فصلنامه دانش سرمایه گذاری
پیاپی 37 (بهار 1400)

There are different theories in capital structure litreture witch describe financing behavior of capital structure. Trade-of and pecking order theories, as two famous capital structure theories, make diffrent explaination for capital structure adjustments. Recent studies find evidence that support the idea of using both theories simultaneously would help explaination ability of capital structure adjustment model. So in this way, examining adverse selection cost while moving toward optimal capital structure can make better designation of capital structure adjustment models. Using partial adjustment mode, this research investigate factors influence adjustment speed of capital structure toward optimal leverage ratio. We examine impact of cashflow inbalances, industry concentration, industry munificence and industry dynamism on speed of adjustment by using fixed effects regression and generalised method of moments. Our sample consists of 155 companies listed in Tehran Stock Exchange for the period from 1385 to 1394. We find that for above-target firms, adjustment for firms with financial surpluses is faster. For concentrated below-target firms, adjustment speed would be slower than other firms. Also dynamic above-target firms have strong tendency to adjust their leverage by reducing it.

Among the important producers and financial organizations in the national economy, the country's major producers, including petrochemicals and refineries, have an important role in improving efficiency and preventing crude oil. In this regard, managers of these organizations are struggling to improve efficiency in light of the economic conditions. The classic approach of data envelopment analysis models takes into account the linear pricing performance for inputs and outputs in the evaluation. In this paper, we examined the efficiency of the top ten petrochemical companies in the year 1395 by modeling with the help of auxiliary variables and nonlinear values ​​of inputs and outputs. An important feature of the proposed model is that it considers nonlinear values ​​of inputs and outputs. In the DEA total analysis, all weights are taken linearly They can not show the reality of the issue in many practical applications.

Researchers previous research show that the existence of appropriate corporate governance mechanisms increases the quantity and quality of information disclosed by the company and, as a result, reduces information asymmetry. Foreover, as information asymmetry decreases, market liquidity increases. Accordingly, the purpose of this study is the impact corporate governance strength on stock market liquidity in listed companies on Tehran Stock Exchange. For this purpose, a sample of 120 companies during 2011-2017 was selected by systematic elimination sampling. The research method is library and correlation. Following Al-Jaifi et al. (2017), eight corporate governance features are used to measure corporate governance power and three different indicators (including Amihud’s measure, transaction volume, and bid-ask spread) are used to measure stock liquidity. Analysis and testing of hypotheses have been done with the help of generalized least squares regression (EGLS) and with panel data approach. The results show that there is a positive and significant relationship between corporate governance strength and stock market liquidity based on triple criteria, Amihud, Share turnover ratio and bid-ask spread.

Statistical arbitrage as one of the subsets of algorithmic trading refers to strategies that employ some statistical model or method to take advantage of what appears to be mispricing between assets while maintaining a level of market neutrality. One of these strategies is pair trading that implements on two related long-term(co-integration) financial assets. The pair trading strategy of the research is based on the description of the visible process, the remainder of the co-integration model in terms of an invisible mean reverting process. This representation is in a state-space model and solved by the Kalman filter approach and the time of buying and selling is calculated in terms of two probabilities of growth and fall. The profitability of pair trading strategy on 21 stocks from oil product index and basic metal index of Tehran Stock Exchange between 1390-1395 was evaluated according to return and Sharp ratio. The results of the research show that the research method has the daily returns of 0.0048 and Sharp 1.23, which is more profitable in comparison with the pair trading based cointegration and market performance but the average daily its return is in the second place after the co-integration method.

One of the features of a financial market, the stock market in particular, is its affectability from other financial and non-financial markets. regarding the importance of this issue, the present study aimed at investigating the dynamic conditional correlation (DCC) between the returns on the domestic and foreign assets in monthly data (oil, industry, exchange and base metals including total, copper, steel) and returns on the stock price index in Iran during March 2001 to April 2017 using the DCC-FIAPARCH approach. The obtained results indicated a statistically significant and positive DCC coefficient difference between the metals, industrial products, and copper returns with the stocks returns. Consequently, it is not possible to put each of these assets with the stocks in an identical situation (purchase or sale), but instead they should be always placed in opposite situations for the purpose of risk control. However, with regard to other assets, the DCC was not significant; accordingly, the assets can be placed in the investment portfolio together with the stocks although the presence of such assets in the given portfolio did not help to reduce the portfolio risk.

Given the large number of investment funds, their different performance in the past and their different characteristics, choosing the appropriate investment fund is important for investors. In addition to past performance including risk and return, there are several structural and behavioral factors that can affect the return on investment fund. These factors can include size, fund costs, management fees, portfolio turnover ratios, cash flow, fund life, focus, location, experience and management skills, gender management, volume of transactions, governance structure of equity funds, etc. On the other hand, if the factors affecting decision making are known, the process of analyzing, interpreting and selecting the fund is also unknown.

Cloud computing is one of the technologies of providing services and services that has a high potential for organizations that, in addition to reducing the cost of information technology, improves the way of attracting and retaining customers. The main objective of this research is to analyze the criteria for improving efficiency in Cloud computing services. The statistical population of the study is the experts in the field of information technology in universities. The tools used were interviews and questionnaires. A total of 25 questionnaires were distributed among experts. Finally, 21 questionnaires were gathered. Data were analyzed by the DEMATEL method. By analyzing the data, it was found that among the six criteria introduced, the economic factors criterion with the highest total line had the most impact on other components of the efficiency improvement of cloud computing systems and organizational factors with the highest coefficient The weight is among the other criteria and has the most impact on the whole system. As a result, the use of cloud computing technologies to reduce costs and increase efficiency in the optimal use of hardware issues within the organization has attracted the attention of managers. Cloud computing management software stores storage hardware resources and improves the efficiency of the network and improves the power consumption by employing them in an accurate and timely manner.

The present study attempts to investigate the turbulence of parallel markets of capital markets on stocks of Bourse banks. In this study, the visibility of bank metals has been measured separately from parallel markets of foreign currency and gold, as well as oil market as an independent market. In this regard, the method of self-regression vector analysis (VAR) and self-regression model are used to determine the heterogeneity of generalized multivariate variances (MGARCH). The data of this research have been compiled using Eviews software from the beginning of July 2012 to the end of September 2012 and tested. The method of this research is based on the classification of research based on the method, nature and direction are descriptive, applied and post-event respectively, and are considered as a correlation in terms of type. The results of this study confirm the relationship between the impact of bourse banks on parallel markets of currency, gold and oil. Accordingly, the main assumptions of the research that the stock markets of stock exchanges in the capital market are affected by parallel markets is maintained from two perspectives of return and risk.

Predict the Financial Limitations of Companies Accepted in Tehran Stock Exchange Using the Relief-Svm-Caiid methods Abstract Discussion of financial constraints is one of the key issues facing all companies. Predicting financial constraints is an important phenomenon for investors, creditors and other users of financial information. This research uses the information of 7 financial years during the period 2012-2017 and using financial information of 213 companies to study the factors affecting financial limitation and its prediction using artificial intelligence algorithm method (backup algorithm classification algorithm and the rule-oriented algorithm Chaid). In the first step, using the Relief Algorithm, among the initial research variables, five variables of the ratio of total operational assets to total assets, the ratio of total debt to the total assets, the kbitwin, the return on sales, and the ratio of institutional owners were selected as important variables in the company's financial constraint, respectively. The results also showed that the three-class support algorithm using selected financial data has the ability to predict future financial constraints with a power greater than 80% and more than the law-governed algorithm. Keywords: financial constraints, Machine learning method, financial variables and corporate governance jel: M41-B26-C63.

Multi-purpose Card in investment bank (branches in Tehran city) by five main factors including satisfaction, external variables, organizational factors, supportive factors, collaboration and coordination factors, and 28 indicators. The level of effectiveness of these indicators in the innovation acceptance of the research model is processed after designing a Likert-spectrum questionnaire and distributing it to 240 managers, experts and clients of investment Bank branches in Tehran, using the structural equations and LISREL software, which 5 factors with 23 indices were finally accepted. According to the research, a successful innovation acceptance in investment Bank requires consideration of all the above factors. The results also indicate that social factors of service innovation are of prime importance and special attention to social factor indices has a significant impact on acceptance of the multi-purpose card innovation in investment Bank.

One of the financial institutions of the countries in the world is the Stock Exchange, which is used as indicators of economic health. As for a large volume of capital is managed through the stock market and is placed in the production and industry, the recession in this market can have important effects. In this paper, we seek to extract the cycles of prosperity and recession in the Tehran Stock Exchange using the TEPIX and the Pagan and Sossounov method. Then, using the PSO algorithm, the most important predictor variables are determined and in the next step We predict market financial cycles using ANFIS, MLP, RBF and PNN networks. The results show that according to the mean square error, the root mean square error, the accuracy of the model and the Kappa coefficient, the MLP model provides better results in predicting future market conditions.

Today, one of the most important reasons for the effectiveness of the board of directors should be their composition and attributes such as size, independence of members, number of members in other teams, gender structure of the composition of the board, the average age of the combination, and such cases. The purpose of this research is to investigate the impact of the Board of Directors on the unlawful actions of the company. statistical data between 2011 and 2016 are among the companies listed in tehran stock exchange. The board's features and illegal actions of the company are considered as the variables of this research. statistical sample of the systematic method of all companies in tehran stock exchange The number of 21 companies has been selected. The research method was descriptive-correlational and historical data were extracted from financial reports and corporate reports, finally, the statistical analysis was carried out by Eviews software, version 9 and using the logistic model. The results of the research show that the characteristics of the board of directors have a significant effect on the company's illegal actions.

Due to the fact that all firms mangers’ decisions have financial effect, it is necessary to have at least the necessary knowledge of the financial rules (financial literacy) since they are effective in shaping these decisions. Financial literacy and its measurement in different classes of society have been the issue of many internal and global researches; however, financial literacy of firm executives was received less attention in Iran. The present study aims to identify the effective factors in shaping the professional financial literacy of firm’s managers. The paradigm of this research was interpretative. Because employing the life experiences of people involved in this subject, the financial experts were necessary qualitative research method and the phenomenological approach and Collaizi’s seven steps method h were utilized and data was analyzed with software Nvivo 8. A snowball sampling method was used as it belonged to targeted sampling method for selecting the sample of the study to achieve the theoretical saturation principle, and the final sample consisted of ten financial experts. Based on the results, eleven main components were identified in the formation of financial literacy of managers. These components are the recognition and analysis of financial statements, familiarity with the laws of social security and labor insurance, familiarity with tax regulations and trade law and familiarity with the laws of the stock.

The purpose of investing in stocks is to obtain appropriate returns and generally investors' decisions are based on risk and stock returns and are influenced by two factors: macroeconomic variables and microeconomic variables. Due to the high sensitivity of investors in obtaining the highest return on investment and selecting the best investment portfolio in the capital markets, a significant part of research in the field of accounting and finance, to examine the state of the capital market and before سهام The stock return is dedicated because the study of accounting variables affecting stock returns can be useful in assessing the future status of the company and its future stock returns. The present study examined whether an accounting-based fundamental analysis strategy can help investors perform better in their investment portfolio, using RSS and CORFS indicators. used. The statistical population of this study includes all companies listed on the Tehran Stock Exchange from 1387 to 1396 and the sample was selected through the method of systematic removal from the statistical population. According to the specific conditions, 118 companies were selected as a statistical sample of this study. It is worth mentioning that by performing ANOVA tests and designing multivariate regression models, the developed hypotheses were tested. The results showed that the formation and calculation of the RSS index can not achieve higher efficiency; By forming and calculating the CORFS index, higher efficiency can be achieved; Therefore, the CORFS index brings higher efficiency than the RSS index.

has not been raised in recent years, but has been the focus of researchers in recent decades. Different sources of financing make it possible to make the desired investment and can increase the wealth of shareholders. Therefore, considering the importance of risk in the financing structure, the purpose of this study is to model risk in accordance with the financing structure in the money market based on probabilistic decision theory. In terms of research method, this research is in the category of descriptive-analytical research of the time series type. The statistical population of the study is experts in the field of financial management of banks. In this study, after reviewing various literature in the fields of financial risks and financial ratios of banks, the most important risks were identified. A combination of two methods was used to collect data. By using the library method of the subject literature; A theoretical framework and background were provided for the research, and in the second stage, we modeled by collecting the opinions of experts. In this study, after collecting information, Ahp technique was used. The results showed that systematic risk has the highest priority. Liquidity risk is in the second priority. Income distribution risk in the third priority, operational risk in the fourth priority, capital risk in the fifth priority, credit risk in the sixth priority,Market risk in the seventh priority,Competition risk in the Eighth priority andMarket liquidity risk in the last priority. has it.

Designing and implementing a credit risk measurement model in the country's banking system will play an effective role in increasing the productivity of the country's banks in the optimal allocation of resources. Therefore, credit has an important role in the performance of the country's banking sector. Therefore, based on this argument, the present study designs and explains a model for the contagiousness of companies' financial distress risk and credit risk in the country's banking system. For this purpose, the limit (limit) theory of Akhtar and Dali (2017) research was used to measure the contagiousness model of financial distress risk. The hypotheses were tested using the statistical method of regression analysis with combined data using the information of 23 banks listed on the Tehran Stock Exchange during the years 2014 to 2019. The findings of the first hypothesis of the study indicate that there is a significant relationship between the risk of financial helplessness of banks and the credit risk of the country's banking system. Also, the result of the second hypothesis showed that the risk of financial helplessness of banks is transmitted to the Iranian banking system in the form of credit risk.

The present study investigates the role of asset characteristics, entrepreneurship and information in analyzing the financial structure of startups (Case Study; Campus Park Technoir. The purpose of this study is to investigate the effects of asset characteristics, entrepreneurship and information on the financial structure of startups. The purpose of this study was to describe the problem and importance of the topic in the first chapter. The statistical population consisted of all knowledge and technology companies based in Campus Technology Park, which sample size was determined using Cochran method of 148 people. It was confirmed by referring to the experts and experts of its validity and alpha method The reliability of the questionnaire was confirmed by Cronbach.This study was descriptive-survey in terms of purpose, applied, and inferential results from data analysis showed that between variables of asset attribute, information and entrepreneur attribute with structure Finance has a meaningful relationship, also considering the coefficient of determination obtained from Structural Equation test results, it can be concluded that asset attribute (0.514), entrepreneur attribute (0.405) and information attribute (0.362), respectively. There is a significant relationship with the financial structure of startups.

Holding companies, due to the nature and different investment decisions they face, are not in complete confidence and terms of decision-making and face various risks in an atmosphere of uncertainty. Since due to the structure of holdings, the main activity on investment and management is generally focused on companies called subsidiaries, risk management in subsidiaries is important because they are the risk management of investments made by holdings. Therefore, in this article, an attempt has been made to manage the risk of subsidiaries from the point of view of holding. Delphi methods (expert consensus) and case study and library studies have been used to extract and analyze the data. The result of this research is identifying the risk sources of subsidiaries of a holding company (active in cement industry in Iran), prioritizing these risks and finally, drawing a risk map of each company for the operation of the parent company.

If we want to divide startup companies into two general categories (1- Startup companies in the idea stage 2- Startup companies in the post-idea stage), we can divide the second category which has cash flow and physical assets by valuation methods such as value method. Net assets (NAV), book value (BV), present value of cash flows (DDM), etc., but are not applicable to the first category, which is in the early stages and lacks cash flows and physical assets. First, methods such as rating card valuation, Dave Brex valuation, aggregation of risk factors can be used. Research by experts, forensic experts, corporate stock valuation experts, etc., and looking for criteria and indicators that are suitable for valuing startups that do not have cash flows and physical assets, which ultimately led to the extraction of criteria and indicators that are appropriate. With Iranian culture and laws and used Ten for evaluating startup companies is in the idea stage, the extracted indicators are presented in the result section of this research.

The present study, using machine learning and polling techniques, attempts to examine the automated strategic model in order to classify and explore the ideas presented about specific services that have been studied in this area in the field of investment. Provide results in digital marketing services. The neural network-based model, by identifying related opinions, measures different characteristics at different levels of evaluation and automatically categorizes opinions depending on the quality of the presentation. Financial crises in the banking system are usually due to the inability to manage financial risks and liquidity, which is a factor in the lack of transparency and ability to manage capital. Thus, the existence of such uncertainties has reduced the interest of investors in industrial and executive partnerships. This article has been established with the aim of identifying the factors affecting liquidity risk and also providing an intelligent model for predicting and classifying liquidity risk factors, identifying and prioritizing the factors involved. For this purpose, the method of intelligent measurement using perceptron neural network (MLP) has been used, which is considered as a practical approach to artificial intelligence. For this purpose, the necessary studies on financial information and liquidity in Bank Mellat branches in Tehran (consisting of 36 branches) have been considered and for the sample population, a random cluster set of 374 selected customers and investors has been used.

The statistical society used in this paper includes 15 experts who are familiar with industrial car manufacturers and know the concepts of Merge and Acquisition. The tools for data gathering are expert questionnaires and paired comparisons. Five main components are investigated: Social and political, geographical and regional, law, legal and regulation, ICT and financial, economic and profitability. Our results show that all these components have an effect within the Merge and Acquisition model. We can also conclude that law, legal and regulation component has the most significant effect on the formation of Merge and Acquisition model in industrial car manufacturers.

Sustainable entrepreneurship based on value creation in the context of investment is one of the most important issues for today's competitive businesses. Therefore, while paying attention to investing in this field, the concepts of value creation should be considered as very influential characteristics on it as well as the consequence of investing. To conduct this research, first, a comprehensive review of sustainable entrepreneurship management models was conducted. After the interviews, the interviews were coded; challenges, gaps and ideas for resolving them were presented. Using a systematic approach and distributing a questionnaire, the opinions of experts on the importance of sustainable entrepreneurship indicators were examined. Finally, according to Pareto's optimal law, the factors with the highest score (20% higher) were identified as influential factors. Findings indicate that individual input variables are factors of control centre, creativity, individual independence and the need for success and risk, respectively. Environmental input variables are the most important effective factors, respectively, market situation, social corruption and unemployment rate, entrepreneurship education and culture, government support and creating a legal basis. Also, the most important factors related to system outputs are the creation of industries and businesses, economic growth and sustainable development, unemployment rates and social corruption, respectively. Finally, practical suggestions were expressed for activists and researchers in the field of entrepreneurship.

Now is the time to move from traditional to technology-driven and value-added business models. In recent years, the new generation of banking under the name of digital banking has become operational in the world and the main performance of leading banks has been focused on the axis of digital transformation. This research explains and develops the conceptual model of risk management in digital banking by choosing the ground-theory research method and literature review. In the first step, a comprehensive review of risk management models in digital banking and after the emergence of several gaps between the components of current research, the second step began, the researcher conducted interviews with experts in the field of management and decision making in the banking industry. After coding the interviews, based on the concepts developed, he presented a conceptual model of risk management in digital banking. This model will be explained due to the prominent components of monitoring and evaluation of digital banking risk management in macro international, national, regional development, as well as modeling and indexing in the country and region, and will develop a risk management model in digital banking. Using the expert-fuzzy method and distributing the questionnaire in three stages, the opinions of experts on the importance of risk management indicators in digital banking, expert consensus and prioritization of research indicators were examined. The results and findings of the study provide an evaluation of the risk management model in digital banking in the country's banking industry.