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Credit risk

About: Credit risk is a research topic. Over the lifetime, 18595 publications have been published within this topic receiving 382866 citations.


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Journal ArticleDOI
TL;DR: This article used principal component analysis to derive four measures of a bank's ability to perform the core task of financial intermediation and compared the performance of China's state banks, joint-stock banks, and city commercial banks along these measures.

101 citations

Posted Content
TL;DR: In this paper, a Merton-style threshold-value model for the default probability is proposed, which treats the asset value of a firm as unknown and uses a factor model instead.
Abstract: The main challenge of forecasting credit default risk in loan portfolios is forecasting the default probabilities and the default correlations. We derive a Merton-style threshold-value model for the default probability which treats the asset value of a firm as unknown and uses a factor model instead. In addition, we demonstrate how default correlations can be easily modeled. The empirical analysis is based on a large data set of German firms provided by Deutsche Bundesbank. We find that the inclusion of variables which are correlated with the business cycle improves the forecasts of default probabilities. Asset and default correlations depend on the factors used to model default probabilities. The better the point-in-time calibration of the estimated default probabilities, the smaller the estimated correlations. Thus, correlations and default probabilities should always be estimated simultaneously.

101 citations

Journal ArticleDOI
TL;DR: In this article, the authors presented evidence on the effectiveness of using the information in market equity prices to predict corporate default and linked those results to the valuation of corporate debt and showed that, contrary to previous negative results, the approach pioneered by Fischer Black, Myron Scholes, and Robert Merton provides superior explanations of secondary-market debt prices.
Abstract: “Quantifying Credit Risk I” (in the January/February 2003 Financial Analysts Journal) presented evidence on the effectiveness of using the information in market equity prices to predict corporate default. This Part II links those results to the valuation of corporate debt and shows that, contrary to previous negative results, the approach pioneered by Fischer Black, Myron Scholes, and Robert Merton provides superior explanations of secondary-market debt prices.

101 citations

Posted Content
TL;DR: In this paper, the authors examine the extent to which currently reported data reflect the true credit risk in loan portfolios and whether lending decisions have started to be taken on a commercial basis.
Abstract: Substantial effort has been devoted to reforming China's banking system in recent years. The authorities recapitalized three large state-owned banks, introduced new governance structures, and brought in foreign strategic investors. However, it remains unclear the extent to which currently reported data reflect the true credit risk in loan portfolios and whether lending decisions have started to be taken on a commercial basis. We examine lending growth, credit pricing, and regional patterns in lending from 1997 through 2004 to look for evidence of changing behavior of the large state-owned commercial banks (SCBs). We find that the SCBs have slowed down credit expansion, but that the pricing of credit risk remains undifferentiated and banks do not appear to take enterprise profitability into account when making lending decisions. Controlling for several factors, we find that large SCBs have continued to lose market share to other financial institutions in provinces with more profitable enterprises. The full impact of the most recent reforms will become clear only in several years, however, and these issues should be revisited in future research.

100 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the accuracy of consumers' self-assessments of their credit ratings and found that approximately 32 percent of consumers overestimate their credit rating, while only 4 percent underestimate their rating.
Abstract: There is considerable evidence to suggest that consumers are often misinformed about basic financial and economic principles. The purpose of this study was to examine the accuracy of consumers’ self-assessments of their credit ratings. Findings suggest that approximately 32 percent of consumers overestimate their credit ratings, while only 4 percent underestimate their credit ratings. Those who overestimate their credit quality are less knowledgeable about financial matters in general and are more likely to have acquired their financial knowledge from difficult past experiences. In addition, consumers who overestimate their credit ratings are less likely to budget, save, or invest regularly. There is considerable evidence to suggest that in general, consumers are unaware or misinformed about basic financial and economic principles— information they need in order to make important decisions such as buying a home and planning for retirement (Chen and Volpe 1998; Hogarth and Hilgert 2002; Lee and Hogarth 1999; Mandell 2006). This issue has gained more attention recently as a result of concerns about borrowers in the subprime market obtaining mortgages that they cannot afford. There is little known about the specific nature of this lack of awareness and misinformation. Credit scores are designed to measure credit risk at a particular point in time and are based on models that use information in consumer credit reportsmaintainedat thecredit reportingagencies topredictfuturepayment behavior(Fair Isaacs16). Lendersusecredit scores tohelp them makelending decisions, although each lender may differ in terms of the level of risk it finds acceptable, and this may even vary for different types of loans. Higher scores indicatelowercredit risks orhigher credit quality, althoughnosingle cutoff score is used by all lenders. Previous research on biases in judgment and decision making has shown that individuals tend to display overconfidence about their knowledge and

100 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20251
2023343
2022729
2021799
2020915
2019921