policy and the index of inclusive development has been weakened. It seems that the reform of the budgeting process and the simultaneous attention to the two constraints of equality and sustainability in growth and development targeting for fiscal policy on inclusive development is essential.

Due to the importance of balancing internal and external of the economy, research on the interaction effects of the budget deficit, savings gap, and current account deficit has always been a major issue for policymakers. The main purpose of this study was to test the validity of the triple deficit hypothesis during the period 1978-2019 in the Iranian economy with the presence of the degree of trade openness for two models of oil trade and without oil trade. In the present paper, by providing a theoretical framework and using the Johansen - Juselius cointegration test method and the error correction mechanism, long-term and short-term relationships of the variables of this research are investigated. The results showed that the long-run relationship among the components of the triple deficit hypothesis is established in the two models of oil trade and without oil trade, but the validity of the triple deficit hypothesis is not confirmed in the short run. Through the Impulse response functions, decisions were made about the interrelationships among the variables, and the results of this method confirmed the validity of the triple deficit hypothesis for the oil trade model and the occurrence of the inverse mechanism for the oil-free trade model. Finally, in the oil trade model, internal and external imbalances reduced trade openness, and in the non-oil trade model, only the savings gap played such a role. This emphasized the key role of the private sector in reducing internal and external imbalances.

Acquiring information about expectations is difficult as individuals' beliefs are unobservable. Thus, how expectation forms and how to model expectation is an open question in economic modelling that has been addressed recently by experimental economics. In this article, in order to identify expectations, we examine the behaviour of subjects when encountering new exchange rates in an experiment. Furthermore, in this experiment, differences of expectation formation among participants and their relation to cognitive abilities are analysed. To motivate people, incentive payments are used. In our setting, while the rational expectation hypothesis is not supported, the adaptive expectation is not rejected. Agents form their expectations in the same way regardless of their cognitive ability. In this context, individuals overreact to the new quantity of exchange rate which is assumed as a noisy perception. This finding is considered as evidence of emotional behaviours in the exchange market.

In long-term gas contracts, there is usually a risk for the seller that the buyer will refuse to take delivery. For this reason, the condition of obligation to take or pay in such contracts has become common. Commitment condition is a condition that obliges the buyer in the gas sales contract to pay the seller a part of the contract price, which is determined as a percentage of the total amount, even if he does not receive the agreed gas volume. The research question is whether this condition has economic efficiency? Will a long-term balance between buyer and seller be an option for this condition in the contract or not? To answer these question, first, with the concept of evolutionary game theory, we have shown a picture of contracts before the existence of this condition and after its formation. Then, by setting the normal form of the game and using Python software, we have repeated this game thousand times, the results show that accepting the condition of commitment to take or pay will be stable evolutionary equilibrium. From this perspective, the inclusion of such a condition in the contract creates economic efficiency, and the policy recommendation in this regard would be for policy makers to prefer a lower definite income to a higher probable income by including such a condition.

Urban planning typically involves technical and political procedures of developing and designing land use and determining urban boundaries. However, similar to other government interventions, urban planning creates rents for some urban lands while causing losses to other lands. To gain the maximum profit, land developers prefer to develop lands that have acquired higher privileges, i.e., more extensive construction permits. It will make cities' development patterns unbalanced in favor of land with more accumulated planning rents. The transfer of development rights (TDR) is a market approach to designing urban development that balances. It evenly distributes the benefits and disadvantages of urban planning, especially in protecting historic buildings and agricultural and garden lands. This paper simulates the application of TDR as an alternative urban planning way to cope with the unbalanced development of urban lands in Tehran. We utilized an urban dataset from 2007 to 2019 and evaluated the efficiency of TDR using Agent-Based Modeling (ABM). Results implied that the usage of the TDR would improve the distribution of investment in Tehran in a more balanced pattern. However, more studies, especially considering the regional differences in the city and expansion of the model for other for-profit or non-profit usages such as urban gardens, make it imperative to use.

"Corporate governance" includes mechanisms to monitor CEO's performance to assure efficient decision adoption and maximize firm value. One of the most effective aspects of firm performance is the degree of risk-taking. This study investigates the relationship between CEO power and institutional ownership with risk-taking behavior of member firms of Tehran Stock Exchange and Iran Fara Bourse during 2010-2019 by utilizing quintile regression. According to the results, by the increase of CEO's power and the company's benefit from powerful managers, the company risk (total risk and systemic risk) will decrease. As a result, managers are eager to safeguard their reputation as expert decision-makers and, as a result, they try to reduce company risk. In addition, the existence of institutional ownership among the shareholders of the company will reduce the risk, which can be referred to in the agency theory. Also, if the impact of these two variables is considered together, the risk will increase significantly. This very fact reflects the exercise of the power and influence of institutional owners. As a result, large shareholders have a supervisory role in the discipline of managers, but despite their impact on the relationship between managers' power and corporate risk, they do not alter the main negative relationship.

One of the characteristics of the financial market, especially the stock market, is the effects of behavioral factors and on other financial and non-financial markets. There are several factors that affect the return of a stock exchange. We can refer to political, socio-cultural, technological and finally economic factors. A stock market is an economic market in which securities are traded under specific rules and regulations. Accordingly, in this study, the effect of behavioral financial arguments and other financial markets on stock market returns based on quantitative analysis has been studied. This article tries to examine how exchange rates, gold, and oil as key factors of a model can explain fluctuations of the stock market index. so the effect of those variables on the stock market index in the period 2008 to the first six months of 2018 has been analyzed using the FIAPGARCH-X model. The results of the analysis show that the effect of exchange rates on the stock market fluctuations is greater than the other two factors. The results also indicate that there are asymmetric effects of increased returns on the stock market, which is consistent with behavioral bias in behavioral finance.

The tremendous advances in artificial intelligence over the past decade have led to their increasing use in financial markets. In recent years a large number of investment companies and hedge funds have been implementing algorithmic and automated trading on their trading. The speed of decision-making and execution is the most important factor in the success of institutional and individual investors in capital markets. Algorithmic trading using machine learning methods has been able to improve the performance of investors by finding investment opportunities as well as time entry and exit of trading. The purpose of this study is to achieve a better portfolio performance by designing an intelligent and fully automated trading system that investors with the support of this system, in addition to finding the best opportunities in the market, can allocate resources optimally. The present study consists of four separate steps. Respectively, tuning the parameters of technical indicators, detecting the current market regime (trending or non-trending), issuing a definite signal (buy, sell or hold) from the indicators’ signals and finally portfolio rebalancing. These 4 steps respectively are performed using genetic algorithm, fuzzy logic, artificial neural network and conventional portfolio optimization model. The results show the complete superiority of the proposed model in achieving higher returns and less risk compared to the performance of the TEDPIX and other mutual funds in the same period.

The present study aimed to identify the most effective causes of conflict of interest by examination of accounting literature and expert consensus. Understanding these factors, using cognitive psychology theories, can lead to a model for reducing conflict of interests. The dignity of the audit profession depends on fair and proper professional judgment by auditors, and achieving this requires identification and controlling of the key factors affecting judgment and decision-making. When auditors intentionally or unintentionally accredit financial statements in line with the opinion of their employers, public interests and the auditing profession are at serious risk. Several factors that can categorize into seven categories of structure, community, culture, environment, personality, audit firm characteristic, and ethics and behavior are rooted in a conflict of interests. However, no comprehensive research examining all the above factors and identifying the most effective ones has been done so far. By reviewing the research literature, major and minor factors were identified in domestic and foreign sources. Ten expert auditors were selected by the snowball method and interviewed. The considered major and minor factors were selected from among the introduced factors, and a questionnaire was sent to the experts using the Fuzzy Delphi (Screening) method. The results of the above statistical analysis identified eighteen of the most prominent sub-criteria of the factors affecting conflict of interests and identified structural factors the highest rank in this classification, which was agreed by the experts.

The management control system provides valuable information on the managers' needs at different levels of the organization. Today, with changes in the political, social and economic dimensions, the management control system in the public sector also needs to be changed and adapted to new conditions and use new tools to meet stakeholders’ needs. The purpose of this study is to provide a model to investigate the role of the management control system and increase accountability in the public sector administrations and companies. In this regard, the present study explores the role of functions of management accounting in improving the management control system in the public sector. For this purpose, data were collected through interviewing 13 experts in the field of the management control system and functions of management accounting and reviewing related texts, articles and books in this field, and their content was analyzed through grounded theory and content analysis method and MAXQDA 2021 software was used for data analysis in 1399. The findings of this study showed that a management control system, if it has the necessary tools, can play a key role in preventing corruption, increasing transparency and accountability, performance-based budgeting, and performance-based auditing. The existence of a management control system is necessary for any organization; such a system will help identify resource flow, help management in decision making, motivate employees, make decisions related to outsourcing and contracting, reduce service delivery time, and many other issues in organizations, and it will ultimately lead to optimally allocate resources, prevent corruption, and increase legitimacy, transparency and accountability, Therefore, the optimal use of management accounting in the management control system, improves the achievement of organizational goals and the effectiveness of programs

Researchers examined anomalies in the market to understand the market dimensions. Prior studies considered the effects of biases on momentum strategy. Stock liquidity as one of the risk factors for assets was also considered by researchers. The purpose of this study is to examine the role of stock liquidity in the separately and jointly effect of anchoring bias and the disposition effect on momentum profit. The population of this study consists of all companies listed on the Tehran Stock Exchange. Based on systematic election sampling this study covers 136 companies over the period of 2007-2020. In this study, the effect of disposition effect is calculated using the approach of Greenblatt and Han (2005) and Frazzini (2006) and the anchorage bias is calculated according to George and Hwang (2004). This study calculates momentum profits according to Jegadeesh and Titman (1993). To test the hypotheses, multivariate regressions and the five-factor model of Fama and French (2015) have been used. The results of this study show that the disposition effect in stocks with low liquidity increases momentum profit. In addition, anchoring bias in stocks with low liquidity leads to an increase the momentum profit. Findings of this study document that the interaction effect of anchoring bias and disposition effect, while reinforcing each other, is also associated with increasing in momentum profit. Finally, when anchoring bias and disposition effect reinforce each other, and stocks have low liquidity, they do not increase momentum profits.

In the present study, the competitiveness of Iran's agricultural, industrial and in global markets services sectors has been investigated and analyzed. This measurement was taken by calculating four indicators of relative comparative advantage (RCA) at the level of two- and four-digit codes of the International Industrial Standard Classification System for Economic Activities (ISIC) and using the data of Iran-world input-output tables during the period 1996-1995. The results show that out of 3 main subgroups of agriculture, only subdivisions of agricultural products, horticulture, livestock and poultry and hunting and other related activities, and out of 19 subdivisions of industry, only subdivisions of mineral extraction and other related materials, have RCA in all studied years. Other subsections have fluctuations in the presence or absence of comparative advantage, and some have a distinct RCA pattern. This situation has existed in 10 service sub-sectors of the country, but in general, the relative export advantage for service sub-sectors has not been identified in the whole period. In addition, the results of RCA index compatibility tests by performing 3 Cardinal, Ordinal and Dichotomous Measures show that the results of Ordinal tests are more satisfactory than the results of Dichotomous and Cardinal tests and therefore, the present study provides an Ordinal interpretation of RCA indicators in the formation of economic policies. Finally, the results of stability tests show that the indicators of comparative export advantage did not have a stable trend during the period.

The expansion of the globalization process has increased the relationships among financial markets in different countries, which itself has motivated investors to move among them to make more profit. Given the situation in Iran after sanctions, the possibility of investing in well-known financial markets is facing with the risk of sanctions. The present study aims to evaluate the existence of volatility spillover among the financial markets of Iran and Islamic oil exporters countries. To this aim, a multivariate factor stochastic volatility (SV) model and stock price index data were used with daily frequency for the period 12/05/2008-02/19/2020. Based on the results, the main hypothesis that the volatility spillover among the financial markets of OPEC oil-exporting Islamic countries follows a common and uniform random trend is accepted for the United Arab Emirates, Saudi Arabia, and Qatar, but not for Iran and Nigeria. Therefore, diversifying the portfolio for Iranian investors in the financial markets of OPEC Islamic oil exporters can reduce the investment risk in the long run which make such economies an appropriate investment destination for Iranians due to the conditions of sanctions.

The experience of some countries indicates that export has been an important factor in economic growth and its sustainability. Cost advantage, knowledge and innovation are the factors that affect export. Cost advantage in turn depends on various factors such as learning by doing. Learning leads to the expansion of international trade and economic growth by reducing production costs and creating a competitive advantage. The main purpose of this paper is to evaluate learning by doing and investigating its impact on industrial exports at four-digit ISIC codes level during 2011 to 2015. For this purpose, three different indicators have been operationalized to quantify learning and three export supply models have been estimated using panel data technique. Obtained results indicate that in all three models, learning by doing has a positive and significant effect on export supply. In other words, the effect of learning on exports is not sensitive to the way of offering operational definition. Also, the variables of trade openness, research and development costs and human capital all have positive and significant effects on the export of four-digit ISIC code industries.