فصلنامه دانش سرمایه گذاری
پیاپی 51 (پاییز 1403)

In the present study, stock price forecasts were evaluated based on fundamental, technical and economic factors. For this purpose, three groups of fundamental, technical and economic factors were studied. In data analysis, fitting of least squares error regressions was used for the share price data of 30 companies with more than 50% of the stock market value in 2020 and the stock prices of companies were analyzed unbalanced from 2002 to 2020. The results showed that each of the fundamental, technical and economic factors alone can predict stock returns, while the technical and economic factors did not have additional information content than the fundamental factors.

Today, profit rates and the possibility of managing and manipulating the profits are clear to all, and researchers have always sought solutions to remove the uncertainties facing investors and stakeholders when making their financial decisions. To clarify users' decision path of financial data users, Beneish (1999) has developed a profit-management predicting model that has yielded different results in different societies. Thus, this article aims to optimize and localize Beneish’s model by adding the Tunneling variable to Beneish’s variable and using a modern neural network and particle swarm algorithms. The statistical research population consisted of 196 companies listed at the Tehran Stocks Exchange from 2014 to 2019. The research method was a descriptive-library method in which the variables are interrelated through the causal-correlational method. From an objective point of view, it is an Ex-Post Facto research design. To analyze the data, the regression method and artificial neural and the PSO algorithms were used. The model analysis results suggested that all financial ratios had significant effects on Beneish’s profit management, as the Tunneling phenomenon and the financial leverage had the highest and lowest effects on predicting Beneish’s profit management, respectively.

Currently, due to economic fluctuations in Iran, the investment return of banks in Iran has undergone a major transformation. One of the major challenges facing bank investors is effectively allocating their money to projects and accurately assessing credit risk. Various factors affect the credit risk of banks. In this paper, the effective variables on credit risk estimation are examined and then the effect of credit risk on investment return performance is determined. For this purpose, three hypotheses were determined and the annual data of the member companies of the Tehran Stock Exchange in the period 2001-2021 were used to test the hypothesis. The study method has two stages, so that in the first stage, the Markov switching method is used to select variables affecting credit risk and for this purpose, the relationship between important indicators such as financial development and economic growth. Then, in the second stage, the important and effective variables selected in the first stage are used to estimate the credit risk and its impact on investment returns. Findings from the study showed that variables such as interest rate, inflation, ratio of domestic credit to private sector and exchange rate have a significant and positive effect on credit risk and variables such as foreign direct investment and annual real GDP growth have negative and significant effect on credit risk and credit risk has a negative and significant effect on investment returns.

Money laundering is an illegal activity in which the proceeds of wrongdoing enter the global economy and gain legal legitimacy. The effects of money laundering on the economy can be mitigated by planning programs and solutions. This phenomenon causes serious damage to a country's economy in the long run, and the existence of money laundering in a country's economy indicates a structural weakness in that country's economy. Therefore, the purpose of this study is to predict the causal relationships between organizational risk management structures (control environment, risk assessment, control activities, information and communication and monitoring) and money laundering risk of organizations. The statistical population of this study includes company managers, auditors and faculty members of universities (experts in the field of capital market, banking and auditing) and a standard questionnaire was used to collect data. After performing the reliability and validity tests of the sample data, the relevant analyzes were performed based on the structural equation modeling approach. The results showed that money laundering risk of organizations is affected by organizational risk management structures (control environment and information and communication).

 Managers and shareholders engage in Financial information quality and conservatism in order to maximize benefits and maintain collaboration. Or for whatever reason (perhaps morally) they refrain from doing so. The purpose of examining this conflict and cooperation between managers and shareholders of listed companies using game theory is to find a balance point in which the manager and the shareholder are satisfied as the main elements of the game in order to maximize their interests. Accordingly, this study seeks to find a strategy to maximize the equilibrium benefits of managers and shareholders by applying strategic features of accounting information and accounting conservatism. The method of data collection is the method of document mining during the period (1391-1391) and the method of data analysis is inferential and the software used to prepare the data and estimate the models is SPSS. The test results of the research hypotheses show that the combination of high conservatism strategies - high reporting quality and low conservatism - low reporting quality - are the equilibrium points (Nash equilibrium) in the game between the manager and the shareholder. The results show that game theory plays an important role in the relationship between managers and stakeholders; and finding the equilibrium points of the game can play an effective role in the decisions of the game parties (managers and shareholders). In this way, it informs the parties of the game of the strategy that has been most desirable and beneficial for them.

 Investment in projects is one of the factors of economic growth and sustainable development in countries. Since investors are usually exposed to different risks and due to the importance of risk in selecting projects, it has always been focused on the optimization of project selection and optimization techniques to reduce risks. The main risks associated with investment projects are divided into market and political risk groups, which can lead to decrease in productivity and increased cost in a capital project .Market risk consists of four risk factors: commercial risk, project progress risk, vector gain risk and construction risk. The aim of this paper is evaluation and ranking of market risks in selecting different types of capital projects based on mathematical programming model with DEA / AHP combined technique so that according to the relative weights, the overall impact of market risk on project prioritization is determined. After the implementation of the proposed algorithm, the risk of advancing the first priority, risk of construction / completion of second priority, risk taking and commercial risk were placed third and fourth priority so that investors can identify and reduce their effects in projects.

It is very important to distinguish how the volatility in the return of assets occur. For this reason, in recent years, realized volatility and frequencies of daily volatility recognition studies have been developed. This study uses stock prices of 30 big companies of Tehran Stock Exchange during the years 1390 (2011) to 1394 (2016) and calculates the realized stock volatility during trading days using the HAR-CJ model to examine the effect of size and intensity of price jumps in predicting index volatility. The results showed that the development of HAR-CJ and HAR-RV-CJ models using the size and intensity of jump did not have a significant effect on improving the index volatility prediction but, to a small extent, the model prediction performance Adjusts for index volatility. Also, using intraday jumps instead of daily jumps, does not improve the performance of the prediction model.

The purpose of this study was to investigate the effect of firm size and financial leverage on the relationship between working capital financing and profitability in companies listed on the Tehran Stock Exchange using panel data during the period 2013-18, through the generalized torque method. (GMM). The variables of firm size and financial leverage are moderators whose effect on the relationship between working capital financing as an independent variable and profitability as a dependent variable is studied. The results of the study showed that there is an inverse U-shaped relationship between working capital financing and profitability. Also, the inverse U-shaped relationship between working capital financing and profitability is weaker in firms with small firms than in large firms. Also, the inverse U-shaped relationship between working capital financing and profitability in companies with high financial leverage is weaker than other companies. In other words, the relationship between profitability and financing through working capital is adjusted by the financial leverage and size, and this adjustment goes to a certain extent and is reversed from then on, which is the breaking point. The relation series is U-shaped.

Choosing the best method for implementing infrastructure projects is always the main concern of governments, especially the governments of developing. One of the main issues in the field of oil projects is the supply of capital for these projects. According to the international oil companies and national oil companies, how and in what way will attempt the funds required for the implementation of oil projects, Outcome and financial effects also, consequently, will be different. Up to now, various methods have been implemented for this purpose. In general, financing is divided into two parts: Corporate financing and project financing. In This paper is paid to examine the contractual terms of financing a project looking at the oil and gas industry as well as a quick look at the Foreign Investment Promotion and Protection Act (FIPPA) and its implementing regulations to attract foreign investment for projects in the country

Non-financial data may refer to variables that represent the dimensions of the company's management. Company size and industry are other non-financial dimensions used when assessing business risk. In this regard, the purpose of this study is to explain the effect of micro and macro factors (specific characteristics of the company, industry characteristics, corporate governance, ownership structure and macroeconomic variables) on business risk in listed companies on the Tehran Stock Exchange. In order to achieve this purpose, 1752 firm-year (146 companies for 12 years) observations collected from the annual financial reports of listed companies on the Tehran Stock Exchange during the period 2007 to 2018 have been tested.Findings show that firm size, firm liquidity, firm profitability, firm growth opportunity, firm size, number of firms in industry, board independence, existence of audit committee and management ownership have a negative effect on business risk. while debt ratio and the exchange rate have a positive and significant effect on business risk. The results also show that statistically, firm life, industry decentralization, board size, duality of CEO duties, board financial expertise, audit committee size, audit committee independence, audit committee financial expertise, ownership type, Institutional shareholder ownership, major shareholder ownership, government ownership, interest rates and oil price growth have no effect on business risk.

In view of the developments that have taken place in the field of commercial law, the issue of Mergers and Acquisitions of companies can be considered as a legal-commercial necessity. Nevertheless, the acquisition of companies is a new issue in Iranian legal system. Although, in the Iranian legal system, the issue of Mergers and Acquisitions of companies and its types is not defined in the form of a specific legal structure, and it is not mentioned in the Iranian commercial law, but in the law of cooperative companies and in the eighteenth chapter The merger law is slightly mentioned, however, it is also briefly mentioned in the proposed new (Commercial Act) Bill. This legislator approach to the two processes of Mergers and Acquisitions has caused these two processes to be confused with similar concepts. Therefore, in order to understand a subject, in addition to providing definition and enumeration of elements, compare with similar institutions and expression, prevents them from mixing. In the field of company law, there are institutions that have similarities with Mergers and Acquisitions that are significant, such as conversion, division, demerge, Split of a company, and corporate combination. The current study seeks to show that the concepts of Conversion, Division, demerge, Split of a company, and Corporate combination are different from Mergers and Acquisitions, and each of them has specific legal effects and consequences.Keywords: Merger, Acquisitions, Corporation, Division, Conversion, demerge, Split of a company, and corporate combination

The present study investigates the relationship between acquired factors and monetary disorders for the first time in Iran. The statistical population of the banks are members of the Tehran Stock Exchange. The sample size is based on new methods based on experiments and using sample power software and according to the type of research relationship hypothesis which is a combination of two scale variables but abnormal, Spearman test has been used. The first hypothesis of the research based on the relationship between the two variables of financial knowledge and monetary disorders showed that there is no significant relationship between these two variables and the first hypothesis of the research was not accepted. However, based on the results, the second hypothesis has a significant relationship between the variables of attitude to planning and monetary disorders, which shows a negative relationship between the variables. The second hypothesis was accepted as research. Therefore, based on the acquired origin of variables has monetary disorders.

The present study analyzes the content of financial risk management studies in Iranian banks. The main purpose of the research is to provide a conceptual framework, create a database and provide a comprehensive picture of the current state of the research. The present study is applied, review and retrospective and the data were collected by document analysis. The statistical population of the research includes 509 articles that have been published in scientific research and extension scientific journals approved by the Ministry of Science, Research and Technology between 2005 and 2019. This research presents a conceptual model for banking risk studies with a descriptive approach and content analysis. The content of the research has been reviewed and analyzed based on the analysis of journals, time course, keywords, thematic literature, objectives, data collection method, analysis tools, evaluation models, research variables, statistical tests and thematic trends in previous researches. Credit risk, practical purpose, correlation analysis, archival method, ivory software, statistical method, regression test, dependent variable of default probability and independent variable of interest rate had the highest frequency in articles. Sanctions, individual and social norms, cultural values and inclinations, climatic and geographical conditions, ethics, religiosity and family values that may contribute to risk were not found in the content of the articles.

The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, the amount of systematic risk can be very different from the expected amount, due to the confusion in stock price changes, resulting from emotional transactions, overreactions and price manipulation. Therefore, it is necessary to control the effects of these disturbances in measuring systematic risk. The method of the present study is descriptive-correlational which was performed using statistical methods to examine the relationships between variables based on Ives software. To analyze the data in this study, it is suggested to use Kalman filter. Also, filtered and turbulent values have been used under the heading of unobserved systematic risk. According to the obtained result, it can be said that all variables have a significant relationship with the systematic risk not observed in the model. Then, using data analysis, the hypotheses were examined. The results obtained in relation to statistics and a significant level show the confirmation of all hypotheses in terms of the impact of economic variables on the components of inflation, economic growth, exchange rate, stock market index and volume. Money showed unprecedented systematic risk. Also, the effect of different variables and finally the estimation of coefficients showed that the highest coefficient among the variables is related to inflation index and stock market.

The spread of the corona virus has led to negative reactions of financial markets in different countries and the fall of indices. The purpose of this research is to investigate the stock price index in selected groups of the capital market in Iran in this period and provide a model to predict the index. In this research, using the panel data regression method using Arch. GARCH has been used to investigate the stock price index in twelve selected groups of stocks with twelve different hypotheses in 189 companies in a two-year period (2008-2018). The results showed that Corona has a negative and significant impact on the price index of all groups except the pharmaceutical group. Also, vaccination has had a negative and significant effect on the price index of most groups. However, this factor did not have a significant effect on transport, communication devices, multi-field holdings, basic metals, and also technical engineering services ultimately. This means that the spread of this disease and its results, such as the number of deaths, have had major consequences on the return of the capital market in Iran.

One of the most vital research programs of financial knowledge today, which is at the forefront of rejecting the theory of efficient markets, is financial behavior theory, which is the cause of joint efforts between financial sciences and social sciences and has deepened our knowledge of financial markets. Today's financial topics, which we are going to explain, describe and compare, are called financial behavior, which in simple terms is a pattern of thinking in which markets use patterns consisting of social sciences, psychology, finance and several other disciplines. They are studied, and in other words, economic agents are not rational in behavioral patterns contrary to neoclassical theories, but are normal either because of their preferences or because of cognitive biases. The purpose of this study is to design and explain a model for identifying behavioral factors affecting stock price fluctuations in the Tehran Stock Exchange. This research is applied in terms of purpose and in terms of working method is a type of survey research. The data of this research were analyzed using SmartPLS software. The results of the study showed that the emotional bias of short-sightedness, the emotional bias of optimism and the emotional bias of adaptation affect the fluctuations of stock prices of companies.

The purpose of this research is to investigate the mediating role of suppressing managers' opportunistic behavior in the relationship between shareholders' loyalty and capital market efficiency. the time scope of the research is the years 2015 to 2021.In this research, 143 companies have been considered as a statistical sample of the systematic elimination method Findings In the first hypothesis of the research, it indicates a significant relationship between the loyalty of the shareholders and the efficiency of the capital market, so it can be said that if the loyal shareholders behave analytically and logically, we can witness the efficiency of the capital market. In the second hypothesis of the research, this result We found that the loyalty of the shareholders leads to the suppression of the opportunistic behavior of the managers. It is possible that the owners can reduce the opportunistic behavior of the managers by establishing the conditions that certain accounting methods are used for certain purposes. We found that suppressing managers' opportunistic behavior can lead to capital market efficiency. In this way, the managers will not use available and private information for their personal interests and will consider the interests of all owners and will move the market towards efficiency. in the main hypothesis of the research, which is the goal of the research, we came to the conclusion that the suppression of the opportunistic behavior of managers is a mediator. It has a relative clause.

The main aim of this study is to present a pattern for determining and measuring investment efficiency in accordance with the market conditions of Iran. To do so, studying previous studies and thematic literature, 17 variables were identified to present an optimal investment efficiency model. Using panel data and the use of eviews9 & stata 14 software, it was suggested to provide a concrete investment efficiency pattern based on the cash flow of investment activities was undertaken. The statistical population of this study includes 129 companies listed on the stock exchange during the time period of 2007- 2016. Finally, the final model of the research, with the abbreviation title of (ineff) and the participation of 11 variables including company size, leverage, company's age, Qtubin, sales growth, return on assets, ratio of operating profit to assets, ratio of operating cash flow to assets, liquidity ratio, standard deviation of operating cash flows and cash ratio with a coefficient of 45% was estimated

Due to the economic problems and the government's special view on tax revenues in recent years, the discussion of changing the method of tax collection and creating an optimal method that both realizes tax revenues and solves the problems of the current tax collection method is of particular importance. This article examines the role of tax based on bank transactions in increasing government revenue. The required information is obtained from the budget deduction reports and financial statements of stock companies based on the 1872-year company- information. The trends related to Expressed tax, diagnostic tax, definitive tax are drawn and finally the difference between fixed taxes and taxes from FTT is calculated based on statistical tests and the results show that for all years the difference between fixed revenues and revenues from FTT is at significant levels and the differences are confirmed. Thus, FTT will improve tax collection and largely correct the current erosive process.

Information ambiguity is defined as ambiguity about the lack of information or the multifaceted nature of the information. The amount of reaction to ambiguity varies from person to person and they will perform unique trading behaviors. Therefore, the aim of the research is the transactional behavior of investors under the conditions of information ambiguity and behavioral fluctuations. For this purpose, the present study was conducted with 90 sample companies in the period 2012-2018. The results showed that there is a positive and significant relationship between the ambiguity of asymmetric fluctuations in yield and short-sightedness, and there is no significant effect with prominence. There is a significant relationship between information ambiguity, asymmetric yield fluctuations and transactional behavior of earnings and risk aversion, and there is no significant relationship with risk taking. There is no significant relationship between ambiguity of information distribution, profitability distribution and transactional behavior of return on profitability, risk aversion and risk taking. Short-sighted behavioral fluctuations have a complete mediating effect on the relationship between information ambiguity, asymmetric yield fluctuations, and risk-averse trading behavior. No mediating effect was found on other traumas and information displacement.

Four major approaches to financial analysis can be defined. Traditional, Ultra -Traditional, modern and postmodern approach. In the novel theory of business resilience system, in measuring financial risks or otherwise, conditions are provided that by comprehensiveness and also considering the rule of contingency paradigm, the possibility of measuring financial indicators and other cases on a case-by-case basis. Or comprehensive, be provided. Or comprehensive, be provided. Statistical data of listed companies in the period 1390 to 1398 were used. In this study, using different methods based on innovative financial instruments, the power of these instruments in estimating financial distress, traditional, ultra -Traditional, modern and postmodern perspectives are compared. Finally, it was found that the financial engineering method, relying on the theory of business resilience system in determining financial distress, reduces the fluctuation of the estimate and increases the accuracy of the estimate of financial distress. Of course, along with new methods, traditional methods should always be considered as indicators to determine the extent of financial distress and for comparison.

The purpose is to provide a model of financial resilience of the hotel industry in crisis in Iran. This research was conducted using the mixed method research of exploratory type. In the qualitative section, the grounded theory method, based on Strauss and Corbin's paradigm model, was used. Semi-structured interviews were conducted with hotel experts and continued until theoretical saturation based on the snowball technique. From 982 key phrases obtained from the interviews, 86 concepts and 18 main categories were obtained. The qualitative evaluation of the model was carried out and confirmed according to the opinion of Strauss and Corbin in all dimensions. In the quantitative evaluation of the model, structural equation modeling and SmartPLS software were used. All significant numbers were greater than 1.96 and standard coefficients were greater than 0.4 and the model was approved. Considering that the data fitting criterion was 0.603, the fit of the final model was confirmed. The most important findings of the research were identified in the field of financial resilience strategies of the hotel industry in crisis conditions, strengthening of human resources, strengthening of inter-institutional cooperation, tourism industry marketing, optimal financing and innovation. The most important findings of the research were identified in the field of financial resilience strategies of the hotel industry in crisis conditions, including: strengthening of human resources, strengthening of inter-institutional cooperation, tourism industry marketing, optimal financing and innovation.

The purpose of this research is to identify and prioritize the key indicators of financial technology evaluation in Iran's banking industry based on the DNAP technique, In this research, using a mixed-method design. This research is exploratory-descriptive based on the method of data collection and nature and development-applied in terms of purpose. In order to achieve the goals of the research using the snowball method, the opinions of 12 banking experts and university professors were used until the theoretical saturation stage. The process of data analysis was done in two stages. First: Identifying the key indicators of financial technology evaluation in Iran's banking industry through interviews and using thematic analysis method; Second: Determining the effectiveness, effectiveness and the degree of importance of the components through the questionnaire and DNAP method. The results of the research showed that the key indicators for evaluating financial technology in Iran's banking industry are 20 sub-indices as well as six main indicators including, new revenue models, interaction of financial technologies with customers , organizational innovation, and financial technology, technological innovation, organizational innovation and new business partners. The results of this research can be considered and used in the evaluation of the financial technology in Iran's banking industry

This study investigates the analysis of Granger causality in mean patterns to measure the number of lags of the cross-correlation between the standard-residuals of returns and the volume of transactions during the crisis period. For this purpose, based on daily data from April 2020 to April 2021, structural breakpoints were first determined and then the relationship between the volume of daily transactions and price changes of the Tehran Stock Exchange was investigated using the GARCH-ARMA model. Finally, the causality was investigated in the average between returns and volume of transactions for each sub-period. The results showed when the prices fall sharply during the crisis period, market participants tend to use the volume of past transactions to predict current returns. Also, the results showed when there is an upward price movement in the post-crisis period, it is observed the correlations are significant from lag 2 to 20. These observations suggest causality-in-the-mean between both series occurs asymmetrically after the crisis period. Such asymmetric behavior supports the trader heterogeneity hypothesis from two perspectives, firstly, the degree of significant cross-correlation between the standardized residuals of both series is stronger in the highest interval before the crisis than after the crisis. Second, the time frame for past trading volume to correlate with current returns becomes longer after the crisis. The results of the research can be used to predict stock prices at a time when we are facing the fall of the stock market and the emergence of behavioral phenomena, especially negative market sentiments.

In this study, latent volatility modeling and Bayesian analysis of stochastic Volatility of intraday data of Tehran Stock Exchange index based on Markov Monte Carlo chain in uncertainty conditions (downward crisis of stock market index) have been developed. The method of the current research is a correlational description. For this purpose, at first, the distribution of the logarithm of the squared return as a measure of the realized volatilities was simulated using the stochastic Volatility model to obtain the latent volatilities, and then by using the hybrid MCMC-Copula model, the parameters affecting the stochastic Volatilities were identified and estimated in the training phase. Finally, using the results obtained from the training phase, in the test phase, the comparison of Copula and GARCH models was done. The results showed that the Copula Gumble, Galambos, Joe, Clayton and Frank provide similar and lower MSE and RMSE indices than the GARCH base model, and therefore the model based on copula provides the possibility of serial dependence in the latent volatility process. The findings of the current research can be useful for financial and investment companies for portfolio management and portfolio management in different conditions of market volatilities in order to achieve the investor's goals and increase the value of the portfolio.

Financial inclusion means the extent of the level of access of people in the society to financial services and it is important for countries as a measure to measure financial development and economic growth. Governments have gone towards the use of financial technologies to develop financial inclusion in the society. Therefore, the purpose of this research was to investigate the impact of fintech on financial inclusion in Iran, and the relationship between them was discussed by presenting a model. The data related to financial inclusion and financial technologies were collected from the website of Central Bank of Iran in the period between 2006 and 2022. The research hypotheses were analyzed based on a linear regression model of the OLS method. The results of the model showed that there is a positive and significant relationship between fintechs and financial inclusion. The findings of the research show that the development of fintechs in the banking industry, especially in recent years, has led to the development of financial inclusion in Iran and fair and equal access to financial products and services for people in the society (which aims the main one is financial inclusion) and with the expansion of financial inclusion, financial deprivation in the society has decreased.

Due to the importance that investors place on the return of their shares, the phenomenon of falling share prices leads to a decrease in returns. Many researchers believe that the changes in the company's stock price originate from its internal information management. Since the stock price changes not only through financial information but also through social, governance, economic and environmental information, therefore publishing a special report such as the governance dimension of sustainable performance reporting can affect the liquidity of stocks and the crash risk. Using the structural equation modeling approach, the present research seeks to predict the crash risk of stock price and its liquidity through governance sustainablity reporting and the forecasting accuracy and earnings comparability. Using the systematic elimination method, 147 companies listed on the Tehran Stock Exchange for the period of 2011 to 2014 selected as a sample. PLS software used to analyze the data. The results showed that the governance component of sustainablity performance reporting leads to an increase in the comparability of earnings, an increase in the liquidity of stocks and a reduction in the crash risk of stock prices. Other findings showed that the comparability of earnings has a mediating role on the relationship between the reporting of sustainable governance performance and the crash risk of stock and liquidity. Meanwhile, the accuracy of the earnings forecast does not have a significant effect on the crash risk of the stock price and the liquidity.

Identifying and prioritizing factors affecting financial resilience in Tehran Stock Exchange companies in order to prevent bankruptcy.The research method is exploratory from the point of view of the practical goal and the method of data collection, and the data analysis mechanism is based on meta-composite method and focus groups. Papers related to financial resilience including 40 articles and works were selected and analyzed based on valid criteria among 110 articles and works. The second statistical population included experts in the field of financial resilience, who were finally determined to be 10 people, and due to the conditions and limitations of the Corona pandemic, they provided opinions and suggestions remotely. By applying the seven stages of metacomposition, a conceptual model was obtained in six conceptual layers, categories and codes. Concepts and topics were included in each of the layers, and finally 28 categories were identified. In order to validate the quality of the obtained model, based on the opinions of experts, it was obtained in the form of focus groups, and the conceptual model was approved by the research experts. According to the findings from the implementation of the hybrid process in identifying the dimensions and categories of financial resilience, which can be a basis for future researches in the direction of how to implement financial empowerment policies and maintain financial resilience in

Human physical, emotional and mental abilities do not have a linear trend and differ from each other in different time periods. The science of biorhythm is a set of mental, emotional and physical curves that determine different human states in a sinusoidal form from birth to the end of life and is therefore one of the most important human discoveries. The important question that arises is whether the state of human biorhythm influences her decision in the stock market and her cognitive function and follows a certain pattern or not. The purpose of this study is to draw an analytical model to explain the effect of biorhythm cycle on investment. The statistical population includes 384 capital market investors in Tehran. After collecting the questionnaire, Kolmogorov-Smirnov test, ANOVA and Pearson correlation were used to analyze the data. The results show that there is a significant relationship between the physical, mental and emotional dimensions of biorhythm with the decisions of stock market investors and the effect of investors' biorhythm status on their cognitive performance is positive and significant. In other words, the biorhythmic status of stock market investors can play a role in their decisions. The results are in line with previous research.Key words: Physical biorhythm, Mental biorhythm, emotional biorhythm, cognitive function.

This research is a sequential mixed study in the sense that qualitative data from the literature review is first collected through in-depth interviews and then analyzed. After collecting the data and identifying them, the coding stage was done using the Swara method using the opinion of experts. The data was collected according to the reliable information and data of large companies accepted in the stock exchange and the Kodal system, and the reports and financial statements of the aforementioned machinery and equipment industry companies were used. The examined experts are all managers and experts of machinery and equipment industry companies and university professors, who are somehow considered experts in the concepts of the current research.In general, the main goal of this research is provide a model of the financing supply chain that can identify the optimized indicators influencing the financial supply chain in order to improve its performance and introduce the degree of influence of each one.This research creates a model of the financing chain that studies the management and control of risk and obstacles and bottlenecks, as well as the effects of the financing decision, and the relationship between the management of the financing chain and finally shows what Factors can improve and upgrade the production cycle and affect the performance of the company.

The present study aimed to evaluate the smooth behavior of individual investors in the Iranian capital market and the factors affecting it with a complex network approach. The statistical population of this research is limited to explaining the model, decision-making, and selection of the optimal capital combination including 246 mutual funds on the Tehran Stock Exchange. The research method is based on the factors identified from the research sources and according to Christie and Huang model with emphasis on complex networks, and Eviews and Matlab software to explain the model in which according to the research variables, and changes in cross-sectional stock returns of the method Arch and Garch have been used to calculate the herd-like behavior with a complex network approach. Finally, the results of this study show that the herd behavior in individual and institutional investors in the Iranian market has been approved in the period 1393 to 1398. It can be clearly seen.