The papers in this special issue of Mathematics and Computers in Simulation cover the following topics. Improving judgmental adjustment of model-based forecasts, whether forecast updates are progressive, on a constrained mixture vector autoregressive model, whether all estimators are born equal....

This study utilizes comparisons and Probit regression analysis to determine the influence of previous migrations and other variables on the likelihood of future migrations of agricultural loan credit risk. The Farm Credit System association data set contains a large number of lender risk-rated...

Since rural microfinance is a credit which grants loans without collateral and guarantees to farmers, it is considerably important to evaluate and control the household credit risk. Through establishing the evaluation index system and then using catastrophe progression theory, three common types...

Loan records and lender credit risk classifications are used to examine agricultural credit risk migration. The results include estimates of the likelihood of borrowers transitioning among five credit risk tiers. The paper also examines factors that influence or predict credit risk migration and...

The development of credit derivatives market, the delineation of credit securitisation technique along with their combination confirm the importance attached to these financial innovations with regard to the financial risk management. The present paper is based on the addressed observation and...

This paper investigates the role of credit and liquidity factors in explaining corporate CDS price changes during normal and crisis periods. We find that liquidity risk is more important than credit risk regardless of market conditions. Moreover, in the period prior to the recent ‘Great...

The purpose of this study is to identify important variables that influence on credit risk. Statistical analysis was used. In order to achieve the purpose of this research, a frame of references has been constructed based on a wide literature review. The calculations have been done by using SPSS...

The aim of this paper is to examine the efficiency of two credit risk modeling (CRM) to predict the credit risk of commercial Iranian banks: (1) Logistic regression model (LRM); (2) Artificial neural networks (ANNs). The calculations have been done by using SPSS and MATLAB software. Number of...

In this paper we analyze the impact of quantitative easing policies issued by the European Central Bank, the Bank of England, the Federal Reserve and the Bank of Japan on credit risk, in nine states belonging mainly to the Central and Eastern European area. We use an ARMA-GARCH model to obtain...