farhad hanifi

The current study has investigated the effect of liquidity growth rate and real interest rate deviation on the performance of banking industry and credit institutions in Tehran Stock Exchange during the period of January 2011 to March 2021. In this way, autoregressive vector model, Granger causality test and instantaneous reaction functions have been used to explain the mechanism of the effect of liquidity growth rate and real interest rate deviation on the return of the banking industry index and credit institutions. According to the investigations, there is an inverse relationship between the uncertainty of the real interest rate and the return of the banking industry index in the Tehran Stock Exchange market; But the volatility of liquidity growth does not significantly affect the performance of the banking industry index. Keywords: Liquidity Growth Rate, Uncertainty of Real Interest, Returns of The Banking Industry Index and Credit Institutions, Autoregressive Vector Model, Granger Causality Test

The issue of taxing stock gains is a complex and sensitive phenomenon that has the capability to significantly impact the capital market and the macroeconomy. The present research aims to thoroughly study the dynamics and complexities associated with this process in the Tehran Stock Exchange. The scope of the research includes the stock transactions of companies listed on the Tehran Stock Exchange, and data has been collected through library studies, interviews, and questionnaires. The DEMATEL approach has also been employed for data analysis. The findings suggest that taxing stock gains, if carried out with precision and attention to specific requirements, can have positive effects such as economic growth and increased government revenue. However, overlooking important aspects could lead to the improper redistribution of incomes and even taxation on capital losses.The issue of taxing stock gains is a complex and sensitive phenomenon that has the capability to significantly impact the capital market and the macroeconomy. The present research aims to thoroughly study the dynamics and complexities associated with this process in the Tehran Stock Exchange. The scope of the research includes the stock transactions of companies listed on the Tehran Stock Exchange, and data has been collected through library studies, interviews, and questionnaires. The DEMATEL approach has also been employed for data analysis. The findings suggest that taxing stock gains, if carried out with precision and attention to specific requirements, can have positive effects such as

Choosing the right portfolio is a crucial goal for investors. Two key factors to consider when selecting a portfolio are return and portfolio risk. This problem can be written as a mathematical programming equation and can be solved quickly. For instance, some investors choose stocks based on past performance, while others consider factors like liquidity when making their selections. Additionally, fundamental and technical analysis are often used in stock and portfolio selection. However, the strategies and methods used to select stocks and portfolios can vary depending on the current market conditions and the investor's level of knowledge. This article focuses on designing and explaining a portfolio optimization model using the cuckoo optimization algorithm. Results show that the best value of the utility function increases as the number of iterations increases. The growth value of the best value of the utility function is higher in the initial iterations and gradually decreases until it reaches zero, indicating that the algorithm has converged to the optimal solution. This research fills a gap in the study of investment portfolio optimization using nested optimization models. Additionally, the study finds that shares selected from industries with better performance make up a higher proportion of the portfolio.

Banks and credit institutions through attracting financial sources in the form of bank deposits and allocation them in the form of variety of loans, play an important and vital role in the economy of any country. Banking activities, due to Special features such as, high leverage degrees, existence of maturity mismatch between assets and liabilities, contagion the problems to other institutions, and the last but not least, having direct impact on Macroeconomic conditions, necessarily requires risk acceptance, which depends on the dimension, complexity of activity and degrees of systematically important and in the lack of effective supervision, can affect both economy and financial systems, domestically and even internationally. Systemic risk is the probability of sudden fall in total financial system and can lead to instability or chaos in financial markets. The systematically important institution is an entity that in the event of a crisis due to its special characteristics such as, size, market share, interconnectedness, cross boarder activities, complexity and etc. can have important effects on domestic or even international macroeconomic condition. So, the importance of Convergence in the field of managing banks and existent of homogenous rules and regulation in this very important industry is completely obvious. Considering that no study and research has been done about systematically important banks in Iran, the main goal of this research is to develop the methodology to determine systematically important banks in Iranian banking system and then measuring Systemic risk using ΔCoVaR and MES. The time period under review is from the beginning of 2014 to June 21, 2022. The results show that there are many qualitative similarities between the systemic risk calculated by theΔCoVaR and MES, despite the numerical differences. Also, according to the results of both methods, Tejarat, Parsian, Pasargad, Saderat, Novin Eghtesad and Mellat had the highest to lowest level of systemic risk in the study period respectively.

One of the important topics discussed in the stock market, which should be considered by both natural and legal investors, is choosing an optimal investment portfolio. In this regard, investors are studied in order to select the best portfolio based on risk and return. However, traditional investment methods do not focus on portfolio optimization and only consider the highest return and lowest risk. This research addresses the gap in solving the problem of wide portfolio optimization by comparing answers using more effective and efficient metaheuristic optimization algorithms, thus reducing the probability of error. During this research, metaheuristic optimization methods are well-designed and studied, and then used to optimize the portfolio despite real market limitations. The developed algorithms are all implemented to solve the extended portfolio optimization problem. In this research, more effective and efficient metaheuristic optimization algorithms are used to solve the problem of wide portfolio optimization and by comparing the answers, the probability of error can be almost zero. The stock portfolios formed by the model based on censoring models have more returns and less risk (variance) than the invasive weed algorithm, showing the superiority of the proposed model in comparison to the invasive weed algorithm. The findings of the research have filled the research gap in investment portfolio valuation and demonstrate that the proposed model has effectively considered investment portfolio selection conditions and determined an optimal investment portfolio.

The use of traditional variables and patterns in explaining the factors affecting the management of real and accrued earnings has faced many challenges in the literature. This article tries to fill this gap by considering different variables in the context of traditional and new theories and by using Bayesian econometrics and panel data related to 131 listed companies during the period 1380-1388. First, the determinants of real and accrued earnings management are explained theoretically, then using the "Bayesian model averaging" method; The profit management model is estimated and after calculating the variables, its effect on price manipulation is determined. Based on the results, both real profit management and accrual management have a significant effect on price manipulation in both high and low price manipulation business cycles. It has an asset index.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

The exchange rate affects the economic activity, foreign trade and wealth of economic enterprises. The aim of this study is to explain a model to investigate the effect of exchange rate shocks on the profitability of export-oriented production groups. In this regard, the data on exchange rate, tax, oil revenue, export and profitability were collected for 19 export-oriented production groups from 2008 to 2019. To achieve the research goal, the Panel Vector Autoregressive Model (PANEL VAR) using the generalized method of moments (GMM) was used to analyze the data. The results of the the Impulse Response Function show that the effect of exchange rate volatility, tax and oil revenue on the profitability variable is initially negative, but has a positive effect over time and is neutralized after several periods. But, the export impulse has positive effect on profitability. According to the results of variance decomposition, it can be said that the exchange rate fluctuations have more explanatory power for profitability fluctuations.

From a theoretical point of view, the meaning of financial disorder is to try to reduce the opportunistic behavior of managers; Therefore, it seems that many companies are involved in financial irregularities, and for this reason, it is very important to determine the factors affecting the level of financial irregularities in companies, for this purpose, the indigenous model of Hanifi et al. (2022) was used. For this purpose, a questionnaire was prepared and distributed among experts to ask the opinion of the experts about the weight and importance of the criteria considered for measuring the financial irregularity of the company, and the weight and importance of the criteria were determined using one of the methods of the multi-criteria decision-making model (Shannon's entropy). Also, in order to measure the relationships of the hidden variable, which in this research is financial irregularity, confirmatory factor analysis was used; Also, in this research, we will try to measure the impact of financial risk on the presented model of financial disorder. Therefore, in this research, data from 167 companies during the years 1390 to 1400 has been used. The obtained results show that the proposed model is a suitable indicator for financial disorder. Also, the results include that financial risk increases financial irregularity

The aim of this research is to present a risk- based supervision model by the bank and credit institution supervisor. The statistical population includes all experts in the banking industry and our sampling method is a theoretical and targeted one(snow ball).For this purpose ten experts- experts and senior managers of the banking sector (central bank and banking network) and university professors- are selected and interviewed. Propositions and conceptual relationships of the phenomena that makeup the model are introduced, based on the grounded theory, after collection of organized data and inductive analysis of concepts derived from interviews, through open cooling, axial coding and selective coding of categories. In addition, after reviewing the theoretical foundations and experiences of other countries, some effective components are included in the model. The results of the research represent 35 dimensions. Findings show that the lack of a clear definition of the supervision concept and its goals has caused stakeholders and actors to face different expectations of the concept of performance and the outcome of regulatory system. This issue leads to an inconsistency between the supervised organization, supervisory institution and decision-making authorities Also, the inadequacy of the monitoring in current situation, due to the retrospective nature of the existing monitoring framework, has placed satisfaction with the output of the current monitoring framework at a low level. Relying solely on the approach of comparative supervision and not paying attention to future risks and future forecasting, as well as the lack of a proper process and structure in applying supervision show the necessity of the risk-based supervision.

An efficient banking system is the most effective means for economic development, and the most important task of banks is to allocate resources in the form of banking facilities, and the design and establishment of the credit rating model has an effective role in increasing the efficiency of banks in equipping resources. In the current research, the design and explanation of the credit rating model was done using the data envelopment analysis model. Statistical sample related to the information of legal clients admitted to the stock exchange and receiving facilities from Tejarat Bank during the years 2018 to 2019; expressed In this context, 30 explanatory variables including financial and non-financial variables were examined. Among the available variables, finally, using the factor analysis technique and Delphi method, the variables affecting credit risk were selected and entered into the data coverage analysis model, and the efficiency scores of law firms were obtained using them. The results of the comparison of two data coverage analysis models indicate that the validity of the financial model is 0.072 more than the combined model. In the financial approach, 7 companies were efficient and in the combined approach, 12 companies were recognized as efficient.

Among the very important topics that are currently being considered in most researches is the discussion of financial disorder and the results that come from it. For this reason, it is very important to determine the factors affecting the level of financial disorder in companies, because a comprehensive index has not been provided to measure financial disorder, and in the present study, by considering different indicators of financial disorder through methods such as the multi-criteria decision making index, a comprehensive index has also been presented. It was paid to measure financial irregularities. In this regard, the companies admitted to the Tehran Stock Exchange in 2010 to 2019 were examined based on a sample of 167 companies. For this purpose, a questionnaire was prepared in line with the opinions of experts to measure financial irregularity and was distributed among experts. Multi-criteria decision-making method was used to give weight to each of the considered criteria. Also, in order to measure the relationships of the hidden variable, which in this research is financial irregularity, confirmatory factor analysis was used; The obtained results show that the proposed model is a suitable indicator for financial disorder.

liquidity is a fundamental aspect of stock market efficiency and in terms of methodology , most of the theories related to the structure of financial markets account for the implications of liquidity behavior more than other market characteristics . therefore , the central role of market liquidity in the form of prices , and reducing the costs and risks of sustainable development and stability of financial systems is important , so liquidity issue has attracted much attention in recent years in academic studies as well as in important publications . in this research , the criteria of each liquidity type are introduced and the relationship between them is studied . in fact , the main question of this research is what measure is the criterion for the selection of liquidity in tehran stock exchange . the purpose of this thesis is to evaluate and compare liquidity capability and design a model for explaining liquidity measures in tehran stock exchange with emphasis on 11 different measures . for this purpose , a sample of eight firms listed in tehran stock exchange ( tse ) during the period 1380 to 1389 were reviewed . to achieve the goal of this research , factor analysis - vikor 's numerical algorithm which is one of multi - criteria decision making methods is used .

In ‏this ‏study, ‏using ‏factor ‏analysis ‏technique ‏and ‏Delphi ‏method, ‏the ‏variables ‏affecting ‏credit ‏risk ‏were ‏selected ‏and ‏entered ‏into ‏the ‏data ‏envelopment ‏analysis ‏model, ‏and ‏the ‏efficiency ‏scores ‏of ‏Tejarat ‏Bank ‏legal ‏and ‏credit ‏companies ‏listed ‏on ‏the ‏stock ‏exchange ‏were ‏obtained ‏using ‏them. ‏Then ‏the ‏ranking ‏is ‏done ‏by ‏the ‏model ‏of ‏Fitch ‏Institute ‏and ‏using ‏the ‏results, ‏the ‏transfer ‏of ‏customers ‏in ‏different ‏groups ‏is ‏predicted ‏using ‏the ‏Markov ‏chain ‏process. ‏The ‏results ‏of ‏data ‏envelopment ‏analysis ‏indicate ‏that ‏7 ‏companies ‏were ‏identified ‏as ‏efficient ‏in ‏the ‏financial ‏approach ‏and ‏12 ‏companies ‏in ‏the ‏combined ‏approach. ‏The ‏results ‏of ‏the ‏Markov ‏chain ‏show ‏that ‏the ‏average ‏probability ‏of ‏stopping ‏at ‏the ‏current ‏rank ‏in ‏1400 ‏in ‏the ‏financial ‏condition ‏is ‏46% ‏and ‏in ‏the ‏combined ‏mode ‏is ‏53% ‏and ‏the ‏average ‏probability ‏of ‏improvement ‏of ‏the ‏companies ‏is ‏23% ‏and ‏the ‏average ‏probability ‏of ‏the ‏decline ‏is ‏20%. ‏Turns..

In the present study, he presented a statistical sample related to the information of legal and credit customers of Tejarat Bank, accepted in the stock exchange during the years 1398 to 1399. Using factor analysis technique and Delphi method, the variables affecting credit risk were selected and entered into the data envelopment analysis model, and the performance scores of law firms were obtained using them, and then ranked by the Fitch Institute model. Performing and using the results to predict the movement of customers in different groups using the Markov chain process. The results of data envelopment analysis indicate that 7 companies were identified as efficient in the financial approach and 12 companies in the combined approach. The results of the Markov chain show that the average probability of stopping at the current rank in 1400 in the financial condition is 46% and in the combined mode is 53%, the average probability of improving the situation of companies is 23% and the average probability of falling is 20%.

In this study the usefulness of expected credit loss of loan facility compared with loss impairment for predicting banks, future profitability was tested. The model of Altamuro and Beatty (2010) and Kanagaretnam et al. (2014) was applied for predicting banks, future profitability and for calculating fair value of loans was applied the model of Tschirhart et al. (2007) and expected credit loss is calculated by fair value of loans. The hypotheses of the study were tested through the panel data gathered from 18 listed banks in Tehran Stock Exchange.The findings of the first hypothesis of the research indicated that with 95% assurance loss impairment has a significant and negative relation with one year-future profitability and expected credit loss has no effect. The findings of the second hypothesis of the research indicated that with 95% assurance both of expected credit loss and loss impairment have a significant and negative relation with two year-future profitability. Also the size of assets has a significant and positive relation with one and two year-future profitability.

One of the variables affecting the behavior of enterprises is the exchange rate. Uncertainty about the amount of exchange rate volatillity for each firm is considered as a risk. The aim of this study is to explain a model to investigate the effect of exchange rate shocks on the financial sustainability of export-oriented companies. In this regard, the data on exchange rate, tax, oil revenue and export variables on financial sustainability was collected for 19 groups of companies from 2008 to 2019. To achieve the research goal, the Panel Vector Autoregressive Model (PANEL VAR) using the generalized method of moments (GMM) was used to analyzed the data. Then the results were interpreted using the Impulse Response Function and variance decomposition. The results of the IRF show that the effect of exchange rate volatility on the financial sustainability variable is initially negative, but has a positive effect over time and is neutralized after several periods. The same goes for an impulse equal to a standard deviation in tax. Also, the oil revenues and exports impulse have negative and positive effects on financial sustainability, respectively. According to the results of variance decomposition, it can be said that the effect of exchange rate on financial sustainability is greater than the effect of sustainability on exchange rate, because the exchange rate shocks have more explanatory power for sustainability fluctuations.

The purpose of this research is to examine the effect of ownership structure and audit features on the financial distress likelihood by considering the moderating effect of managerial ability. This study utilized partial least squares structural equations modeling (PLS-SEM) analysis and data from 107 firms listed in the Tehran Stock Exchange. Audit features measured by auditor size and audit opinion and ownership structure measured by the block-holder ownership and institutional ownership. Backward logit analysis was used to calculate the financial distress likelihood. DEA technique and Tobit regression were used to measure the managerial ability. The results of the study show that audit features have a positive effect on the likelihood of financial distress. Moreover, the effect of ownership structure on the financial distress likelihood and the moderating effect of manage-rial ability were not confirmed. This paper offers evidence on the extent to which distress is associated with corporate governance and managerial ability from a developing country. The paper should be of interest to the regulatory bodies and practitioners because in many developing countries the implementation of corporate governance mechanisms is voluntary and is not yet required.

An investment manager puts the investment fund in a stable position before the market rises and falls. With this approach, in this study, an attempt has been made to model the factors affecting the timing of liquidity in Iranian mutual funds using Structural Equation Modeling (SEM). To achieve this goal, the required information was collected by survey and by designing a questionnaire from investors, experts and specialists in the Iranian capital market for the year 2020. Based on the results, external factors (with a path coefficient of 0.281) and internal factors (with a path coefficient of 0.419) have a significant effect on the timing of liquidity in mutual funds. The larger the coefficient of the path of internal factors indicates the fact that these factors have a stronger effect on the liquidity timing of mutual funds than external factors. Finally, the variables of interest rates on deposits, parallel market and stock returns, inflation rate, oil revenues, economic growth and political developments are external factors that respectively with path coefficients 0.786, 0.827, 0.664, 0.506, 0.582 and 0.404 and the variables of fund management ability and skill, relative life and size of the fund, net value and percentage of cash assets of the fund, return, profitability and capital expenditures of the fund, risks facing the fund and the number of industries in the fund's investment portfolio are intra-corporate factors that respectively with path coefficients 0.756, 0.426, 0.736, 0.553, 0.767 and 0.580, have a significant effect on the liquidity scheduling of mutual funds.

 The housing market has been one of the most volatile sectors of the economy in recent times, experiencing periods of stagnation and boom. It is important to note that the housing sector is most closely linked to other sectors of the economy. With the recession, the whole economy will be in crisis. Also, the housing sector, given these features, has a stronger impact on investment and housing prices than short-term economic fluctuations, as well as its widespread and past relevance to other sectors, has the potential to generate growth and development in other sectors of the economy and can serve as an endogenous growth incentive. To play a slower role, and to stimulate, to stimulate economic growth in the short term and to drive the recession out. Therefore, further reflection is necessary in this section. Therefore, in this study, using the vector auto regression Time Series (VAR) analysis model, we investigate the interaction between housing price markets of some macroeconomic variables such as liquidity volume, per capita income. The results showed that the volume of liquidity has a significant share in the volatility of the housing market. Therefore, policymakers in the economic field should pay more attention to this.

Empirical facts derived from research done on the effects of earnings management of listed companies shows that the economy of earnings management has always impose huge costs on economic, social and political experts provide organizations of all sizes. The role of crisis management on financial profit represents earnings management considers failure prediction models. The present study considers this failure in identifying explanatory variables and experimental model design, factors that this research is trying to improve.In this study, 13 variables affecting real earnings management and 56 variables affecting accrued earnings management were included in the model. According to the output of the results, it can be said that profit management in Iranian stock companies is a multidimensional problem; Because the variables related to profitability, liquidity and debt index affect this type of management.The multidimensionality of the factors influencing this process will require coordination between financial and capital market policymakers to reduce the effects of adjusting and reducing earnings management in the stock market.

Mutual funds are one of the types of financial intermediaries, including institutions that sell their investment unit to the public, raise funds and invest them in a variety of securities. However, managing mutual funds is fraught with complexities and difficulties that arise from achieving optimal returns and cash flow management as the most important management criteria. Market scheduling, meanwhile, is an important dimension for mutual funds. With this approach, in this study, an attempt has been made to identify and rank the factors affecting the timing of liquidity in Iranian mutual funds. The results of the study showed that the returns of parallel markets and stocks (weighing 0.206), bank interest rates (weighing 0.194) and political developments (weighing 0.193) are the most important external and macroeconomic factors that affect liquidity and liquidity timing in mutual funds. In addition, among the internal factors, the three variables of ability and management skills of the fund (weighing 0.206), net value and percentage of cash assets of the fund (weighing 0.1734) and the risks facing the fund (weighing 0.1726) are the most They have had an impact on liquidity and the timing of liquidity in mutual funds.

Since investors’ behavioral bias is a relatively vague concept, its accurate definition and measurement are extremely challenging. Furthermore, the common asset pricing models do not take into account the effect of behavioral biases in portfolio assessment. However, the dawn of behavioral finance undermined all the foundations of rational finance yet it did not result in an independent paradigm for explaining the inefficiencies. This concept also led to this major question among the investment advisers: How the advice about buying, maintaining or selling an investment shall be offered based on theories or the immeasurable behavioral biases? Attempts to quantify the biases and use them in the mathematical models became the subject of behavioral finance. Noise is one of the difficulties in finding the dynamism factors of financial market behavior. The chance events that occur round the globe are constantly changing the values but extraction of these chance events from the possible definite forces is difficult. Therefore, this study is an attempt to propose a mathematical model for measuring biases and its application to behavioral optimization in portfolio selection.

The purpose of this study is to investigate the factors affecting the stock price crash risk of listed companies between the years 2009 to 2016. Based on this, the researcher first calculated the stock price crash risk based on two different criteria and then tested the internal and external factors of the company on the crash risk. The statistical model used in this study is regression model and data type is panel data type. Dependent variables include calculating stock crash risk based on the first criterion, the Hutton model, which considers the monthly price fall in a fiscal year for a company when that company experiences a monthly return of 3.2 standard deviations below the company's average specific monthly return for the entire fiscal year and second criteria, Chen model, Based on the negative skewness criterion in the company's stock returns, Independent variables include in-company factors (financial ratios) and external factors. Based on the findings of the present study, there is a significant relationship between dependent variables and factors within the company and the organization external factors, can help in predicting stock crash risk.

Stock price crash have been described as a severe negative event in stock returns, causing major losses in shareholders' wealth and a loss of confidence in the capital market. This study sought to investigate the stock price crash risk of 114 companies listed on Tehran Stock Exchange within the years 2009 to 2018 on the basis of Bradshaw et al EXTR-SIGMA (2010) and Chen et al. NCSKEW (2001) criterion. Accordingly, the researcher first calculated the stock prices crash risk based on two different criterion and then tested the internal and external factors of the company on crash risk. The statistical model used in this study encompassed regression model and the data type is panel data type. Based on the findings of the present study, there is a significant relationship between the dependent variables (the first and the second criteria for calculating and predicting stock price crash), the factors within the company (company features and financial ratios) and external factors such as dollar market price, volume of shares traded, Iranian oil price and global gold price.

Credit risk issues and methods for identifying and predicting it have been constantly evolving over the past few decades. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financial losses to shareholders, creditors, investors and other people in the community. Advanced credit risk models that are based on market value include improving credit quality as well as reducing or decreasing credit ratings. In the present study, we have Investigated two models of advanced credit risk models, so two samples were selected, namely companies with financial problems and companies with financial health, in each group probabilities of default are estimated by two models which are KMV and ZPP, and then we compared probabilities of default. We have concluded that the ZPP model has more predictive ability than the KMV model. This method is denoted the Zero-Price Probability or simply the ZPP model. The main focus is on the new simulation based approach rather than the older established models.