List of Articles Probability of Default

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  1 - Dependence of Default Probability and Recovery Rate in Structural Credit Risk Models: Empirical Evidence from Greece
  A. Derbali S. Hallara
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  2 - Agent-oriented modeling for credit risk analysis
  Homa Azizi Mohammadali Rastgav
  The credit crisis in recent years has increased the focus on bank credit risk. This paper uses an agent based model (ABM) to investigate the impact of bankers’ credit decision actions on bank credit losses that are induced by lending to corporate clients. In this More

  The credit crisis in recent years has increased the focus on bank credit risk. This paper uses an agent based model (ABM) to investigate the impact of bankers’ credit decision actions on bank credit losses that are induced by lending to corporate clients. In this model, we assume one bank  give credit to corporate clients and divide corporate in two sectores: small and medium corporates and large corporates. The results show that credit decision actions have substantial effects on bank credit losses, thus implying that regulators should consider organizational factors as a complement to bank assets when assigning capital requirements to banks. The study also aims to point to a new area of application of ABMs for both researchers and practitioners. Manuscript profile
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  3 - The Probability of Default on Payable Facilities of the First Micro Finance Bank in Herat Afghanistan
  Mohammad Sadeq Mohammadi Mostafa KarimZadeh Mehdi Behname
  10.30495/eco.2021.1918882.2468
  The aim of this study is to investigate the factors affecting the probability of banking facilities default by customers and to determine the main variables coefficient related to the probability of default. Finally, using logit regression, a model has been provided to More

  The aim of this study is to investigate the factors affecting the probability of banking facilities default by customers and to determine the main variables coefficient related to the probability of default. Finally, using logit regression, a model has been provided to increase the ability of the bank's managers to solve the problem of non-repayment of credit facilities on time. First, 7 variables that had a significant effect on customers' credit risk were identified and fitted to the significance level of 5% of the final model using LR statistics. The results showed that the variables of the borrower's monthly income, the borrower's relationship with the guarantor, the guarantor's guaranteed capital, the borrower's experience and job stability, the loan repayment period and the years of borrower's relationship with the bank, have adverse effect on credit risk and the variable loan amount has a direct effect on credit risk. Manuscript profile
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  4 - Calculating the probability of default of sample banks in Iran Using The Systemic Model Of Banking Originated Losses(SYMBOL)
  Mohsen Golniya Ramin Khochiani Hamid Asayesh
  The probability of default is the degree of certainty that a particular bank will default or that the counterparty will not repay its obligations according to the agreement. This article seeks to calculate the default probability of sample banks in the banking network o More

  The probability of default is the degree of certainty that a particular bank will default or that the counterparty will not repay its obligations according to the agreement. This article seeks to calculate the default probability of sample banks in the banking network of Iran, for this purpose, using the new approach of the systemic model of bank losses and the Monte Carlo simulation method, to calculate the probability of bank default in the two cases of the presence and absence of contagion effects between Bank is paid. The sample includes 15 Iranian banks and the time period of 2017. The results indicate that in the studied sample, the situation of banks' capital is not favorable for covering leading risks, the probability of bank defaults has a negative and significant relationship with the criteria of banks' excess capital, and with the increase of inter-bank correlation, a kind of There is a cluster effect of bank defaults, and the default of one or more banks can lead to a banking crisis and the collapse of the entire banking system. Manuscript profile
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  5 - Usage of ZPP Model in Credit Risk Prediction
  elahe kamali mirfeiz fallah Farhad hanifi
  Credit risk issues and methods for identifying and predicting it have been constantly evolving over the past few decades. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financia More

  Credit risk issues and methods for identifying and predicting it have been constantly evolving over the past few decades. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financial losses to shareholders, creditors, investors and other people in the community. Advanced credit risk models that are based on market value include improving credit quality as well as reducing or decreasing credit ratings. In the present study, we have Investigated two models of advanced credit risk models, so two samples were selected, namely companies with financial problems and companies with financial health, in each group probabilities of default are estimated by two models which are KMV and ZPP, and then we compared probabilities of default. We have concluded that the ZPP model has more predictive ability than the KMV model.This method is denoted the Zero-Price Probability or simply the ZPP model. The main focus is on the new simulation based approach rather than the older established models. Manuscript profile
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  6 - Forecasting Probability of default of Corporations with the Merton model: Using Capital Asset Pricing Model with Time Varying Beta
  mehdi sabeti Gholamreza Zomorodian mirfeyz fallah mehrzad minuyi
  The purpose of this article is to predict probability of default of 60 corporations with structural Merton model. we used market data of 60 corporations from 2018/08/01 to 2019/09/01 witch are listed in Tehran Stock Exchange For predicting probability of default . to re More

  The purpose of this article is to predict probability of default of 60 corporations with structural Merton model. we used market data of 60 corporations from 2018/08/01 to 2019/09/01 witch are listed in Tehran Stock Exchange For predicting probability of default . to reach this goal we estimated assets value of corporations, volatility of assets and drift rate. We used Capital asset pricing method to estimate expected assets return. Then We used simple regression method and multivariate GARCH (MGARCH) to estimate Beta of corporations. in the end we compute d likelihood function of the average predicted default for each industry and compared the results with actual default rate of that industry in the next year after predicted date. Regarding obtained results of likelihood function probability of default prediction with multivariate GARCH (MGARCH) approach outperform the simple regression model, therefore we recommend using the MGARCH approach for its better prediction performance. Manuscript profile
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  7 - Prediction of Default Risk Using Structural Models at Tehran Stock Exchange
  Saeid Fallahpour Masood Tadi
  Nowadays one of the most critical issues of risk management in banks, financial institutions and credit rating agencies is credit risk. Credit risk refers to the risk of default by the borrower, i.e. the borrower fails to fulfill its obligations to repay debt, or at lea More

  Nowadays one of the most critical issues of risk management in banks, financial institutions and credit rating agencies is credit risk. Credit risk refers to the risk of default by the borrower, i.e. the borrower fails to fulfill its obligations to repay debt, or at least does not settle the obligations on time. In this study, we intend to predict the probability of default, in the selected companies at the Tehran stock exchange. It can be divided modes of assessing the default risk in three categories. These are structural models, data based experimental models and expert assessment models that determined by experts without statistical estimations. Our research is based on the structural models. Structural models such as first passage models are developed based on the Merton model. It can be said that the structural literature on credit risk starts with the paper by Merton (1974), who applies the option pricing theory developed by Black and Scholes (1973). Merton model has a number of simplifying assumptions, i.e. occurrence of default only could happen in maturity time. In this study by relaxing the above assumption, we will reach more developed model to calculate the probability of default. After that, we calculate the annual default probability of the selected companies both by the Merton model and the proposed model during the years 1390 and 1391 SH. Ultimately, the performance of both models is compared using Wilcoxon signed-rank test that indicates a significant difference between the two models. Manuscript profile
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  8 - Estimating the probability of Loss of Credit Portfolio using the sharp asymptotic method and Latent variable model
  Mohammad reza Haddadi Reza Maaboudi Saeedeh Fallahyan
  The purpose of the study is to obtain a probability of a very high loss for a credit portfolio in a fixed time horizon and to calculate the loss of this portfolio in the worst possible case (the defaults of all customers). For this purpose, the Copula function approach More

  The purpose of the study is to obtain a probability of a very high loss for a credit portfolio in a fixed time horizon and to calculate the loss of this portfolio in the worst possible case (the defaults of all customers). For this purpose, the Copula function approach is used. A Copula function is a new tool that increases the accuracy of the calculation of this probability. Gaussian Copulas cannot simulate the dependence between the members of the portfolio. For this reason, the T- Copula method has been used as an alternative model in this paper. The T-Copula pattern, in contrast to the normal Copula method, supports the extreme dependence between variables. The structure of a multivariate distribution t is the ratio of a multivariate normal distribution on the second root of a Chi-square random variable. If the denominator of the distribution chooses values ​​close to zero, then the corresponding vector coordinates of the random variables are distributed t , Can record large joint movements. The Chi-square random variable plays "common shock" roles. The present study, using the hidden variables method, has calculated the probable unpredictability of loss for a heterogeneous portfolio of given facilities consisting of 250 borrowers. For this purpose, based on the type of borrowed loans, borrowers are divided into three groups. Using the Monte Carlo simulation method, the probability of a loss in this portfolio is estimated, then the residue levels in each group of agents and the total amount of exposure are calculated. The findings showed that, considering the degree of freedom 2 for the distribution of the student's t-test related to the vector of hidden variables, the maximum probability of loss of credit portfolio Has been 11.01. Manuscript profile