List of Articles ریسک نقدینگی

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  1 - Measuring efficiency score by cross-efficiency method in data envelopment analysis and its relation to profitability and risk in banks admitted to Tehran stock exchange
  Donya Shikh-hasani Malihe Alifarri Balal Karimi
  The main purpose of this study is to measure the efficiency score by the cross-efficiency method in Data Envelopment Analysis (DEA) and its relation to profitability and risk in banks listed in the Tehran stock exchange for the period 2011-2017. The statistical populati More

  The main purpose of this study is to measure the efficiency score by the cross-efficiency method in Data Envelopment Analysis (DEA) and its relation to profitability and risk in banks listed in the Tehran stock exchange for the period 2011-2017. The statistical population of the study consists of 19 banks listed in Tehran stock exchange. The proposed method is developed in two steps as follows. First, we evaluate the efficiency measures of banks using the cross-efficiency method in DEA. Then, we address the relationship between obtained efficiency scores with risk and profitability of banks through inferential statistics. In order to analyze the data, first, we apply pre-tests of variance homogeneity, F-Layer test, Hausman test, and Jarque and Bera test and then we use multivariate regression test to confirm or reject the research hypotheses.The following three conclusions emerge from the obtained results. First, we have a significant relationship between the credit risk and the efficiency measure of the banks listed in Tehran stock exchange. Second, there is a significant relationship between liquidity risk and the performance of the banks listed in the Tehran stock exchange. Finally, we show that between the profitability and the efficiency score of the banks listed in the Tehran Stock Exchange is also a significant relationship. Manuscript profile
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  2 - Liquidity Risk Management in Modern Interbank Payment Systems
  rassol khoshbin Farzin Rezaei Mohammad Ali Rastegar
  In this study, in order to measure the liquidity risk in interbank payment systems, the time series of daily data balances of an Iranian bank's payment systems from 01/01/94 to 31/5/98 and then We examined stationary time series with Dickey Fuller and Philips Peron test More

  In this study, in order to measure the liquidity risk in interbank payment systems, the time series of daily data balances of an Iranian bank's payment systems from 01/01/94 to 31/5/98 and then We examined stationary time series with Dickey Fuller and Philips Peron tests and compared the expected value and risk value of payment systems data with the historical method and compared with the Pareto method. The results of the Kopik and Christofferson tests showed that Pareto's generalized approach to better manage banks' liquidity risk is better than historical method based on daily data of payment systems. The bank can then provide liquidity management operations to manage the liquidity risk in the payment system Manuscript profile
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  3 - Provide intelligent classification model based on perceptron artificial neural network (MLP) and hierarchical analysis (AHP) in digital marketing services to prioritize liquidity and investment risk
  Alireza Ashouri Roudposhti Hormoz Mehrani Karim Hamdi
  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 resul More

  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. Manuscript profile
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  4 - Mutual Fund Liquidity Risk Management Tools
  seyed hossein hosseini mohammad hassan ebrahimi sarveolia moslem Peymani
  Due to the continuous cash flow of Open-End mutual funds, liquidity risk is the most important risk of this financial institution. The main challenge of managing the liquidity of these funds is to provide cash in the event of a crisis and to face redemption requests. Fu More

  Due to the continuous cash flow of Open-End mutual funds, liquidity risk is the most important risk of this financial institution. The main challenge of managing the liquidity of these funds is to provide cash in the event of a crisis and to face redemption requests. Fund run and the pressure to finance and sell assets will transfer costs and possibly leave a portfolio of less liquid assets for the remaining investors.it is necessary to use liquidity management tools to control the repurchase pressure, share costs fairly and protect the interests of remaining investors.while reviewing and introducing common liquidity risk management tools of this industry in the world, the need to provide the possibility of using any of these tools for fixed income funds and stocks, the possibility of using any tool in normal and / or special conditions, and the necessity / non-necessity of approval of the use of the tool by the regulator before use, as the three key components of the use of these tools, has been deliberately fuzzily consulted by experts. After sending the questionnaire and during the two stages of the survey, a final agreement was reached by the experts on the use of Swing Pricing and Anti-Dilution Levy in any situation and at the discretion of fund managers and the use of Redemptions In-kind, Redemption Gates, and Suspension of Redemptions in special circumstances and with the approval of the regulator. No consensus was reached on the need to provide the use of Side Pockets. Manuscript profile
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  5 - طراحی الگویی مناسب مدیریت نقدینگی و پیش بینی ریسک آن در بانک صادرات ایران
  علی اسماعیل زاده حلیمه جوانمردی
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  6 - Presenting a Comprehensive Model for Measuring the Liquidity Risk of Banks Listed on the Tehran Stock Exchange (Case Study: Mellat Bank)
  Toraj Azari Mojtaba Tastori Reza Tehrani
  10.30495/fed.2022.694721
   AbstractLack of liquidity management of banks is one of the most important risks for any bank and lack of attention to liquidity risk leads to irreparable consequences. Preventing liquidity risk requires a comprehensive measurement method but liquidity risk is com More

   AbstractLack of liquidity management of banks is one of the most important risks for any bank and lack of attention to liquidity risk leads to irreparable consequences. Preventing liquidity risk requires a comprehensive measurement method but liquidity risk is complicated issue, and this complexity makes it difficult to provide a proper definition. In addition, defining liquidity risk determinants and formulation of the related objective function to measurement its value is a difficult task. To address these problems and assess liquidity risk and its key factors, in this study we propose a model that uses artificial neural networks and Bayesian networks. Design and implementation of this model includes several algorithms and experiments to validate the model. In this paper, we have used Levenberg-Marquardt and Genetic optimization algorithms to teach artificial neural networks. We have also implemented a case study in Bank Mellat to demonstrate the feasibility, efficiency, accuracy and flexibility of the research liquidity risk measurement model.  Manuscript profile
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  7 - Modeling to Predict the Liquidity Risk of Iran's Government Banks Using Artificial Neural Networks and Accounting Indicators
  Mahdi Khosroyani Farzaneh Heydarpoor
  10.30495/faar.2022.697091
  AbstractOne of the most important risks of bank is liquidity risk, so banks must have appropriate information systems to measure, predict and control liquidity risk. Banks manage their liquidity risk using different tools and methods, depending on the conditions and typ More

  AbstractOne of the most important risks of bank is liquidity risk, so banks must have appropriate information systems to measure, predict and control liquidity risk. Banks manage their liquidity risk using different tools and methods, depending on the conditions and type of activity. Despite the fundamental differences in the size, type of activity and structure of Government owned banks,is it possible to model and forecast the liquidity risk of state banks? To answer this question in this study, using the accounting information of Government banks in Iran, and the research accounting indicators were calculated and liquidity risk was modeled by the multilayer perceptron neural network. Then, the difference between the results of the model and the real data was measured by MSE. The research results showed that the designed model can be used to predict the liquidity risk of Iran's Government owned banks. Manuscript profile