mohammadjavad salimi

Over the last few years, pension funds have encountered sustainability issues. Despite this, no scientific research has been conducted on strategies for overcoming instability. Therefore, the current issue is to identify the key drivers influencing the financial sustainability of pension funds and analyze and understand their interrelationships. Additionally, it is crucial to pinpoint areas for action and develop strategies and plans to overcome financial instability based on potential future scenarios.

In terms of its goal and nature, the current study is applied and uses a mixed-methods approach, respectively. Moreover, the study was conducted using both survey and exploratory approaches. To address the issue, the impact and influence of the key drivers were determined through structural analysis and results obtained from MicMac software. By identifying the significant and uncertain key drivers, future scenarios were extracted according to the Schwartz Theory. Through content analysis of expert interview results and the literature review, the areas of action and policy-making for pension funds were examined, and strategies were formulated by integrating these actions. Using MATLAB software, the fuzzy inference system, and based on six stable planning methods, robust strategies to improve financial sustainability were established.

The research findings reveal that sanctions, economic and military tensions, along with the independence of the funds from the government are the two primary key drivers of the financial sustainability of the funds, exerting the greatest influence on financial sustainability and other key drivers. Morphological analysis of these two key drivers results in nine potential scenarios that pension funds may face in the future. The research findings highlight ten strategic action areas, resulting in the discovery of thirty-two distinct strategies and the creation of ten knowledge bases. Using the fuzzy inference system and knowledge base analysis, the essential data for analyzing the robustness of strategies was gathered. The strategies to overcome financial instability were assessed using the results from six stable planning methods. The chosen strategy includes reforming and enhancing parameters that impact pension funds’ obligations. Additionally, it seeks to implement a multi-pillar system, integrate the pension system with the tax system, and develop insurance schemes. Furthermore, the strategy focuses on providing comprehensive coverage (including migrants) for taking part in pension and insurance plans and delegating the management of the fund’s investments to financial institutions to boost profitability.

Structural analysis of the key drivers highlights the significance of macroeconomic variables and fund governance. In addition to their impact on sustainability, these two dimensions also affect other key drivers. Therefore, the relationships between these key drivers must be taken into account in decision-making. Furthermore, these dimensions are heavily influenced by general national policies and greatly impact the potential future scenarios. Revisiting this matter will positively influence the funds' performance. To overcome financial instability, pension funds must take extensive actions, including drafting new pension schemes, securing sustainable funding sources, and improving investment returns. Pension system laws and regulations need to be reviewed by the relevant authorities, and the independence of the funds must be considered in financial decision-making. Given the intertwined social and economic impacts of pension funds, any reforms or strategies adopted in this sector must be implemented with full stakeholder awareness and a thorough assessment of both visible and hidden effects to ensure the best outcomes.

Regional Electric companies are organizations that pursue both social and financial goals in order to fulfill their assigned missions, so fulfilling accountability for their dual goals is of fundamental importance. In this research, by examining the information needs of the users of the financial reports, the factors affecting the financial reporting of the sector have been studied. The aim of this research is to present a model for the environmental conditions and characteristics of regional electric companies in Iran. For this purpose, the required data, after a library study and exploratory search in the theoretical foundations and financial and accounting rules and regulations governing the relations of these entities, were collected using a questionnaire and analyzed using the fuzzy Delphi research method and appropriate statistical tests. The evidence from the analysis of the respondents’ views shows that the influencing factors are in four dimensions, including the compatibility of the model in achieving the organization's goals, the needs of information users, compliance with financial and accounting laws and regulations, and finally, budget control and credit status reporting. Experts also agree on the factors proposed by this research for designing and explaining the financial reporting model of regional power companies in Iran.

The government and other public sector institutions provide many goods and services essential to society. One of the most significant areas in which the government engages in commercial activities is the energy sector, particularly the electricity industry, which plays a key role in social and economic development and in improving the quality of life in society. The financial resources of the country’s regional electricity companies are derived from various sources and must be utilized for specific purposes in compliance with various laws and regulations. Given the fundamental importance of performance and the evaluation of accountability by authorities to stakeholders in democratic governments, it is necessary to produce clear and reliable reports on how resources are allocated and consumed in different areas. This research seeks to identify the weaknesses and shortcomings of the financial statements of these institutions by reviewing existing literature and employing other methods. Ultimately, the study presents a suitable model for the financial reporting of these institutions, enabling improved accountability and more effective economic decision-making.

What is the financial reporting model of Iran's regional electricity companies?

Sayedi and Babajani (2011) conducted research with the aim of achieving a desirable model of financial reporting in Islamic capital markets. The findings of their research confirmed the usefulness of relying on the fund theory to achieve reporting goals. The result of their study led to a financial reporting model in which the central focus is not the economic entity but rather the main business activities and departments of the company. Babajani and Shekarkhah (2012), using the Delphi method, investigated the appropriate accounting model for Islamic banking in Iran. According to their findings, the accounting system used by experts was unable to meet user needs and required changes, the generalities of which were presented as key factors in the proposed research model. Additionally, the research indicated that a conceptual framework based on accountability is more suitable than one based on decision-usefulness for financial reporting in the usury-free banking system. Mohammadi et al. (2020), in their research to develop a desirable model of financial reporting in the public sector, addressed the key factors influencing public sector financial reporting. The results showed that the quality of public sector financial reporting is influenced by factors such as budgeting structure, public sector infrastructure, the quality of human resources, the accounting system and basis, education, and the accountability system governing society. Weaknesses identified in the research include poor implementation of accrual accounting, incomplete implementation of operational budgeting, political influence in decision-making processes, lack of access to the annual budget performance statement and budget deduction report, and non-identification of certain financial statement items.

The current research is an applied and developmental study. It aims to analyze existing conditions and assist in the decision-making process, classifying it as descriptive research. Furthermore, since it seeks to gather the opinions of a large statistical community on the research subject, it is categorized as descriptive-survey research.
Using the fuzzy Delphi method, the statistical population includes experts selected based on three criteria: the presence of representatives from expert groups, deep knowledge of the research topic, and breadth of opinion and expertise. These experts were chosen from groups such as auditors, the head of the State Court of Audit, auditors of executive bodies, directors of audit organizations, and academic faculty members with relevant experience. Participants were selected through snowball sampling. Initially, to identify the dimensions, components, and indicators of the Financial Reporting Model for Regional Electric Companies in Iran, a review of the subject literature was conducted. After identification, examples of these cases in the public sector were examined based on expert opinions. Given the advantages of the fuzzy Delphi method (29FDM) compared to the traditional Delphi method (30TDM), the fuzzy Delphi method was employed in this research.

By examining the needs of users and the current state of financial reporting for regional electric companies, which is affected by several factors, it was found that the financial reporting models of private sector for-profit institutions cannot fully address the information needs of users in this sector. The findings of this research revealed that the operating environment and user needs in this sector differ significantly from those of private-sector for-profit institutions. These differences have created challenges in aligning the information needs of users with the form and content of the current financial reports, leaving report users facing difficulties.
In this research, by identifying and analyzing the factors influencing an appropriate financial reporting model for Iran's regional electric companies, a step has been taken to better meet the information needs of users. Identifying the set of influencing factors for the proposed model, in accordance with the conditions and laws governing the financial and accounting systems of this sector, and determining the importance of each factor in the desired framework are among the key findings of this research effort.

According to the findings of the research, the consistency of the model in reporting the degree of achievement of the set goals of regional electric companies, the consistency in supporting the goals of information users, its compliance with financial and accounting rules and regulations, as well as budget control and credit status reporting, were identified as the effective dimensions of the reporting model. Each of these dimensions comprises several components and indicators.

This research aimed to present a financial reporting model for Regional Electric Companies in Iran. Using the fuzzy Delphi method and based on expert opinions, the dimensions, components, and indicators of the proposed model were identified and presented.

The study and structuring of effective problem-solving or system improvement drivers are important. Understanding the relationships between stimulating factors in a complex system and identifying internal relationships helps establish order between elements and make better decisions. So far, few scientific research studies on the financial sustainability of pension funds have focused on holistically identifying the effective drivers of pension fund financial sustainability. Additionally, the internal relationships among the influential factors on pension fund financial sustainability and the way and extent of their impact have not been examined. Interpretive structural modeling can significantly assist in prioritizing and analyzing the impact of drivers on each other.

When research is conducted with the intention of practical application and solving a problem, it is considered applied research. Therefore, due to the use of its results to address the financial issues of pension funds, this current research is considered applied research from an objective perspective. In terms of execution, it is field-based. The research is of a mixed method, comprising qualitative and quantitative components. Data collection is conducted in a real and unaltered manner, and it falls under the category of descriptive (non-experimental) research, specifically survey and exploratory research. This research identified key drivers through interviews with experts and using the best-worst method. Then, by employing interpretive structural modeling, the relationships between drivers were identified, and the drivers' degree of influence and dependence were determined using structural analysis.

The research findings indicate that the identified key drivers are classified into four levels. Economic sanctions and tensions are the most influential drivers, directly affecting two drivers: population growth rate and growth rate of employed individuals at the third level. Responsiveness and reporting quality to program members and stakeholders, automation and substitution of robots for workers, independence of funds from the government, the presence of appropriate reporting standards, diversity of retirement plans, and commitment to transparency and accountability are drivers at the second level. Timely debt repayment by the government, the possibility of fund investments in foreign markets and vice versa, gross domestic product growth, balance in employer-employee relationships, innovative management approaches, prescription of fund resource investments in specific and low-yield securities, and the efficiency of the banking system are the remaining seven influential drivers at the first level.

in a system with this level of complexity, any decision-making and planning should be done comprehensively and holistically. What is evident is that the ability to change the trends of these drivers is generally beyond the capacity of pension funds. Funds should be prepared to face any potential threats when formulating strategies to achieve sustainability, which may disrupt their performance. Changes in each driver will have different effects depending on the socio-economic structure. The most important factors, such as macroeconomic variables and international sanctions, should always be considered. The findings indicate that economic sanctions have had a significant and negative impact on the unemployment rate and the informal sector's contribution to the Iranian economy, as well as a significant and positive impact on the inflation rate, the agricultural sector's contribution, and taxation. The volatility of the macroeconomic environment has shown an influence on women's fertility rates, where income growth has a positive effect on fertility. Furthermore, economic growth has provided a basis for reducing managerial discretion in corporate profit reporting and improving the quality of reporting. On the other hand, sanctions, along with increasing political instability, can create ambiguity in the future political system and consequently have adverse effects on the country's trade and financial relations, domestic and foreign direct investment, and lead to economic instability, thereby affecting the labor market of that country. The consequences of sanctions result in increased transaction costs and a less productive use of available resources. This particularly holds true in the labor market, as workers may shift from the formal to the informal sector based on their expected job prospects. Studies indicate that trade shocks are associated with changes in informal employment. Contraction in both imports and exports can negatively impact the sanctioned economy's labour market, leading not only to a reduction in employment in import and export industries but also to a reallocation of the workforce across various sectors. From a governance perspective, ensuring the sustainable financial management of pension funds requires policymakers to consider the effects of drivers in their short-term and long-term planning and legislative processes in various social, economic, and political domains. Changes in each driver will have different effects depending on the socio-economic structure. Economic instability, high risk, and uncertainty regarding economic policies impact the performance of funds and, in addition, create tensions that reduce the level of investment and sustainable growth. Another important aspect that should be considered by governing bodies is demographic changes. The decline in birth rates in the coming years can lead to a decrease in the working-age population (reducing the support ratio as a key indicator of sustainability) in the coming decades. On the other hand, the current workforce is reaching retirement age while life expectancy has increased in recent years. This poses significant commitments to pension funds. Government policies heavily influence the governance structure, accountability, and reporting of pension funds, and they should be reviewed and modernized, similar to other countries, as one of the key factors.

Stability affects the planning process and making optimal decisions by managers; Uncertainty and instability have been introduced in financial and economic literature as one of the most important factors affecting the amount and level of investment in countries. The impact of uncertainty on the reduction of income and profitability of companies and, as a result, the lack of attractiveness of the Country's financial market for foreign investors, has attracted the attention of experts and researchers. This research aims to systematically review uncertainty research to determine the future trends of this research field. For this purpose, a systematic literature review with a Meta-synthesis approach is used. After deciding on the search protocol and article selection indicators, 68 articles were selected. The evaluation of the selected articles led to the identification of 47 Factors and the measurement indicators related to each Factor. Uncertainty Factors were classified into company, industry, macroeconomy, and international economy. Examining the research carried out in the company aspect shows the interest of the researchers in investigating the uncertainties related to the upstream and downstream chain; In fact, managers and shareholders of companies are insecure about the supply of raw materials for production and sale of manufactured products. In the following, trend-setting articles and highly cited authors were mentioned in each period. The authors believe that the future research process in the field of uncertainty will focus on combined research in both global and corporate dimensions, and researchers will investigate the impact of uncertainty on international companies; This line of research has been started for several years with the tariff war between the United States of America and China and has been intensified by changes in tax rates by governments, so it seems that the research process in the field of tax arbitrage will increase; Also, due to the increasing trend of joint research in the field of uncertainty and cryptocurrencies, this research path is expected to become one of the main paths of uncertainty studies.

Pension funds in Iran use defined benefit pension plan and their sustainability is important. However, the evaluation of their sustainability has always been criticized. Minimum reporting and simple accountability indicators do not meet the informational needs of stakeholders. Thus, the main issue is to identify the indicators and standards for comprehensive evaluation of financial sustainability. To address this issue, the theoretical foundations of sustainability evaluation of pension funds and the indicators applied by other countries and international organizations were examined. The indicators were presented to experts for receiving their opinions and in order to reach a consensus on key indicators a fuzzy Delphi method was applied. For ranking and developing a combined indicator, the final indicator was obtained using experts' opinions and the SWARA method. 27 indicators in four dimensions were extracted from the theoretical foundations: equity, adequacy, financial, and innovation. According to the results of the fuzzy Delphi method, 15 key indicators were confirmed finally. Among the key indicators, the support ratio obtained the first rank, while the replacement rate and penetration coefficient obtained the second and third ranks, respectively. The results of the SWARA method confirmed the combined indicator consisting of equity dimension (1 sub-indicator), adequacy dimension (3 sub-indicators), and financial dimension (11 sub-indicators). The weight of equity, adequacy and financial in the combined indicator is equal to 6%, 21%, and 73%, respectively. The support ratio, present value of Assets to Liabilities Ratio, and actuary analysis obtained ranks 1 to 3. the financial dimension has the highest importance,

According to the research literature of initial public offerings (IPOs), despite the high Performance of them in the short-term, their long-term performance will probably be lower than the average performance of the relevant market {or industry} and this issue, if confirmed, requires the special attention of capital market activists. By using factor models, the current research has focused on the long-term performance of IPOs and, accordingly, the phenomenon of their underperformance in the long-term. In particular, in order to create a broad and reliable insight into the phenomenon " long-term underperformance of IPOs”, analyzes have been carried out at various levels, including the market and industry levels.

The research was conducted on 235 initial public offerings (IPOs) between February 2015 and December 2020 (57 months in total). The analyzes have been done with the approach of factor models and the use of monthly time series of portfolios consisting of initial public offerings (IPOs). To investigate the phenomenon of low or high Performance of IPOs, the intercept level of the models has been used. Due to the lack of agreement among researchers regarding the length of the long-term period of IPOs, this research has used three periods (12-24 and 36 months).Also, according to the existence of the different models explaining performance of the IPOs and the possible effects of the model on the results, three different and conventional models have been used, including Fama and French (2003 and 2015) and Hou et al.'s model (2015).The stock and over-the-counter markets have been investigated separately, and since the research data only made possible the portfolio of 4 chemical, pharmaceutical, agricultural, and basic metal industries, the analysis of industries was carried out only at the level of these 4 industries.

Validation test of the models supported their validity and the results of fitting them showed that all the investigated models have adequate explanatory power and the minimum adjusted explanatory power (adj R2) is 69% and the maximum is 85%. As the definition of the long-term period becomes longer, their explanatory power decreases. IPOs move almost in line with the market, and the most important factor in predicting their return is market risk and profitability, and other factors have little effect on explaining the long-term return of IPOs. Regarding the investigation of the under-performance phenomenon, it should be said that sufficient evidence was not obtained to support the phenomenon of low or high performance of initial public offerings. And the intercept of the models in all periods and for all models lacked statistical significance. Breaking the data into the market and industries level did not create a special difference in the results. The analysis of the 4 mentioned industries showed the phenomenon is not statestically significant in any of the industries, although in the case of the chemical industry, a borderline significance level with a positive coefficient was obtained in some periods. Whether the IPOs are listed in stock market or over-the-counter (OTC), does not make a difference in their long-term performance.

The evidence of the current research does not support the existence of the phenomenon of “IPOs long-term underperformance” its reverse form (over- performance) in any of the tested cases, and the results for periods of more than one year (12-24 and 36 months) and for both stock and over-the-counter (OTC) markets and for all four industries (, chemical, pharmaceutical, agriculture and basic metals), are consistent and the model used, also has no effect on it so it must be said that the existence of under or over-performance of IPOs in Iran's financial markets is not confirmed. In more technical terms, in periods of more than one year, the market does not recognize the difference between the IPOS and the other companies due to factors other than known fundamental factors. This issue challenges the need to adjust individual decision-making models in the face of initial public offerings, and on the other hand, provides guidelines for use by legislators when legislating processes related to the capital market and especially initial offerings

The rapid development of technology and extensive environmental changes have accelerated economic growth, and the increasing competition among enterprises has restricted access to profit and increased the probability of enterprises ' financial distress. Due to the effects of high costs of financial distress, its prediction has attracted the attention of researchers since the beginning. Therefore, this paper aims at a bibliometric analysis of financial distress research in the accounting, management and economic areas.

Design/methodology/approach: 

The research method is based on a three-step protocol of dataset setting, dataset refining, and analyzing the data. First, the published articles in the financial distress field were collected from the Web of Science database. Second, the document information was refined, and 801 articles were chosen for literature review in this area. Finally, we used the bibliometric analysis toolbox to investigate the documents. Also, bibliometric analysis in this research was conducted using VOSviewer software.

The findings of this research indicate the existence of six main streams of research (methods of predicting financial distress, predictors of financial distress, restructuring strategy, corporate governance, bank bankruptcy and earnings management) in the field of financial distress. Additionally, the results highlight the importance of social responsibility of the company, also demonstrate that improvements in technology, particularly the use of artificial intelligence tools, have enhanced predicting accuracy.

The Earnings Forecasts report is one of the sources of information for stakeholders in the capital market. The presentation of this report has been a challenging issue in recent years. The purpose of this research is to develop a framework for Earnings Forecasts reporting in the Iranian capital market. In this research, a qualitative research method and an approach based on theme analysis have been used. To achieve the purpose of the research, First, the primary framework was identified by studying the literature review and theoretical background of the research. then, Using the snowball sampling method, 21 experts in the field of financial reporting and capital market were interviewed in a semi-structured manner. Finally, the data of the research was analyzed with the method of theme analysis and the Earnings Forecasts reporting framework was extracted according to the country's environmental characteristics. According to the findings of the research, 14 sub-themes and 6 main themes including generalities, antecedents, characteristics, consequences, challenges and evaluation were identified, which were determined as the components of framework for Earnings Forecasts Reporting. The results of this research can be a suitable guide for amending regulations and developing financial reporting standards.

The purpose of this study was to investigate the possibility of using principal component analysis method as a tool for data reduction of the proxies of stock liquidity in Tehran Stock Exchange (TSE). First, the initial set of proxies of stock liquidity (8 variables) was identified and after the initial validation tests, the method was implemented at 2 levels: 1) all companies and 2) companies with much data. According to the obtained results, applicability of using this method to reduce the initial set of variables was concluded. The results showed that in both levels of analysis, the method could be used successfully for data reduction of liquidity proxies. Depending on the purpose of different researches, the initial set of liquidity proxies could be appropriately reduced by extracting 2 or 3 main components, while explaining the acceptable part of the total data variance.

The earnings forecasts report is considered as one of the most important and effective reports in investors' decision-making. The purpose of this study is to present an earnings forecasts reporting framework in Iran's capital market. To achieve this research goal, the earnings forecasts reporting framework was identified first by studying the theoretical foundations and the background of the research, as well as interviewing 21 experts using the snowball method and the theme analysis method. Then, through the implementation of the fuzzy Delphi method and solicitation of opinions from 183 experts using a questionnaire and targeted judgmental sampling method, a consensus was reached on the reporting framework, resulting in the presentation of the earnings forecasts reporting framework in Iran's capital market. The research population included university faculty members, employees in regulatory organizations, investors, auditors, and providers of financial information. The research results showed that out of 122 detailed themes extracted through theme analysis, categorized into six main themes and 14 sub-themes, 97 detailed themes obtained the consensus among the Delphi group, thereby forming components of the earnings forecasts reporting framework. The main elements of the earnings forecasts reporting framework encompass generalities, environmental fields, characteristics, consequences, challenges, and evaluation. The findings of this research can serve as a guide for developing financial reporting standards and modifying procedures and regulations.

The management forecasts earnings is one of the disclosed information outside the financial statements, which reflects the management's forecast about the future prospects. This report is one of the most important sources of information for companies in the capital market. Corporate management possesses considerable information advantages about contingencies related to future profitability. Management disclosures are considered a valuable and potential source of information for investors. Investors are interested in estimating the future benefits of their investment so that they can assess receiving future cash earnings as well as the value of their shares. Therefore, the expected earnings from companies are important for investors and beneficiaries to make investment decisions.
How to present the earnings forecast report has been a challenging issue in recent years. Therefore, in the current situation, examining the framework and reporting method of earnings forecasting in the Iranian capital market using the opinions of experts is regarded as an essential need.
Considering the importance of earnings forecast reporting for investors, the problem of the current research is: What is the earnings forecast reporting framework in Iran's capital market? Additionally, what are the components of this framework based on the country's economic and capital market conditions?

Literature Review:

There are several reasons for disclosing the information of managers and publishing the earnings forecast report. One reason for this is agency theory, which refers to the conflict of interests between managers and owners. In addition, we can refer to the Signaling theory, Expectation adjustment hypothesis, and Legal liability hypothesis.
The primary framework of earnings forecasting reporting includes the purpose, users, limitations, environmental fields, characteristics, and consequences.
Hirst et al. (2008) provided a framework regarding management earnings forecasting. They categorized earnings forecasts into three components including antecedents, characteristics, and consequences. They concluded that earnings forecasting characteristics are less explored in both theoretical and empirical research, despite managers having the most control over this component.
Preussner and Aschauer (2022) synthesized the literature on management earnings forecasts and adaption mechanisms, combined existing theories into a unifying framework. Overall, the literature review provides strong support for a positive correlation between the extent and credibility of management earnings forecasts, on the one hand, and stock returns, share liquidity, and analyst coverage, on the other hand. Earnings forecasts tend to be optimistically biased, with a positive correlation with forecast uncertainty, earnings flexibility, financial distress, investor sentiment, and the share price dependency of managers' remuneration. Firm growth, legal liability, and litigation risk are significantly associated with forecast pessimism.
Until 2017, listed companies in Tehran Stock Exchange published an independent report titled earnings forecasts report. The Securities and Exchange Organization announced in a notification that since January 2018, the Issuers are not allowed to publish earnings forecasts report. Instead, they are required to prepare and disclose the management's interpretive report alongside the interim and annual financial statements. Recently, as of July 2021, the return of the earnings forecast report was announced with a new procedure for five industries.

To achieve the goal of the research, the primary framework was first identified by studying the literature review and theoretical background. Semi-structured interviews were then conducted with 21 experts using the snowball sampling method. The data from the interview was analyzed using the theme analysis method and the earnings forecasts reporting framework was extracted according to the country's environmental characteristics. Finally, the fuzzy Delphi method was implemented and opinions were gathered from 183 experts through a questionnaire and targeted judgment sampling method to reach a consensus on the earnings forecasts reporting framework.
The statistical population of the research included university faculty members, employees in regulatory organizations, investors, auditors, and providers of financial information.

The research results showed that out of 122 detailed themes extracted through theme analysis, which were categorized into 6 main themes and 14 sub-themes, 97 detailed themes obtained consensus from the Delphi group and were identified as components of the earnings forecasts reporting framework. The main themes of the framework are generalities, environmental fields, characteristics, consequences, challenges, and evaluation. Each main theme consists of sub-themes. For example, the generalities theme includes sub-themes such as purpose, users, and limitations. The environmental fields theme covers aspects related to the forecast environment and company characteristics. The characteristics theme encompasses the method of publishing, features, text of the report, and assurance. The consequences theme addresses the consequences of publishing and non-publishing. The challenges theme explores the challenges in the environment and the company. Lastly, the evaluation theme focuses on the evaluation of the disclosure procedure.

The findings of this research can serve as a valuable guide for developing financial reporting standards and modifying procedures and regulations.
The paper has some limitations. The use of questionnaires, which is common in humanities research, is inherently limited, and this research is no exception. The time limitation, the diverse knowledge base of the experts, and their interest in the research topic may have influenced the quality of the experts' responses to the questionnaire.

This research has presented the earnings forecasts reporting framework in Iran's capital market, consisting of 6 main themes. The results of this study can help Iran's Accounting Standards Development Committee in developing standards. Furthermore, the Securities and Exchange Organization can use the framework, particularly for the evaluation theme to modify and present regulations related to earnings forecasting reporting. Additionally, investors can use the results of this research to enhance their understanding about the earnings forecast report and make more informed investment decisions. Issuers can also use the framework to improve information disclosure and prepare reports.

I am grateful to all the esteemed professors and experts who helped me in this way. I would also like to express my gratitude to the staff of Allameh Tabataba’i University for their cooperation.

The survey on the Relationship between Investor Characteristics and their Loss Aversion Coefficient in Tehran Stock ExchangeAbstractThe present study, after calculating the Loss aversion coefficient of active investors in Tehran Stock Exchange, investigated the relationship between variables of gender, analysis tools, age, marriage, experience and education with Loss Aversion Coefficient by pooling regression method. The sample included 403 investors who responded twice to research questions within 6 months.The results showed that there is a significant relationship between gender, type of analysis and education with investors Loss Aversion Coefficient, these variables are inversely correlated with the Loss Aversion Coefficient in Tehran Stock Exchange, in other words, females are statistically more loss averse than males, also loss aversion decrease with increasing education more over fundamental analysts are more loss averse than technical analysts.

Regarding the importance of the stock market and commodity indexes as a predictive index, the effect of some selected global commodity indexes on the index of metal ores extraction in Tehran Stock Exchange is investigated in this article. Using the monthly state data from April 25th, 2012 to January 20th, 2020, the impact of the index of Bloomberg industrial metals, and the index of Nasdaq industrial metals on the index of metal ores extraction in Tehran stock exchange were studied by ARDL method. To investigate the existence of the long-term relationship, the Bounds testing approach was used and in order to control the effects of liquidity, consumer’s inflation, producer’s inflation, and the exchange rate in the unofficial market on independent and dependent variables, these variables were used as control variables in the model. The results show that the global commodity indexes of CRB without energy, Bloomberg industrial metals index, and Nasdaq industrial metals index have a positive and meaningful relationship with the index of metal ores extraction in the Tehran stock exchange Among the above two indexes, the Nasdaq industrial metals index was more influential on the metal ores extraction index than the Bloomberg industrial metals index.

Given the importance of the growth and development of the capital market in a country, knowing the factors that affect people's equity investment can help Capital market development and growth. Myopic Loss Aversion (MLA) is one of the factors introduced by Benartzi and Thaler (1995). In this regard, the present study, after measuring myopia and the loss aversion coefficient of real, active investors in the Tehran Stock Exchange, investigated the effect of Myopic Loss Aversion on equity investing by pooling regression method. The sample consisted of 403 investors who answered the research questions twice in 6 months in 2018. The results of this study indicate that the median value of the loss aversion coefficient for investors is 2.17. The results of this research show that more myopic loss-averse investors that more change and evaluate their stock portfolios; invest less in stocks and more myopic loss-averse investors that less change and evaluate their stock portfolios; invest more in stocks This finding is consistent with the theory of Myopic Loss Aversion. The findings also showed that men invest more in equities than women and fundamental analysts less than technical analysts. This study emphasizes the importance of myopic loss aversion in the stock market and considers the reduction of myopic loss aversion as a factor in increasing equity investment.

The effect of overvalued equity on the relation berween benchmark beating and unexpected accruals In this study, the impact of overvaluation on the relation between benchmark beating and unexpected accruals in listed companies in Tehran Stock Exchange has been investigated. Our sample was a group of 105 companies in the Tehran Stock Exchange and range of our data was years from 1388 to 1395, respectively. To analyze data and test hypotheses, multivariate regression model was used. Results show that there is no relation between overvaluation and unexpected accruals. Also we found that there is a relation between benchmark beating and unexpected accruals, which these results are in compliance with results of Coulton et al (2015) and Farajzadeh et al (1394). Finally, we found that overvaluation has an impact on the relation between benchmark beating and unexpected accruals, which these results are in compliance with results of Coulton et al (2015).

The present study first investigates the asymmetry of speedup - delay (gain and loss) and Sign Effect in Tehran Stock Exchange, then examine the effect of gender on the discount rate and explain it with the loss aversion. The sample is 403 investors in Tehran Stock Exchange, and the nonparametric Tests are used to test the research hypotheses. The research results show that there is an asymmetry of speedup - delay in the Tehran Stock Exchange, which means; for gains, investors delay premium (a discount rate) is larger than the speed-up cost (a discount rate) and for losses; the discount rates of speed-up are larger than discount rates of delay. Also, the findings of this study indicate that there is a Sign effect in the Tehran Stock Exchange; in other words, the discount rate of gains is greater than the discount rate of losses. This study also finds that gender is correlated with discount rates, which that means; women have a higher discount rate for the delay in gains and lower discount rate for the delay in losses, which is due to their higher loss aversion than men. These anomalies are incompatible with the traditional discount model predictions, which is widely used in financial matters and assumes a constant discount rate.

The problem of portfolio optimization and stock selection is one of the major areas for financial investors in financial markets. In this paper, some of the challenges of simultaneously multi-objective portfolio optimization are addressed. Four different models are designed: a fuzzy multi-objective programming model has been used to consider the multi-criteria nature of stock selection and the uncertainty associated with the return on assets and a simple model for doing this. The models are designed in such a way that both the nature of the multiplicity of the problem of portfolio selection is considered and the considerations of the investor in the choice of portfolios are involved. After designing the evolutionary 3 and 4 objective models of portfolio optimization, multi-objective evolutionary algorithm NSGA-II was used to solve this models. Concretely, it optimizes return, the downside-risk, skewness and the Kurtosis of a given daily returns, taking into account budget, and investor constraints. Because of the NP-HARD nature of the above models, the NSGA-II proprietary algorithm was coded in the MATLAB, and after solving each model and extracting the Pareto frontier, the best portfolio on the Pareto front was selected based on the maximum Sortino ratio. Finally, the results of the obtained portfolios in both fuzzy and non-phase conditions were compared according to the trainer's ratio, and it was determined that the use of fuzzy logic in quadratic evolutionary algorithms, compared to a situation where fuzzy logic is not used in the design and use of these algorithms., Creates more favorable results.

Selecting effective criteria on prices and consequently on investor’s decision making is one of the most debating topics in portfolio optimization debate. Both of market and industry price changing and the information releasement by companies can affect stock prices. As a result, the goal of this study is surveying the role of market and industry price changing on stock prices and its effect on portfolio optimization. So we use stock price synchronicity. Stock price synchronicity measures the degree to which the market change can explain stock price movement. So by collecting price changing data from 130 sample companies during 10 years and with solving regression equations we computed stock price synchronicity. Then by collecting financial and nonfinancial data from the samples and analyzing these data and using data envelopment analysis (DEA) technique we made several portfolio to compare them by sharp ratio. The result shows that stock price synchronicity is about 59% in the sample and it is in conformity with international surveys like Jin and Myers (2006). Also the result shows that if stock price synchronicity affection be considered in portfolio selection then portfolios will have better return. In this research we use data envelopment analysis to choose portfolios and use Fuzzy Delphi to choose effective criteria on stock price changing.