نشریه اقتصاد مالی
پیاپی 66 (بهار 1403)

The development of financial markets and the stock market play an essential role in economic development. Considering that financial markets are always associated with risk and uncertainty, and shocks and turbulence in one market affect other markets, therefore, one of the main objectives of this research is to identify the type of distribution of financial series (stock returns of different industries) and estimate their uncertainty and risk (turbulence), determining the weight of stocks in the investment portfolio, as well as accurately identifying how the volatility changes and the intensity of correlation and interactions between the stocks of different industries over time in order to maximize the interests of investors and provide the necessary solutions to planners and policy makers Investors are for managing and developing the stock market.In order to optimize, statistics related to the weekly price index data of  selected industries (mass housing, banks and credit institutions, chemical, automotive, pharmaceutical and basic metals) have been used. For this purpose, using orthogonal GARCH model and weekly data of stock price index of different industries in the period March 27, 2010 and January 18, 2021, the elements of the variance-conditional covariance matrix were estimated, Then, the stock portfolio was optimized using the obtained information and the distribution of general hyperbolic (GH) skewed t, in the framework of the static and dynamic classical Mean-Variance model as well as the static Mean-CVAR model. The results of fitting (estimation) of the data distribution show that the return distribution of the price index of the studied industries follows the distribution of the general hyperbolic skewed t; Based on the dynamic classical mean-variance model, the highest weight in the stock portfolio in the study period was related to the pharmaceutical (0/6336) and chemical industries (0/3539), respectively.

In recent years, the support of corporate governance has attracted the attention of capital market regulatory bodies, including the stock exchange. In this regard, the corporate governance index has been taken into consideration as a monitoring tool for companies so that companies that better comply with corporate governance mechanisms can be distinguished from companies that do not comply with these mechanisms. On this basis, companies should try to improve these mechanisms and take more effective steps to create more efficiency and value and thus improve the conditions of the capital market. In this research, an attempt is made to use a new index under the title of fuzzy corporate governance index, and according to expert opinion and formulation of fuzzy inference rules, three fuzzy expert systems have been designed to evaluate corporate governance criteria. Also, the data related to 160 companies admitted to the Tehran Stock Exchange as a sample have been collected and their data has been processed using the aforementioned fuzzy systems. The output of the first system shows the quality of the ownership index and transparency in the sample companies. The output of the second system shows the quality of the board structure index and finally the output of the third system shows the quality of corporate governance in the mentioned companies. The results of these evaluations are shown in a list of the weakest and best companies in terms of ownership and transparency, the structure of the board of directors, and the quality of corporate governance.

One of the basic dimensions in the discussion of financial instability is the volatility of asset prices. The reason for the change in asset prices is not only the policies of the central bank, but examining its impact interprets an important part of its changes.
In this research, based on the method of Bayesian averaging and principal component analysis, the monetary policy index effective on the stock price has been determined and through the TVP-FAVAR model, the effect of this variable on the stock price has been investigated in MATLAB software.
According to the results, the changes of one standard deviation in the monetary policy index over time on stock prices have been U-shaped. Changes of one standard deviation in the monetary policy index had a positive and strong impact on stock prices in the beginning to the end of the period.

As the managers due to decision-making and stakeholders, namely investors, tend to predict the occurrence or non-occurrence of financial crisis in the organization under their management, so the present study is aimed to provide a model for predicting this crisis. To achieve the research purpose, smart web models including grey wolf, ant colony optimization, particle swarm optimization and genetics algorithms were used. For this purpose, the data obtained from the questionnaire completed by 20 experts in the quality section and the data obtained from 173 companies from 2009 to 2019 listed in the Tehran Stock Exchange (TSE) were used. 38 indices from the categories of macroeconomic indicators, industry factors, corporate characteristics, political, cultural and behavioral events were identified using the review of the theoretical basics. Then, 25 indicators with high impact on the financial crisis were selected using expert opinion and MICMAC analysis. Then, by reviewing the financial statements of 173 companies listed on the Tehran Stock Exchange (TSE) and using Rahavard Novin software, the data were collected from 25 selected indicators and their impact on the financial crisis was examined using gray wolf, ant colony, particle swarm and genetics algorithm to determine the final model of the research. It was found that in terms of efficiency, the ant colony optimization method is the most efficient and the gray wolf method is the least efficient in predicting the financial crisis.

The main purpose of this research is to examine the relationship between assets growth, profit continuity, profit management and investment opportunities with profit sharing and company value among companies listed on the Tehran Stock Exchange. The statistical sample of the research  includes 113 active companies in the Tehran Stock Exchange during the period from 2015 to 2019. Structural equation modeling (SEM) based on partial least squares (PLS) was used for statistical analysis. The findings of this study showed that assets growth, profit continuity, investment opportunities and profit management have an effect on dividends. There is also a significant relationship between earnings management and dividends. Finally, the distributed profit, assets growth, and the continuity of profit affect the company's performance. Finally, the distributed profit, the growth of assets, and the continuity of profit affect the company's performance. Finally, the distributed profit, profit growth, and the continuity of profit affect the company's performance. When investors determine the value of the company in terms of accounting data, it is necessary to consider the growth rate of assets. When the company does not have a shortage of available cash, the manager does not face a serious problem in allocating resources between investment opportunities and profit distribution. The growth of assets creates value for a company. Managers mostly proceed with profit continuation; Because the amount of profit and its fluctuation is important from the point of view of the company's shareholders and it affects the value of the company. Using investment opportunities and adopting favorable debt and profit sharing policies, which are among the tools of financial decisions, can improve the position of the company.

One of the popular but complicated methods in technical analysis is the Elliott wave method. In this method, the most important part is to recognize the main trend patterns of the market, which is a difficult task due to the fractal structure of the market. But like other fields, the use of artificial intelligence in the field of financial forecasts has also become widespread. Therefore, it seems that the use of artificial intelligence in Elliott wave analysis is attractive. Therefore, in the current research, by introducing a deep learning model to predict the market through the detection of Elliott wave patterns, it has been investigated and compared the power of the model in two modes of binary and multiple classification. In this research, for 15 considered patterns, 1002 examples of stock price charts of companies present in the Iranian stock market in the 11-year period from 1390 to 1400 were collected and labeled, and finally for recognition as input to the deep learning algorithm with Recurrent neural network model was used in binary and multiple classification modes. In this research, RapidMiner 9.9 software was used to design and implement the model, and accuracy criteria were used to determine the power of the model. The results show 18% accuracy in pattern recognition in multiple classification mode and 61% accuracy in binary classification mode. Therefore, the power of the deep learning model in detecting the fractal patterns of Elliott waves and as a result predicting the market trend is significantly higher in the binary classification mode than in the multiple classification mode. Therefore, the present study recommends the use of deep learning model with binary classification to detect fractal patterns of Elliott waves.

In the last few years, the financial condition index has been an important indicator to determine the situation of each country. The Financial Conditions Index can be defined as the current state of the variables that affect the future state of the economy. The Financial Conditions Index is a summary index of financial variables that is effective in predicting the economic situation of a country.
Financial conditions in any country are one of the most important issues in the economy. The purpose of this article is to determine and calculate the financial condition index for Iran using the basic component analysis method and time series data from 1990-2020. The results of calculating the financial condition index show that the credit channel has more weight than other channels and this shows the importance of the volume of credit in estimating the country's financial condition index during this period in the research. After that, the asset channel, ie the stock price index and the housing index, have the most weight. Among these, the exchange rate and interest rate channels have the lowest weight. Therefore, the central bank can adopt a forward-looking approach in monetary policy, so that by changing its retrospective approach in monetary policy decisions, it can show the most correct reaction.

Today, one of the challenges facing health systems is the ever-increasing increase in its costs. This study investigates the relationship between health costs and income inequality. Income inequality has been investigated using four Gini coefficients and, in a quantile, approach using annual panel data from 2000 to 2022 in selected middle-income member countries of the Organization of Islamic Cooperation, the empirical results show that the effect of health costs on inequality The income in the countries that are part of the top 10 percent of the income level in this group is much higher than the countries that are in the lowest income level. The effect of life expectancy, death rate and population on income inequality is also opposite; That is, the countries that are in the highest category in terms of income level, the effect of these variables on income inequality is much greater than the countries that are in the lower income categories. Also, due to the effect of population structure on income inequality, it is necessary to seriously consider it in the design and formulation of policies in the field of health, hygiene and population structure. Health, treatment and quality of life improvement policies to increase life expectancy and decrease mortality rate, policies to increase investment (reduction of consumption, promotion of security, economic development of exports, etc.) should be pursued to reduce income inequality.

Today, the tourism industry is one of the main and stable foundations of the world economy, which can affect other economic and cultural activities by creating the maximum amount of added value. The tourism industry in Khorasan Razavi province can plan and use the province's domestic and foreign investment to develop this sector, grow production, create added value, and increase employment and income sources in the region. The purpose of this study is to investigate the amount of added value created by the main tourism activities of the province (each of the 12 tourism sectors). Another purpose is to analyze the effect of increasing investment on the value-added of the tourism industry. For these purposes, the updated input-output table of Khorasan-Razavi province (2018) has been used. The results were analyzed by considering two scenarios (proportional investment in all economic sectors of the tourism industry together, and investment in each economic sector of the tourism industry separately). The results showed that if investment in all sectors of tourism, increases by 100 billion rials simultaneously -in total equivalent to 1200 billion rials- (as analytical scenarios), 851718 million rials will be added to the value-added of province's economic activities; Of this amount, 95.5% of value-added creation is directly related to the 12 sectors of the tourism industry. The most direct effect of investment in value creation is related to the wholesale and retail sector, the arts, entertainment, recreation sector and Travel agency services sector, respectively. Also, if investment increases by 100 billion rials in each of the tourism sectors separately, maximum direct value-added creation, results from the "arts, entertainment, recreation" sector. The most important suggestions of this study were, Investing in forming groups and institutions in the province to produce, promote and starting various artistic, recreational and sports activities, investing in designing travel packages on specific topics in the field of travel agency services and providing accommodation services based on travellers' tastes.

The main focus of this research is to investigate and explain the role of organizational factors and human resources characteristics in the warning report of auditors of auditing institutions in Iran. The statistical population of the research includes auditors working in audit institutions, members of the public accountants' society and audit organization. Data related to the characteristics of human resources and the variables of organizational factors have been collected using standard questionnaires. Due to the complex nature of standard questionnaires used, a multi-level structural equation model is used to analyze the collected data. The first and second levels of the model are used to confirm the validity and reliability of the research variables. The third level of the model, which explains the relationship between research variables, has been used to test the research hypotheses. The results of the research showed that the free-spirited leadership style is an important organizational factor promoting the warning report in the audit profession in Iran's official audit institutions. Also, managing age in human resource leads to the improvement of transparency of reporting and, in turn, prompts timely warning reporting among auditors in accordance with principles, procedures and legal criteria as a voluntary act.

Capital market anomalies are caused by factors that have not been considered in capital asset pricing models. One of the arguments for explaining anomalies is the theory of extreme value. According to the theory of extreme value, tail risk is an adverse event that can have a negative impact on excess stock returns. Therefore, the aim of the present study was to investigate the effect of combining momentum anomalies and idiosyncratic risk with tail risk on excess stock returns. In the present study, two criteria of cumulative tail risk and combined covariance tail risk have been used to calculate tail risk. The sampling method in this study is systematic elimination and the time period of the research years from 2007 to 2019 has been selected. The number of sample companies includes 136 companies listed on the Tehran Stock Exchange (TSE) and the 5-factor regression of Fama and French was used to test the research hypotheses. The results indicate that the combination of idiosyncratic risk portfolio and tail risk has a positive and significant effect on excess stock returns. Therefore, by combining this portfolio, investors can gain returns in the Iranian capital market. Also, the results showed that the combination of momentum portfolio and tail risk does not lead to excess stock returns. In general, the results showed that tail risk can be used to explain the existence of idiosyncratic risk anomalies.

Digital currency, is one of the most important factors in the success of organizations that will be present in the arena of global competition. In the present review, the most important theories of digital currency forecasting based on fuzzy hybrid models and artificial neural networks have been systematically investigated. These models mainly focus on supervised methods for measuring hybrid models. Also, basic concepts about the history of hybrid models from the first proposed models to current developed models, their combinations and architectural capabilities, data processing and measurement methods of these intelligent models are presented so that evolution This category of intelligent systems is analyzed. Finally, the features of prominent (leading) models and their applications in digital currency forecasting are presented. The results show that fuzzy neural network models and their derivatives are efficient in predicting digital currency with very high accuracy and with good justification capability that is used in a wide range of economic and scientific fields.

One of the basic strategies in supporting Iranian labor and capital is to pay attention to foreign investment. Obviously, foreign investment can lead to the transfer of technology and technical knowledge, improve management and marketing methods, training and education of human resources, easier access to export markets, and so on. so; The main purpose of this article was to investigate the behavioral factors affecting the decisions of foreign investors in Iran in both econometric and qualitative sections. In this article, data in the econometrics section were collected annually in the period of 1372 to 1400, and in the qualitative section, a questionnaire (researcher-made) field method was used to collect information and data. To determine the validity of the questionnaire and test, experts were consulted and the questionnaire in terms of validity (validity) was approved by obtaining the opinion of the respected supervisor. On the other hand, some questions lacking the necessary characteristics were removed and some ambiguous questions were corrected, which indicates the formal validity of those questions in the questionnaire. Then, in this study, content validity ratio was used to examine the validity of the questions. The results of the analysis based on the AR model indicate that an increase in foreign direct investment (FDI) in the previous period will increase foreign direct investment (FDI) by investors from the country, the reason for this should be sought in behavioral economics. The results obtained from the analysis of t-test show that the mean behavioral economics variables (risk aversion, herding behavior, social security, conservative mental accounting (bias) and orientation) influence the decisions of foreign direct investors. Is transient and is statistically valid.

This study examines the role of ethical leadership in employee empowerment. In today's world scenario, understanding the impact of flexibility and emotional Exhaustion is essential to building the concept of empowerment. therefore, the present study examines perceived flexibility and emotional Exhaustion as possible modifiers on the relationship between ethical leadership and employee empowerment. This research is a descriptive and survey type. a 30-item questionnaire was designed and distributed in 2021 to collect data and measure variables in order to evaluate the research model. The reliability of the questionnaire was estimated to be higher than 0.7 using Cronbach's alpha method for each part and the validity of the questionnaire was confirmed by structural validity analysis. The authors, while reviewing the theoretical foundations of the members of the statistical sample, selected them by random sampling method from among the managers of the presidential Administration of Iran in Tehran. Confirmatory factor analysis and regression analysis were performed using Smart PLS software to test the research hypotheses and examine the differences between the structures in the research. Findings showed that ethical leadership has a significant effect on psychological and structural empowerment. Also, the moderating effects of Emotional Exhaustion and Perceived Flexibility on the relationship between ethical leadership and empowerment was significant and the research hypotheses were all confirmed. Given the special characteristics of the Presidential Administration and their emphasis on ethics in order to achieve organizational perfection, the results of this study can be used by other governmental institutions.

Investment is one of the main component of aggregate demand in economy which plays a crucial role in the economic fluctuations and economic growth of each country So economist and policymakers focused on interpret of Investment behavior.  One of the most important factors in the decision to invest in both domestic and foreign investment is the existence of a secure environment. in other words, the most important factors is the proper investment environment and what has been interpreted as the ease of doing business. In such a way that improving the ranking of countries in business environment indicators is one of the prerequisites for attracting domestic and foreign capital and as a result investment. The main goal of this study is to investigate the effect of indicators of ease of doing business and domestic investment on foreign direct investment in selected countries. For this purpose, based on the division of the World Bank, four groups of countries are considered by their income level, including low-income countries, lower middle-income countries, upper middle-income countries and high-income countries, and the effect of domestic investment and indicators of ease of doing business have been evaluated using a Panel data model. The result shows that the level of development of countries and their income influences the magnitude and effect of domestic private investment and indicators ease of doing business on FDI. In a low-income, lower middle income and high-income countries, the effect of investment on foreign direct investment is positive, and in the upper middle countries, this has a negative effect. Meanwhile, the effect of each indicator of ease of doing business on foreign investment varies depending on the income level of countries.

Considering the current economic conditions of the country, the number of helpless companies and the importance of financial helplessness are increasing day by day. The increase in economic factors affecting financial helplessness has also increased the complexity of investment decisions for these companies. For this purpose, the approach presented in this research, taking into account various financial criteria, provides the possibility of dynamic forecasting of Financial Distress for these decision makers. makes The approach introduced in this research is first by clustering the companies in the proportional cluster of financially helpless and non-helpless with the help of artificial neural network method, self-organizing mapping (SOM) and then by using the data envelopment analysis method based on the worst performance (WPF-DEA). A dynamic forecast of the financial helplessness of the companies admitted to the Tehran Bahadur Stock Exchange was carried out. Using the mentioned method, 105 companies were evaluated and the result of the inefficiency of these companies was predicted during 5 time periods from 2015 to 2019. The dynamic data coverage analysis model based on the worst performance has the ability to evaluate the inefficiency of the examined units, including companies that are members of the Stock Exchange and Securities Organization. Data envelopment analysis has been able to successfully identify the financial helplessness of companies as inefficient decision units.

The value of small-vlume transactions stock (shares + preemptive rights + shares ETF) is obtained by deducting the value of block transactions from the value of total transactions in the Iranian Stock Exchange. This research includes two main parts. Considering the importance of the Black-Scholes price model in financial mathematics, using deep mathematical tools such as nonlinear analysis, stochastic analysis, Ito's lemma and the Radon-Nikodym derivative, a theoretical mathematical result was obtained regarding the Black-Scholes price model. we found Theorem 1 in chapter (4) is actually a deep theoretical mathematical relationship for predicting the price in the future. Also, the results of this theorem were used to investigate the trend of the value of small stock transactions in the Iranian stock market in the future time frames. The second topic we discuss in this article is to investigate the impact of changes in the value of small-vlume transactions stock on Tedpix of the Iranian stock market, using modeling and mathematical tools, including the Black-Scholes model, financial technical analysis tools, statistical methods and the Hurst test.
Usually, mathematical and computational tools use stock price data to predict the trend of financial markets. Also, the number of traded shares of a stock company can be an indicator to identify the entry point for buying or the exit point for selling. Considering the extreme price fluctuations in the last few years in the Iranian stock market and the difficulty of setting a ceiling for the price, as well as the existence of processes such as capital increases in company assemblies that change the total number of tradable shares of a company, the importance of using data on the value of small stock transactions It is revealed as a combination of price and number of shares data.
In this study, in a period of about seventeen months (in which the most severe fluctuations in the history of the Iranian Stock Exchange occurred), weekly information on the average value small-volume transactions has been examined. The results of this research confirm that with the increase or decrease of the total index of the Iranian stock market, we see a similar trend in the value small-volume transactions. We also showed that the value of small stock trades is trending by using the Hurst test.

Today, heavy competition in the petrochemical industry among countries requires that attention to the brand issue be given priority, especially companies related to the petrochemical industry in Iran due to the sanctions issues, can move by creating a strong industrial brand to protect their customers. In the present research, the design of the brand performance model in the petrochemical industry was discussed.

The research was conducted in a mixed method. The statistical population of the research included sales and marketing experts of 7 petrochemical companies, and 7 experts from these companies and 238 sales and marketing experts were considered as members of the statistical sample. By conducting interviews with brand experts in the petrochemical industry, as well as library studies, concepts and basic components of brand performance were identified. Among the 28 components identified from library studies, 11 components were identified in the expert analysis as components of the brand performance model, which were the basis of the analysis.

The results of the confirmatory factor analysis showed that among the 11 components mentioned, only 7 components significantly explain the performance of the brand. These 7 components are: sales efficiency, innovation in response, modeling, brand-oriented organizational capital, organizational competitive strategies, product quality, production and sales volume. Also, the results showed that the performance of the brand in the petrochemical industry is not in a favorable state in terms of innovation in customer response and production and sales volume.

One of the consequences of improving the performance of the brand in this industry, according to the research model, can be mentioned the improvement of the quality level of the products, meeting the market expectations, increasing the commitment and loyalty of customers, favorable financial performance and the development and prosperity of the industry.

With the start of the First World War and the entry of the Ottomans into the battlefield, the scope of the war was also extended to Kurdistan. The presence of the armies of the warring governments in Kurdistan, the personal interests of the local rulers by hoarding grains caused a grain the crisis in Kurdistan and social consequences such as poverty, hunger, corruption, prostitution, in the migration of people from cities and the destruction of villages followed.

Research method/approach: 

The current research is based on historical sources, such as books, documents and press, using a descriptive-analytical approach.

To investigate the grain hoarding and crisis in Kurdistan, the activities and performance of local rulers in the First World War.

The presence of the forces involved in the First World War in Kurdistan has disturbed the economic order of the region, the provision of food for these forces from local products, the decrease in the essential food of the people, as well as the hoarding of grains by the owners, the negative and inappropriate performance of the local rulers, and in addition to the problems and the many problems caused by the military forces involved in the war in the Kurdistan region due to their own benefit and the survival of their power have become a factor for increasing the economic and social damage of the region and finally led to hoarding and grain crisis in Kurdistan and caused poverty, hunger, famine and other unfortunate repercussions in Kurdistan.

The present study examines the quantitative effects of uncertainty regarding government expenditure policy (current and construction expenditures) on Iran's economic activity. Uncertainty is a situation where future events or their probability of occurrence are not predicted. In the real world, the economy is full of uncertainty of economic factors, which leads to risk and danger in the decision-making space of economic factors and affects their behavior. In this article, we intend to use the structural vector autoregression model (SVAR), which are known as impulse models; Uncertainty effects created by the government's current expenditures and construction expenditures and other effective indicators such as; Measure the impact of oil prices and financial crises on economic activities such as production and employment. The data of the study was collected from the Central Bank website and the model was estimated using Eviuse software for the years 1365-1399. The findings showed that an impulse from the oil price area causes a 5% increase in production and a 1% increase in employment, also an impulse from the financial crisis area causes a 3% decrease in production and a 12% decrease in employment, respectively. The impulse from the area of uncertainty of current and construction expenses, causes a decrease in order; 12 percent is produced and 7 and 5 percent is employed.