Comparative Analysis of Alternative Credit Risk Models – an Application on German Middle Market Loan

نویسندگان

  • Markus Kern
  • Bernd Rudolph
چکیده

In recent years new methods and models have been developed to quantify credit risk on a portfolio basis. CreditMetricsTM, CreditRisk, CreditPortfolioView are among the best known and many others are similar to them. At first glance they are quite different in their approaches and methodologies. A comparison of these models especially with regard to their applicability on typical middle market loan portfolios is in the focus of this study. The analysis shows that differences in the results of an application of the models on a certain loan portfolio is mainly due to different approaches in approximating default correlations. That is especially true for typically non-rated medium-sized counterparties. On the other hand distributional assumptions or different solution techniques in the models are more or less compatible. Zusammenfassung: Seit einigen Jahren finden sich in Wissenschaft und Bankpraxis neue Methoden und Modelle, um Risiken von Kreditportfolios zu messen. Zu den bekanntesten Vertretern gehören CreditMetrics, CreditRisk und CreditPortfolioView, welche sich auf den ersten Blick stark im Ansatz und in der Methodik unterscheiden. Im Mittelpunkt der vorliegenden Studie steht ein Vergleich dieser Modelle und zwar insbesondere hinsichtlich ihrer Anwendbarkeit auf ein typisches Portfolio aus mittelständischen Bankkrediten. Die Analyse zeigt, dass Unterschiede in den Ergebnissen zweier Modelle für ein und dasselbe Portfolio vor allem auf unterschiedliche Verfahren in der Approximation von Ausfallkorrelationen zurückzuführen sind. Dies gilt insbesondere für Kredite an nicht-geratete mittelständische Unternehmen.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Current Models of Credit Portfolio Management: A Comparative Theoretical Analysis

The present paper aimed at studying the current models of credit portfolio management. There are currently three types of models which consider the risk of credit portfolio: the structural models (Moody's KMV model, and Credit- Metrics model), the intensity models (the actuarial models) and the econometric models (the Macro-factors model). The development of these three types of models is based...

متن کامل

Credit risk management tools ranking in useless banking Using the AHP technique

Equipping and allocating resources to economic activities is done through the financial market where the bank credit market is part of that market. The high reserves of banks and the refurbished or overdue facilities indicate that the banking system does not use credit risk management tools well and that there is no proper model for managing credit risk in the banking network. The present study...

متن کامل

Investigating the missing data effect on credit scoring rule based models: The case of an Iranian bank

Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...

متن کامل

The Comparison of Credit Risk between Artificial Neural Network and Logistic Regression Models in Tose-Taavon Bank in Guilan

One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...

متن کامل

Matrix Sequential Hybrid Credit Scorecard Based on Logistic Regression and Clustering

The Basel II Accord pointed out benefits of credit risk management through internal models to estimate Probability of Default (PD). Banks use default predictions to estimate the loan applicants’ PD. However, in practice, PD is not useful and banks applied credit scorecards for their decision making process. Also the competitive pressures in lending industry forced banks to use profit scorecards...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001