It is necessary to classify credit rating of small and medium-sized companies in Chinese growth enterprises board. We selected the data of 90 small and medium-sized companies, used fuzzy theory to calculate the qualitative variables, and reformulated support vector machine for ordinal regression method so that different input points can make different contributions to decide hyper plane, to ana...

This paper studies changes in the information environment brought about by Regulation Fair Disclosure (FD), which was implemented on October 23, 2000. FD now prohibits U.S. public companies from making selective, non-public disclosures to favored analysts and portfolio managers. FD, however, has a number of exclusions, one of which still allows disclosure of nonpublic information to credit rati...

Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector mac...

The introduction of the Basel II Capital Accord has encouraged financial institutions to build internal rating systems assessing the credit risk of their various credit portfolios. One of the key outputs of an internal rating system is the probability of default (PD), which reflects the likelihood that a counterparty will default on his/her financial obligation. Since the PD modeling problem ba...

Although previous research has reported that the momentum strategy is effective in the US equity market, the contrarian strategy is effective in the Japanese equity market. The current research illuminates the relationship between the return found with the contrarian strategy (contrarian return) and credit rating in the Japanese equity market. We empirically verify the relationship between thes...

Corporate credit-rating prediction using statistical and artificial intelligence techniques has received considerable attentions in the literature. Different from the thoughts of various techniques for adopting support vector machines as binary classifiers originally, a new method, based on support vector domain combined with fuzzy clustering algorithm for multiclassification, is proposed in th...

The paper examines the impact of countries’ credit ratingschanges on cost defaults swaps premium. It is assumed statisticalsignificance abnormal returns due to changes in ratings assignedby agencies. has been put hipothesis that events convey newinformation and lead significant reactions. study usedthe assigned by Standard & Poor's Moody's for period fromJanuary 2005 November 2015 spreads f...

Preface Modeling of credit risk has become a very important and rapidly expanding field of mathematical finance in the last fifteen years. Apart from a purely academic interest, the credit derivatives industry clearly needs advanced mathematical models to objectively assess and hedge this kind of risk, which was only underlined by the recent financial crisis. Although there exist several credit...

This paper uses a unique data set from credit files of six leading German banks to provide some empirical insights into their rating systems used to classify corporate borrowers. On the basis of the New Basle Capital Accord, which allows banks to use their internal rating systems to compute their minimum capital requirements, the relations between potential risk factors, rating decisions and th...

This paper uses a unique data set from credit files of six leading German banks to provide some empirical insights into their rating systems used to classify corporate borrowers. On the basis of the New Basle Capital Accord, which allows banks to use their internal rating systems to compute their minimum capital requirements, the relations between potential risk factors, rating decisions and th...