ON SOME INCONSISTENCIES IN MODELING CREDIT PORTFOLIO PRODUCTS

2007 ◽  
Vol 10 (08) ◽  
pp. 1305-1321 ◽  
Author(s):  
FRANK J. FABOZZI ◽  
RADU TUNARU

The survival probability term structure has become the main concept in modeling credit risk for pricing, risk management, and investment decisions. The Kth-to-default contract is not only a relatively liquid credit risk instrument but also a vehicle that credit rating agencies employ to determine the rating of more esoteric credit risky positions. In this paper, we point out some subtleties in credit risk modeling of default baskets and also identify some potential bias in the pricing formula of the Kth-to-default contract. The numerical examples suggest that this bias increases with the correlation. The results in this paper emphasize the important role of conditioning the information regarding arrival of default.

Author(s):  
Boudewijn de Bruin

This chapter argues for deregulation of the credit-rating market. Credit-rating agencies are supposed to contribute to the informational needs of investors trading bonds. They provide ratings of debt issued by corporations and governments, as well as of structured debt instruments (e.g. mortgage-backed securities). As many academics, regulators, and commentators have pointed out, the ratings of structured instruments turned out to be highly inaccurate, and, as a result, they have argued for tighter regulation of the industry. This chapter shows, however, that the role of credit-rating agencies in achieving justice in finance is not as great as these commentators believe. It therefore argues instead for deregulation. Since the 1930s, lawgivers have unjustifiably elevated the rating agencies into official, legally binding sources of information concerning credit risk, thereby unjustifiably causing many institutional investors to outsource their epistemic responsibilities, that is, their responsibility to investigate credit risk themselves.


Author(s):  
Mccormick Roger ◽  
Stears Chris

This chapter first discusses the origins of the financial crisis, highlighting practice of ‘packaging and selling’ credit risk by financial market participants that led up to the crisis. It argues that although, in retrospect, many aspects of that practice look very bad indeed, the idea that banks might originate a credit exposure and then transfer the credit risk attached to it to a third party was, before the financial crisis, considered to be part and parcel of sound risk management. The discussion then turns to credit-rating agencies. Analysis of the financial crisis and ‘what went wrong’ has shown that rating agencies were too generous with their rating of many of the structured products that contributed to the collapse.


2020 ◽  
Vol 16 (2) ◽  
pp. 61
Author(s):  
Josep Patau

Object: The present work responds to two objectives. On the one hand, it describes the evolution of the main economic-financial indicators that influence credit risk (insolvency) for a sample of 10 Spanish companies listed on the IBEX 35. This analysis is studied for a comparative period of 10 years, which coincides with a pre-crisis stage (2002-2005) and an economic post-crisis phase (2012-2015). On the other hand, it corroborates the relationship between the analysed insolvency and the rating or credit-risk rating published for these companies by an internationally recognized credit rating agency, Standard & Poor's (S & P).Design / methodology: A sample of 10 companies and a 10-year period including the years 2002-2005 (pre-crisis) and the years 2012-2015 (post-crisis) are chosen, omitting the Spanish economic crisis that occurred in the year 2008. For the study of its evolution, 6 ratios obtained from the scientific literature that relate to credit risk and its effects on investments and company results are calculated. Finally, the correlations of these variables with the ratings of credit risk assessment by the rating agency S & P are measured. Descriptive statistics will assign value and graphics to this ten-year evolution, and with the incorporation of a factorial analysis, the correlation between the ratios and the S & P rating will be determined. The statistical analysis explains this correlation to a greater extent.Contributions / results: The results show a clear increase in the value of the impairment variable due to credit risk ten years later that directly affects the results of the companies, despite these companies having significantly reduced their investments in commercial loans pending collection and drastically reduced the period means of collection of clients. In turn, there is a clear correlation between the insolvency studied and the variables used by the S & P rating agency for the assessment of credit risk.Added value / conclusions: The empirical study concludes that there is a correspondence between insolvency and the rating given by an internationally prestigious rating agency (S & P) for the sample of 10 companies studied. Three variables – customer balance-accounts receivable, investments and the net amount of turnover – are determining factors explaining this correlation, and these three variables are the same ones that decisively influence both the pre-crisis period and the post-crisis period 10 years apart. The rating agencies weigh the insolvency variable in their analyses.


Author(s):  
Ella Khromova

Investors are interested in a quantitative measure of banks’ credit risk. This paper maps the credit ratings of Russian banks to default probabilities for different time horizons by constructing an empirical dynamic calibration scale. As such, we construct a dynamic scale of credit risk calibration to the probability of default (PD).Our study is based on a random sample of 395 Russian banks (86 of which defaulted) for the period of 2007-2017. The scale proposed by this paper has three features which distinguish it from existing scales: dynamic nature (quarterly probability of default estimates), compatibility with all rating agencies (base scale credit ratings), and a focus on Russian banks.Our results indicate that banks with high ratings are more stable just after the rating assignment, while a speculative bank’s probability of default decreases over time. Hence, we conclude that investors should account for not only the current rating grade of a bank, but also how long ago it was assigned. As a result, a rising capital strategy was formulated: the better a bank’s credit rating, the shorter the investment horizon should be and the closer the date of investment should be to the rating assignment date in order to minimise credit risk.The scientific novelty of this paper arises from the process of calibration of a rating grade to dynamic PD in order to evaluate the optimal time horizon of investments into a bank in each rating class. In practical terms, investors may use this scale not only to obtain a desired credit rating, but also to identify quantitative measure of credit risk, which will help to plan investment strategies and to calculate expected losses.


2021 ◽  
Vol 12 (5) ◽  
pp. 41
Author(s):  
Emna Damak

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process over time using 89 banks from 27 EMENA countries rated by S&P’s simultaneously before and after 2007-09 crises. We made this comparison based on the CAMELS model with a proposed ‘S’ to BCRR. We use "ordered logit" regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the rating changes in 2012 are mainly a methodology revision consequence of the entire rating process changes, including the weight of components, the important factors and the relevant variables in order to take into account some of the lessons learned from this global crisis. They also show a consistence between the BCRR's revealed and practiced methodologies revised by the credit rating agencies (CRAs).


Author(s):  
Peter Dadalt ◽  
Michael Gueli ◽  
Rafay Khalid ◽  
Ling Zhang

Credit analysis is more than just a quantitative exercise because qualitative factors can influence creditor decisions to lend funds. This chapter discusses the importance of balancing the strengths and weaknesses of quantitative characteristics with an analysis of qualitative characteristics. The extension of credit from a lender to a business is a decision that should follow the careful analysis of factors recognized as industry structuring tools. The “five Cs of credit” provide a framework to begin a qualitative assessment of a company, for without context, financial analysis is almost meaningless. A subsequent discussion of business, industry, and economic analysis rounds out the qualitative considerations. The chapter also offers a discussion of the critical role of the credit rating agencies as gatekeepers. Finally, a review of financial statements, metrics, ratio analysis, and firm capital structure provides a broad view of the firm when conducting a financial analysis. The chapter presents a case study to illustrate key principles.


2021 ◽  
Author(s):  
Riddha Basu ◽  
James P. Naughton ◽  
Clare Wang

We find that corporate credit rating changes have an effect on firms' voluntary disclosure behavior that is independent of the information they convey about firm fundamentals. Our analyses exploit two separate quasi-experimental settings that generate either exogenous credit rating downgrades or credit rating upgrades (i.e., credit rating label changes). We find evidence of a negative relation between the direction of the credit rating label change and the provision of voluntary disclosure in both settings-firms respond to exogenous downgrades by increasing voluntary disclosure and to exogenous upgrades by decreasing voluntary disclosure. The effects we document are attributable to the regulatory role rather than the information role of credit ratings. Overall, our analyses indicate that credit rating agencies as gatekeepers influence firms' provision of voluntary disclosure.


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