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The certainty about retirement income is dependent on the longevity and the selected investment policy by individuals during their working years. Attention to longevity and investment risks is of high significance in making enough income for retirees. In this research, the impact of the objective formulation selection on investment decisions has been investigated. Two functions including terminal wealth objective formulation and retirement income objective formulation are applied to investigate these decisions. Based on the investment alternatives, 5 asset classes including Equity, Certificate of deposit (cash), real estate investment trust (REIT), gold coin, and foreign exchange have been selected for investment. According to the complexity of modeling in the aforementioned functions, the Metaheuristic Genetic algorithm has been used. The results are indicative of the importance of objective formulation selection. The retirement income objective function has the nature of more wealth accumulation and more control over economic and market turbulences through higher cooperation in investment and as a result, it has been recommended as the optimal function.

Protecting the interests of shareholders is considered one of the main pillars of any capital market, which, while increasing the level of financial transparency, prevents the loss of their interests to those in power in companies. Consistency of laws and regulations on the one hand and the effectiveness of the corporate governance system in supervising the financial and legal operations of the company is considered important factor in respecting contracts and supporting the investments of minority and majority shareholders of companies, which makes investors confident in protecting their investments. Governance structural keywords in the corporate governance system can lead to Investor Protection by arranging effective board oversight mechanisms and motivating investors to have confidence in the structures of capital market companies. The purpose of this study is to interpret Investor Protection under the existence of a Governance Civilization based on interpretive prioritization analysis. In this study, theoretical screening based on similar studies was used to identify the components (Investor Protection) and research propositions (themes of corporate governance civilization). Then, in order to determine the reliability of research components and propositions through the participation of 14 experts and experts in the field of accounting and financial management, Delphi analysis was used. In the quantitative part, the components and propositions identified in the form of matrix questionnaires were evaluated by interpretive analysis by 20 managers of the top 50 companies of the Tehran Stock Exchange in 2009. The results showed that the proposition of sociocracy is considered the most influential theme of corporate governance civilization in capital market companies, which strengthens the effectiveness of internal control as a component of protecting the interests of shareholders. This result shows that the theme of sociocracy enables corporate governance mechanisms by promoting the level of sharing and participatory discourses to increase the effectiveness of board oversight, strengthen the weaknesses of internal controls to enhance the effectiveness of control over financial performance, and enrich the capacity to build trust and confidence in the performance of companies.

Examining the importance and influence of financial market companies is one of the main issues in the field of financial management because sometimes the collapse of a stock exchange company can affect an entire financial market. One systematic way to analyze the significance and impacts of companies is to use complex networks based on Interaction Graphs (IGs). There are different methods for quantifying the edge weight in an IG. In this method, the graph vertices represent the stock exchange companies that are connected by weighted edges (corresponding to the extent to which they relate to each other). In this paper, using the GARCH model (1,1) and the Clayton copula, we obtained the lower tail dependence interaction network of the first 52 companies of the Tehran Stock Exchange in terms of average market value, between June 2017 and October 2020. Then, based on the minimum spanning tree of the interaction network, we divided the companies into different communities. Using this classification, it was observed that the companies of the first group (Food Industry) and the second group (Oil Refinery) have the greatest impact on other companies. We also calculated the central indexes of the minimum spanning tree for each company. According to the results, the companies of the third group (Steel) have the highest average in the central indicators.

The purpose of this paper is to investigate the role of managerial ability in information environment quality in the listed companies on the Tehran Stock Exchange (TSE). This research has focused on the quality of the information environment and has attempted to investigate the impact of management ability along with other variables affecting the information environment quality such as size, performance, accrual quality, etc. In this study, to measure the quality of a company's information environment "ratio of stock return volatility to market return volatility " and to measure managerial ability The Demerjian et. al. (2012) model is used. The systematic elimination method was used for sampling 105 firms listed in Tehran Stock Exchange during the time range 2015 to 2021, and the model of panel data was applied to test hypotheses. Based on the research results while managerial ability can enhance the quality of a company's information environment, the size and growth rate of the company can also affect the information environment quality.

The purpose of this study was to investigate the effect of peripheral uncertainty on the relationship between the herd behavior of investors and the price of negative stock shock. Because the capital market is one of the main pillars of the country's economic growth and development, the incidence of any disturbance and deviation in prices causes problems with allocating and equipping funds. Reducing stock prices is an example of the disorders created in the capital market. On the other hand, one of the factors that lead to the fluctuations of return and instability of financial markets is the herd behavior of investors. If investors lack sufficient information about environmental factors, environmental uncertainty occurs. Such a situation also affects the organization. Environmental uncertainty overshadowed the use of financial statements. Changes in stock prices and corporate status are cases that can not speak in full confidence in their occurrence. As a result, environmental uncertainty is part of the economic environment. To test the research hypotheses, 156 companies from the Tehran Stock Exchange during the years 2010 to 2020 were selected by screening method. To test the hypotheses, multivariate regression models were performed using STATA14 software. The results indicate that herd behavior has a significant effect on price shock and environmental uncertainty has no effect on the relationship between the two.

Judgment in the auditing profession as a subjective criterion in the decisions of auditors has a significant role in improving the quality of decision support for analysts, shareholders, and investors in the capital market. Therefore, recognizing the qualitative characteristics in this area can help the theoretical development of improving the quality of auditors' professional judgments. The purpose of this study is to develop the effectiveness of auditing professional judgment based on the mindset of auditors. In this study, to identify the components (auditing professional judgment) and research propositions (themes of auditors' mindfulness), meta-synthesis analysis was used with the participation of 12 experts and experts in the field of accounting and financial management at the university level. In the quantitative part, the identified components and propositions in the form of matrix questionnaires were evaluated by interpretive analysis by 18 auditors with work experience and a level of technical and specialized knowledge. The results showed that the statement of inferential mindfulness is the most influential theme of intuitive judgment in auditing, which can cause auditors to perform more effectively in professional judgment. This result suggests that inferential mindfulness is a factor in intuition in professional judgment.

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.

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.

"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 this study, we examine the correlation between stock returns of Export-oriented (EOIs) and Import-oriented (IOIs) industries and exchange rates, to derive stock-exchange optimal weights, attempting to manage the risk of investors in the capital market. To do so, the ADCC and DCC models are used. The data consists of the stock return of the listed industries, and the daily exchange rate from 2008 to 2020. The results suggest that EOIs have a dynamic asymmetric conditional correlation, and IOIs have a dynamic symmetric conditional correlation with the exchange rate. Moreover, the results indicate that in both currency crises, the weight of optimal portfolio in all industries except pharmaceuticals, in non-crisis period is over 50% and in the crisis period is less than 50%. Accordingly, and to reduce the risk of the portfolio, in the non-crisis period, investors should invest more than half of a one-Rial portfolio to dollar exchange, and in the crisis period, they should allocate less than half of a one-Rial portfolio to this currency. In case of the currency crisis, it is suggested that investors invest in the stock of basic metals, because this industry is a pioneer in attracting currency crisis and increasing stock value of the industry through future cash flow and replacement value, and reduce the stock of pharmaceuticals and computers in their portfolio, due to attracting negative effects of the exchange market.

One of the essential factors that lead to severe disruptions in financial markets is price bubbles and subsequent crashes. Numerous models for detecting bubbles have been developed, one of which (LPPLS) has lately attracted considerable interest. This study aims to utilize this model to detect price bubbles in Tehran Stock Exchange's index (TEDPIX). Confidence multi-scale indicators for this model are presented by fitting the LPPLS model to the data of the TSE index from 2009 through 2020. The bubble is detected when the number of fits that are in our filter conditions increases which means the growth of the indicator's value. By applying this method on TSE data two significant crashes in 2013 and 2020 are detected. The proposed technique can be useful for market participants to detect financial crashes and bubbles.

Risk parity is perceived as one of the stock portfolio selection models that have received a lot of attention since the US financial crisis in 2008. The philosophy of this model is to allocate the same amount of portfolio risk between the constituent assets. In the present study, the combined portfolio selection model of relative robust risk parity is introduced, which uses the worst-case scenario approach on the covariance matrix parameter appearing in the robust risk model in portfolio robustness. According to historical data, several scenarios are considered for the covariance matrix. The objective function value of the hybrid model for each portfolio (feasible point) is the worst result (with most volatility) among the set of scenarios. Finally, the model selects a portfolio for which the worst possible result has the least relative volatility. The research portfolio consists of 8 industries from Tehran Stock Exchange in the period 2011 to 2020. This portfolio has a higher Sharpe ratio than conventional models of mean-variance and weight parity, and is more resilient to market declines than the two models and produces less loss. Therefore, risk-averse investors are advised to use this stock portfolio selection model as a cover to face severe market declines.

One of the most critical investment issues faced by different investors is choosing an optimal investment portfolio and balancing risk and return in a way that, maximizes investment returns and minimize the investment risk. So far, many methods have been introduced to form a portfolio, the most famous of the Markowitz approach. The Markowitz mean-variance approach is widely known in the world of finance and, it marks the foundation of every portfolio theory. The mean-variance theory has many practical drawbacks due to the difficulty in estimating the expected return and covariance for different asset classes. In this study, we use the Hierarchical Risk Parity (HRP) machine learning technique and compare the results with the three methods of Minimum Variance (MVP), Uniform Distribution (UNIF), and Risk Parity (RP). To conduct this research, the adjusted price of 50 listed companies of the Tehran Stock Exchange for 2018-07-01 to 2020-09-29 has been used. 70% of the data are considered as in-sample and the remaining 30% as out-of-sample. We evaluate the results using four criteria: Sharp, Maximum Drawdown, Calmer, Sortino. The results show that the MVP and, UNIF approach within the in-sample and, the UNIF and HRP approach out-of-sample have the best performance in sharp measure.

Compared with net earnings, the components of earnings are more informative in companies whose components have different qualities of persistence and volatility. We examine the issue of whether net earnings together with their components have more information content than only net earnings. We construct a model to describe the effect of components volatility and their persistence through disaggregation of earnings value relevance and predictability. The analyses in our study are based on 600 firm-year observations in Tehran Stock Exchange (TSE) for the period 2005- 2019. Data are derived from RAHAVARD NOVIN Iranian software and firms' financial statements. The statistical tests for data analyses are the difference of means test (t-test) and regression analyses. The results of the current study indicate that as the persistence and volatility of selected components of earnings (sales, employee expenses, other selling, general and administrative expenses, and income taxes) increase, earnings disaggregation can improve earnings predictability. Furthermore, when the volatility of employee expenses increases, disaggregated earnings can improve earnings value relevance. As the value relevance of net earnings has been declined over the past decades, the results of the current study suggest that earnings disaggregation plays a major role in improving earnings value relevance and their predictability.

It is necessary for decision-makers to have a rating system in the banking industry in order to reflect the banks' status and performance. Although most institutions across the countries have rating banks and financial institutions, there is a lack of a comprehensive rating system across Iranian banks. Rating requires identifying the appropriate criteria according to the environmental and macroeconomic conditions. For this purpose, 35 components are determined through the opinion of 34 banking and academic experts using the Delphi method and rating is done by the TOPSIS method for 15 banks listed on the Tehran stock exchange over the period of 5 years from 2015 to 2019. The results show that in addition to the quantitative aspects, the qualitative aspects and aspects related to environmental and macro aspects are effective in the native model of banks ratings. Also, there is a positive and significant relationship between banks stock prices variation and the suggested ratings. The obtained results showed that there is a positive and significant correlation between the comprehensive model and early warning system so that the bank's position can be relatively described in the early warning system by identifying it within the model. This evidence addresses the need for a comprehensive consideration of proposed indicators to evaluate and rate banks.

Out of 64 possible catastrophic events in the whole world, about 34 of them have been experienced in Iran; more than 80% of the regions are exposed to natural disasters risks such as earthquakes exposure. Domestic insurance capacity does not cover this volume of risk and the need for external reinsurance capacity is always felt. Catastrophe bonds structure as a financial & insurance innovative solution (Alternative Risk Transfer Instruments) allows an issuing institution to transfer catastrophic exposures and risk to capital market's investors by creating capital relief and additional risk capacity for our insurance industry. We adjusted the formal cat bonds structure with the Islamic jurisprudence. According to the systematic review research method 8 steps, the Sukuk model was implemented based on the extracted concepts from 23 Farsi articles and 50 English articles. After that interviews by 18 experts who were selected by purposive & Snowball sampling, The Delphi method was used to obtain the opinion of experts and their opinion was modified and implemented in the final model. In the open coding stage, 415 concepts were extracted which were classified into 10 categories and finally presented in 4 Propositions/themes. The trustworthiness and authenticity did base on the four-stage model of Lincoln and Guba and also its complementary step. We finally suggested that the catastrophe bond instrument could be issued in the form of a cat takaful (CT) sukuk contract template, as a solution for transferring catastrophic risks to the Islamic financial market.

A manager’s personality and psychological attributes may influence his or her performance, thereby affecting the quality of financial reporting by companies. On the one hand, today there is an increasing requirement for protecting the interests of investors as providers of investment and the most important group of accounting information and financial report users. The development of audit committees is among the mechanisms expected to be effective in protecting the interests of different groups of accounting information and financial report users. In order to act effectively, an audit committee must be independent. Therefore, the present study aims to examine the role played by the independence of audit committee members as a quality of an audit committee to identify how it may moderate the relationship between managers' narcissism and real earnings management in the firms listed in the Tehran Stock Exchange (TSE) using a statistical sample consisting of 642 observations (year-firm) over the period 2013-2018. The findings obtained through hypothesis testing using statistical analysis of panel data suggest that independence of audit committee members does not moderate the relationship between CEO's narcissism and real earnings management through abnormal cash flow, real earnings management through abnormal production, and real earnings management through abnormal discretionary expenses. Thus, the independence of audit committee members as a moderator cannot moderate the relationship between CEO's narcissism and real earnings management

In this research, the impact of clear rumor declarations on the measurement of abnormal stock returns behavior has been investigated in Tehran Stock Market by means of event research so that to reveal well abnormal stock returns behavior. Following testing 169 clear rumor declarations during the period (2017-2019), Using Spss statistical software version 26 and Eviews version 12, the results of regression analysis and correlation tests indicate that content of clear rumor declarations may affect abnormal stock returns behavior. Confirmation of good rumors has increased the efficiency of abnormal stock returns 10 days after the date of the given declaration and approval of bad rumors has led to reducing the efficiency of abnormal stock returns upon declaration day. Similarly, the results showed that if rumors were disclosed during working hours in Tehran Stock Market they would reduce the efficiency of abnormal stock returns on the same day. After comparing the results of the research, the need to educate and promote the shareholding culture among shareholders is felt more than ever before. They also need to shift their focus from focusing on rumors to principled investing in futures stocks to avoid cross-sectional fluctuations, destructive rumors and other market risks and achieve a good return stock

This work aims to analyze the relationship between stocks in the financial market of the Tehran Stock Exchange embedded in their transfer entropy. In this regard, the behavior of the transfer entropy between indices of 180 corporations of the Tehran Stock Exchange has been studied. Then the footprint of crises of the market has been searched in the trends of the transfer entropy. The result has been compared with the result of the analysis imposed on the stocks included in the Dow Jones industrial index in the stock exchanges of the United States. In order to investigate the financial crisis of the Tehran Stock Exchange, the stock price data of 180 companies in this market that were active in the period from 2008 to 2018 are analyzed. It is observed that the average pairwise transfer entropy of indices in the Dow Jones group declines over the financial crises in the United States. In Iran, despite the United States, the financial crises have not left a footprint in the pairwise transfer entropy over the studied period. Such an observation suggests future studies on the pairwise and possibly collective behaviors of indices in Iran and the United States.

The modeling of strategies for buying and selling in Stock Market Investment has been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Markov Switching models for forecasting the time series observations based on stock prices. The semi-parametric estimators for these models are a class of popular methods that have been used extensively by researchers to increase the accuracy of estimation. The main part of these estimators is based on kernel functions. Despite the existence of many kernel functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel in these estimators. But there is a question if other types of kernel function can be used in these estimators. This paper tries to introduce the other kernel functions that can be a good replacement for this kernel function to increase the ability of Markov Switching models. We first test six popular kernel functions to find the best one based on simulation studies and then offer the new strategy of buying and selling stocks by the best kernel function selection on real data.

Investor sentiment is one of the non-fundamental factors that affect the financial markets, which itself is influenced by various factors, including oil price changes. This study aims to investigate the impact of oil price on investor sentiment in stock market industries in the Tehran Stock Exchange (TSE) using monthly data from April 2010 to June 2020. To investigate this issue, stock exchange industries were grouped into three categories: total industries, oil-related industries, and non-oil industries, and the effect of oil prices on investor sentiments in these three groups was examined using the pooled mean group (PMG) technique. The PMG approach considers both the short- and long-run relation between series and provides reliable results in the context of dynamic heterogeneous panel models. The implementation of PMG in all three models shows the impact of oil prices on investor sentiment over both the short and long run. Findings suggest also that oil price has positive and significant in all three models in the long run and the oil price coefficient is higher in oil-related industries than non-oil-related industries. These results are the opposite of the results obtained by similar studies, which can be due to the special features of countries, e.g. being oil exporters or oil importers

This paper concentrates on the modelling of optimal stock portfolio selection based on Risk Assessment and Behavioral Financial Approach Mental Accounting and 28 expert’s opinion. In this approach developing the model approved by the opinion of academic and practical experts using quantitative and qualitative methods. Using quarterly return data of industrial indices for ten years in form of eight training and two test years indicates that the performance of DMSS and MVO based portfolios is equal however by regarding the value at risk and liquidity constraints in modeling, DMSS based portfolios perform higher than MVO portfolios.

Added over the period 2006-2018. We focused on different proxies of corporate governance indicators, such as the Directors' Effectiveness, the Transparency and the Disclosure, Responsibility. Basel Principles have been used to make corporate governance indicators and Stern & Stewart and Chew (1995) method have been used to make banking economic value added. We used the PCA method to choose important indicators. The results of PCA estimation identified ten important variables affecting banks' economic value added. Due to the importance of banks' age in creating economic value-added, banks are divided into two classes according to age. The GMM method is used to estimate the models. Eight models were designed to examine the impact of different corporate governance measures on the banking economic value added. The results indicated that corporate governance indicators were significant in explaining changes in the Iranian banking economic value added. The result also shows that according to the banks' age, the effectiveness of the board structure is greater than others. This illustrates the importance of board structure more than other criteria.

One of the most fundamental factors in pricing and evaluating the performance of companies is their profitability and profit is used as a basis for predicting the future performance of companies. Therefore, an accurate profit prediction is really crucial and decisive. There are various approaches to this prediction. The first approach would be calculating profit according to accounting standards by using historical cost and the second, calculating profit according to fair value. In this circumstance, this question arises that whether fair values are used instead of historical cost, would it lead to a more accurate and better prediction of the company's future performance?The purpose of this study is to investigate the effect of using the fair value in calculating profits on the performance of investment companies with the help of benchmarking international financial reporting standards for small and medium-sized units.This research uses the data of 95 companies listed on the Tehran Stock Exchange, whose activity is an investment, from 2015 through 2019 and compares the predictability of fair value-based profits with the profit based on accounting standards in predicting the company's operating cash flows and future profits. The data is first collected in Excel software, then the research variables are calculated and finally, research models are tested and analyzed by Eviews10.The results show that fair value-based profit has no greater ability to predict the performance of investment companies in comparison to profit based on Iranian accounting standards.

The present study aims to investigate the needs of users in connection with the information of intangible assets in current financial statements with an emphasis on the way of disclosing non-financial information. For this purpose, the effect of the two independent variables of causal links’ discussion and level of non-financial performance on the financial performance of the firm, as the dependent variable, has been studied. The research is applied in terms of its objective and it is a survey in terms of the research design. The research population includes PhD students of accounting in top-ranking universities of Iran. Statistical methods, including test ratio, single-sample t-test, independent t-test, and one-way and two-way variance analysis have been used to test hypotheses. The findings show that the disclosure of non-financial intangible information along with causal links does not affect the judgment of investors with a low or high level of knowledge. However, it should be noted that the recall of the performance in terms of non-financial criteria by investors, who have a causal link discussion, is higher than others.

Corporate social responsibility (CSR) is a fundamental factor for the survival of any organization. Companies and institutions are active in a society that provides them various opportunities to earn profits and realize their goals. The increasing importance of corporate social responsibility and the costs required by companies to operate and participate in these issue has led to the purpose of this study to investigate the impact of corporate social responsibility on the managers' behaviors in companies listed on the Tehran Stock Exchange. This study is based on purpose, application and data analysis in the field of causal descriptive studies. In this study, the reflection of managers’ myopic and optimistic behaviors is considered as managers' behaviors. Therefore, two hypotheses were developed to investigate this issue, and data from 174 listed companies were analyzed from 2008 to 2018. The regression model of the research was evaluated using a panel data method with a fixed-effects approach and logistic regression method. The result showed that the fulfillment of corporate social responsibility has a significant negative effect on the optimistic behavior of managers and decreases this type of behavior by managers. On the other hand, the results confirmed that accomplishing corporate social responsibility does not have a significant effect on managers' myopic behavior.

Since the auditing profession is a process engaged in judgment activities, knowing the reasoning concepts to achieve a level of rationale in audit judgment is the theoretical and fundamental concept in this profession. In this regard, tactfulness is one of the decision-making components in an auditor's judgment that assigns a level of reasoning for making an intellectual decision and promotes the level of judgment quality in auditing. Accordingly, the purpose of this research is Auditors’ Wise Tactfulness in Professional Judgments by Total Interpretive Structural Modeling (TISM). The mixed-methods approach was used for the research in which, in the qualitative part, two experts population as panel members, and, in the quantitative part, 30 independent auditors as the statistical population participated. In the qualitative part, the meta-analysis approach was used to identify the themes related to wise tactfulness in professional judgment, and then, the basic themes selected were examined based on two criteria, concordance coefficient and average, in three rounds reciprocally until theoretical saturation was met. At this point, 14 themes were accepted among 20 basic themes. In the quantitative part, the themes accepted were coded first and then were distributed among the respective population, based on a matrix questionnaire, to identify the most effective trait of auditor's wise tactfulness in professional judgment using the Total Interpretive Structural Modeling approach. According to the results, the theme adherence to the principles of professional ethics as a basic theme of professional thinking was selected as the most influential trait of wise tactfulness.

Value at Risk model based on a switching regime approach was used in this study to optimize portfolios consisting of industry index (petroleum products, investment, chemical products, and metal products). For this purpose, the VaR of returns on index should first be extracted through parametric models of the (GARCH) family in each of the above industries by using regime transitions. After the risk of return on index is obtained for each industry, the optimal portfolio is created in the next step based on VaR minimization, and the optimal value of each industry is determined in the portfolio. According to the results, (MRS-FIEGARCH) model had no superiority in VaR estimation over the other parametric models of the GARCH family. In fact (MS-EGARCH-t) was introduced as the optimal model. Among the designated industries, returns on indices followed regime transitions only in chemical products and investment by showing asymmetric reactions to external shocks. Moreover, the optimal weights were on the rise in the industries where VaR decreased over time, whereas the optimal weight of the portfolio decreased in the industries where VaR increased over time. The higher share of an optimal portfolio belonged to the industries where stock returns had lower rates of VaR. The risk-return-ratio was employed to show that the optimal portfolio with a risk rate was measured by considering the switching regime was superior over the optimal portfolio with a risk rate extracted without considering the switching effects. To create an optimal portfolio, it is then recommended to make investments in the industries characterized by higher stability in prices and lower fluctuations in stock returns in the long run. This approach can be employed to obtain the best results from optimal portfolio preparation in the worst-case scenario of the market fluctuations.

Information flow is a key parameter in an economic activity that acts as the main factor in the capital market emergence, stability, and efficiency. The purpose of the current research is to investigate the effect of the environmental points of cooperate governance on the pricing of information asymmetry. In this regard, we have extracted data related to companies accepted in the "Tehran Stock Exchange" from 2009 to 2018, and a panel-data regression model was utilized to test research hypnosis. The results show that information asymmetry and environmental points of cooperate governance have a significant effect on the expected return (cost of capital) on an investment. In addition, the effect of environmental points of cooperate governance on the relationship between the information asymmetry and the cost of capital has been verified. Finally, the results show that environmental points of cooperate governance leads to the differences in the cost of capital in the different levels of information asymmetry.