جستجوی مقالات مرتبط با کلیدواژه « risk management » در نشریات گروه « مالی »

Financial resilience seeks to reduce the probability of failure or reduce financial losses and risks before and after the occurrence of economic and environmental shocks. The primary goal of resilience is to prevent bankruptcy and guarantee the activities of the relevant businesses to overcome the conditions and continue the company's activities. The nature of the current research is survey-applied. The statistical population of this research includes experts familiar with financial resilience, entrepreneurs and managers of entrepreneurial businesses, among them, 10 experts identified and considered as the statistical sample of the research. The data collection tools are in-depth interviews, using expert questionnaires and paired comparisons. The findings indicate that 5 components of environmental factors; efficiency; strategic capabilities; Competitors and stakeholders and strategies are the main dimensions affecting the financial resilience of entrepreneurial businesses. In addition, based on the results of fuzzy ANP, among these factors, environmental factors, efficiency and strategic capabilities have had the greatest impact on financial resilience and risk management.

In the hectic world of today, with the rapid changes in various aspects such as political, cultural, social, and technological, leading organizations and industries, are paying special attention to their strategic planning. In addition, with the emergence of new technology and the fast growth of the internet, Digital ecosystems became an inevitable part of the strategic plans, since the future is intertwined with digital business. Digital business creates significant changes in the business ecosystem of organizations, which makes the organization more complex and the need to make strategic decisions related to digital transformation. Digital ecosystems are the digital counterpart of economic ecosystems, which change the way businesses cooperate and compete with strong, and organized architecture and can provide dynamic solutions to complex problems.In this research, by using the COBIT framework and ANP, graph network, and Markov chain, a model has been proposed to measure and analyze the risk of branding management in a digital ecosystem. By evaluating the current status of the risk parameters in an FMCG investment corporate, the research proposed solutions and optimizations, based on a Genetic algorithm and MATLAB software to increase the effectiveness of branding management in the investment Corporate.

In this study, the importance of crisis test in bank risk management is discussed. In order to conduct this research project, information on the financial statements of 20 banks from the stock exchange was collected in 58 quarterly periods from the beginning of 2007 to the middle of 2021. Next, the research variables were calculated for these banks. The collected data was processed through Excel software. Then, the research hypotheses were analyzed and tested according to the type of data and panel data method, using R 4.1.1 open-source software. The results show that among the major variables that have been shocked, the exchange rate variables and the stock market price index have had an important effect on increasing the liquidity risk, which indicates that owners of funds are paying attention to alternative markets such as the foreign exchange market and the capital market.

The current research studies and examines the resilience of financial technology businesses. Resilience is determining strategies that can prevent inefficiency and collapse of businesses, or in case of system inefficiency, return to the pre-failure state or better than that in the shortest possible time. In addition, in this research, a comprehensive model of resilience of financial technological businesses and its introduction to the studied society is presented. All the failure modes that cause the inefficiency of financial systems for technological businesses include 12 failure modes that have been identified through research literature and experts' opinions. The statistical population of this research are managers and experts in the field of financial technology business and related groups in Tehran. In the analysis, the FMEA technique is used to determine resilience strategies in financial technology businesses before failure and the new FAAO technique is used to determine resilience strategies of financial technology businesses after failure. Through the FAAO technique, 6 strategies were determined to make risk management more resilient to failure.

Due to the dynamics of the business world and due to the uncertainty in the current economic environment of the country, there are various risks in this environment that can affect the performance of companies.In this survey, the statistical population is accountants in companies admitted to the Tehran Stock Exchange and includes information from the year1400. For risk graphs two methods fuzzy ANP and network analysis have been used. Also a questionnaire related to pairwise comparisons was used and completed by10 experts in the field of stock exchange with more than10 years of work experience.The selection of people was carried out using the snowball method until theoretical saturation was reached.The obtained results were analyzed, ranked and clustered by the fuzzy ANP method. Also by using the topology method based on network theory, the shape related to the most important risks with their interactions has been drawn and by using the opinion of 10 experts of the pairwise comparisons department, the probabilities, the degree of influence of the risks have been determined and then the intensity of the effect has been determined and ranked.MATLAB 2022 and Excel 2016 software were used for this research. Also,the effectiveness of the most important risks has been determined. Inflation risks(179), liquidity(119), liquidity(80) as critical risks and political risks(72),human resources(52),credit(40) as key risks and operational risks(39) industry(32) interest rate(28), stock price(24) were classified as important risks.Therefore by identifying important risks with a high center of gravity, risks can be managed, and therefore suggestions have been made.

The banking industry, as one of the most important sectors of the economy, plays a very important role in attracting and directing depositors, providing services to people and participating in economic and social development, and in this way, it faces many risks that are particularly important to manage and control. One of the important steps for management of the risk is determination of the factors affecting on it. The purpose of the study is to present a dynamic model for bank liquidity risk management. For this purpose, system dynamics methodology has been used to find the risk-generating structure and provide an effective solution to manage it. In this method, the stimulation of different scenarios is possible by providing a mathematical model. In this regard, the results of the implementation of the four decision-making scenarios on the model were simulated and analyzed. The results show that decreasing the legal deposit and deferred loans and increasing the deposit attraction will affect on reducing banks' liquidity risk.

In recent years, after the economic crises, the value of operational risk assessment has been observed in the financial industry, while the biggest impact of operational risk has been on the banking industry. As a result, more attention has been paid to operational risk assessment in the banking industry after the financial crisis. Operational risk is defined as the risk of loss caused by the inadequacy or inefficiency of internal processes, people, systems, or external events. In this regard, institutions and banks have been looking for operational risk assessment by taking different approaches, including the approaches of the Basel Committee. The current research aimed to review operational risk management in the banking industry. Using the meta-synthesis method, 643 related research documents between 2000 and 2022 were gathered from among reliable scientific databases. By using this method, 43 final documents made the basis for extracting the findings. Finally, this method identified 5 main categories, including operational risk, risk assessment, risk quantification methods, risk analysis, and risk management, as well as 10 subcategories consisting of 43 concepts and 169 codes. The results were confirmed based on the experts’ opinions with a kappa index of 0.756.

The purpose of this research was to survey the dimensions of implementation and development of risk management in financial industry organizations in Iran so as to reveal the level of risk management implementation and its degree of maturity, including the level of risk management culture, risk management governance, and integrity of risk management systems and processes, in the financial industry organizations.This research, which was a survey in terms of its nature and an applied one in terms of purpose, was performed among 173 organizations from all the companies and institutions in the country's financial industry. A questionnaire was used to collect the required data and information. The results showed that the risk management culture in the country's financial industry organizations was at a slightly lower than average level. Risk governance was at a slightly higher than weak level and the integrity of risk management systems and processes was lower than average. This research investigated enterprise risk management and its development among Iran’s financial industry organizations for the first time.

The aim of the current research is to optimize the multivariate portfolio optimization algorithms under illiquid market (commodity and financial) perspective. In this regard, an optimization model for portfolio risk-return assessment with LVaR constraints is investigated using reasonable financial and operational scenarios. This approach is achieved by minimizing LVaR. The research method is descriptive and correlational. The statistical population is the companies admitted to the Tehran stock exchange, which were selected by systematic elimination sampling (screening) of 100 companies that were present in the stock exchange during the financial years of 1392-1399.The required information was extracted through the new Rah Avard software and the official website related to the Tehran Stock Exchange Organization. The unit root test of the variables was investigated using the method of Lin and Chui, and the basics of econometrics were discussed, and the variables were investigated using the vector auto-regression method (VAR) using Eviews and MATLAB statistical software. Based on the results, it can be said; Liquidity affects commodity and financial markets. Also, the effect of optimization algorithms and modeling techniques on portfolio management and risk assessment was confirmed

Value at risk, which is a way of measuring the risk of reducing the price of portfolios or financial portfolios, is one of the most important market risk measures, which is widely used to manage financial risk by the Financial Regulatory Authority and portfolio managers.the effect of monitoring criteria on value at risk is considered as the risk criterion considering the role of intellectual capital and risk management with regard to the importance of value at risk as the main purpose of the research.for this purpose, financial information of 138 companies active between 1390 and 1397 was used as statistical society.to test the hypotheses of the research, using structural equation modeling and statistical analysis tests, the t - statistic was used. the results of the research show the effect of Corporate Governance system on value at risk, as well as the moderating role of risk management on value at risk. in this study, it has been shown that intellectual capital is not related to the impact of the criteria of Corporate Governance and value at risk of the information content.

The current research is to present an applicable and suitable model for the financial resilience of entrepreneurial businesses with a risk management approach. This research aims to create a model to achieve and create the necessary platforms to create a culture of financial resilience in order to lead them to manage the risk of entrepreneurial businessesThe methodology used in this research is qualitative. in which the ground method of foundation data theory is used. that by using the opinions of subject matter experts and interviewing 10 experts in this field and using the snowball method until reaching the theoretical saturation stage in order to identify the effective factors in formulating the desired pattern and model of the research using open coding, central and selective has been discussed. In the end, the results of this research lead to the presentation of a model for financial resilience in entrepreneurial businesses, which has been developed and presented in the direction of financial resilience and risk management in entrepreneurial businesses, as well as the conceptual model of the research. From the results of the current research, the most important activities in the sectors such as designing discovery mechanisms and creating financial resilience of entrepreneurial businesses; redesigning financial resilience processes; Creation of creative innovation processes in financial resilience; Creating a culture of using new technologies and the desire to innovate in the implementation of financial resilience is in the direction of financial resilience.

the tax organization , like other organizations , is faced with some risks in achieving its goals such as the realization of predicted tax revenues in the course of the annual budgets . there are many time lags in the process of cutting tax cases and finally paying taxes . therefore , this study aimed to design a risk management model of tax arrears with tax litigation approach using grounded theory . this research is qualitative . in the present study , a deep interview was used as data collection tool whose data were analyzed using open , axial and selective coding . in this research for selecting the sample , purposive sampling has been used which is based on the principle of theoretical sufficiency , in the present study using interview16 of this important . the validity of the questionnaire was confirmed by the content validity test ( cvr ) and its reliability was confirmed by cohen 's kappa test ( k ) . the results of the study include identification of causal factors , background , meddling and consequences ,risk management of tax arrears with tax litigation approach and finally presenting the final model . the results indicate that the risk of no doing legal duties by taxpayers , lack of tax compliance , no timely payment of taxes , prolongation of tax proceedings , multiplicity of jurisdictions , lack of optimal use of human resources as causal of risk management of tax arrears ,is known .

This scientific research aims to study the strengthening and limiting role of effective factors on fraudulent behavior of opportunistic companies in order to change the profit and risk management. The purpose of present research is to delineate the role and importance of overconfidence of managers, quality of auditing and political relationships on influencing process of fraudulent behaviors upon risk and profit management of companies in order to control. The effective factors in This regard. The statistical society consists of listed companies in Tehran stock Exchange and statistical sample consists of 152 companies by using financial information of 2011-2021 time period. Hypotheses have been tested by using multivariate linear regression model and data have been analyzed by panel date analysis. findings indicate in addition to significant positive relationship between fraud incident and risk and profit management, political relationship and quality of auditing have negative moderating effects and managerial over confidence results in increasing intervening effect on positive relationship between fraud and risk and profit management..

Investment efficiency is achieved when the company invests only in all projects with a positive net present value. Of course, this scenario works if the market is complete and there are no incomplete market issues such as incorrect selection and agency costs. Do not haveThe purpose of this research is to apply artificial intelligence algorithm in predicting investment efficiency by emphasizing the role of risk management criteria. For this purpose, the financial information of 139 companies between 2010 and 2019 was used using genetic artificial intelligence and neural network methods. The results indicate the effect of risk management criteria on investment efficiency and also the results showed that the neural network artificial intelligence method has higher power than the genetic artificial intelligence method to predict the investment efficiency of companies listed on the Tehran Stock Exchange.

The experiences of recent decades in financial markets, and in particular the banks of different countries, indicate an increase in the importance of risk management in financial activities. Therefore, international efforts are aimed at creating a framework for standards that can be achieved by improving the financial health of the institution, especially banks. The axis of these standards has been manifested in creating an integrated risk management framework in the context of corporate risk management. The main purpose of the present research is to design a structural model of the types of existing risks in the banking sector. By studying thematic literature and using the textual content analysis approach, eleven effective risks were identified and for localization of them in the country's banking sector, Delphi technique was used for three periods of use It turned out The statistical population of the study consisted of managers and experts familiar with the subject and working in the banking sector. A researcher-made questionnaire was used to collect data. The reliability and validity of the questionnaire was confirmed by calculating Kendall's correlation coefficient (0.82) and Goghos and Boucher's correlation coefficient (0.08, 0.06), respectively. In order to design a structural model of risk, an interpretive structural modeling approach was used in fuzzy environment to manage linguistic ambiguity in judgments. The results of the Mick-Mac modeling and analysis showed that liquidity, credit, operational, interest rate, exchange rate risk and risk of laws and regulations are key and basic risks in the banking sector.

Given that investing in the stock market is associated with risk, measuring it is one of the most important issues for investors. The present study measures risk measurement by the measure of risk. In this study, the value at risk, using the GARCH, APARCH and GJR models with normal distributions, T-stents, T-stents, strings and strings, including string distributions; the reverse distribution of normal GIG (NIG) and generalized hyperbolic distribution (GHyp) is estimated. In this study, to measure risk, the efficiency of Tehran Stock Exchange index in chemical industries and total index has been used. The time period in this study includes a seven-year period with a daily frequency during the period of 05/01/1392 to 28/12/1398. The results showed that the Garc models were more accurate with the Levy distribution, and among the Garc models, the GJR model was more accurate, considering the Lou distribution and the Skewed-t distribution used among the other models.

The purpose of this study is analyzing the relationship between firm financial status and value at risk by emphasizing the role of risk management. Therefore, from value at risk information with the bootstrap simulation between the period of 2012 and 2019 and information of 138 companies in Tehran stock exchange (TSE) for statistical sample companies and the company's financial status criteria (performance measures and firm risk) and management criteria, as a moderating variable firms were used. In this study, the method of structure analysis which tests a specific model of relation between variables is used because this model is a comprehensive approach to test assumptions about the relationships of the observed and latent variables. The results of the hypotheses and model fitting showed that the firm's financial status on the value at risk is significantly effective and the risk management of this connection can be properly adjusted, however, performance measures were higher power in explaining the company's status as well as the value at risk.

Major developments in the business environment, such as globalization and the rapid pace of change in technology, have increased competition and management difficulty in organizations. In complex environments, organizations need managers to consider these inherent complexities when making important decisions. Effective risk management is an important part of this decision-making process. The purpose of the present study is to evaluate corporate risk management by analyzing the relationship between gray matter and entropy weight in listed companies of Tehran Stock Exchange. The sample included 20 companies during the years 2013 to 2018. In this study, we first sought to find relative weight for measuring corporate risk management by using variables (strategic risk management, operational risk management, risk management reporting and risk management non-compliance). Then, based on the results of the entropy analysis, we will try to determine the rankings of the companies in terms of risk management performance using the gray relationship analysis in the companies. The results of this study indicate that many companies have high performance in risk management.

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.