Research On Rating Model Of Bank Credit Based On Small Sample

The commercial bank credit rating is one kind of assessment of the total financial capacity that some bank can pay its financial debts currently. The importance of commercial bank credit rating is as follows:Firstly, the rating results contribute to surveying and controlling banking risks and maintaining the financial system safety for the financial regulation authorities in various countries. Secondly, their own risk managements of commercial banks are on the basis of credit rating. Thirdly, the commercial bank credit rating is taken into consideration seriously during the business transaction and the buildup of cooperation relationship among the financial institutions. Fourthly, the enterprises and the public can choose the commercial banks that provide the corresponding service and operations according to the credit rating.This dissertation is divided into five chapters. In the first chapter, the author analyzes the grounds of selected topic, relative research progress and methods, technique routes and research content. In the second one, the index system of commercial bank credit rating based on nonlinear mapping is established. In the third one, the commercial bank credit rating model of the optimal weighting is expounded. In the fourth one, small sample credit rating research is conducted. In the last one, we draw some conclusions and do some expectations. The main content is as follows:(1) The nonlinear mapping theory is introduced and the index system of commercial bank credit rating is established. According to Euclidean distances of two different states of nonlinear mapping results with and without specific indexes, it shows how much the specific indexes have impacted on the rating results. The measurable method can contribute to nonlinear mapping’deleting indexes. All indexes are mapped nonlinearly. After the specific indexes are deleted, the nonlinear mapping is conducted. We try to obtain Euclidean distances of two nonlinear mapping results. If there is no change or little change of Euclidean distances, the indexes will have little impact on the rating results. We set that the indexes are deleted when the multiple correlation coefficient and the correlation coefficient exceed the threshold at the same time, which avoids deleting indexes mistakenly with single standard and ensures less information loss. The commercial bank credit risk evaluation index system with6criteria layers and19indexes is established, which reflects91%of original information with17%of indexes. The empirical research shows that the rating results of research have the same order relationship with ones of Moody’s and Dagong Global. There are two causes of the same order relationship:Firstly, the core rating indexes, the rating methods and weighting methods aren’t announced by the authorities such as Moody’s and Dagong Global and so on. So it can’t be rated the commercial banks which the autorities haven’t rated with their methods. Secondly, this kind of same order relationship not only ensures the rationality of rating results but also rates all commercial banks.(2) The optimal weighting commercial bank credit rating model is established with the improved Spearman test. According to the commercial bank credit rating results issued by the authoritative rating institutions, the rating results of different weighting methods are tested with the improved Spearman. We choose the weighting method which brings rating results very close to the ones of authoritative institutions as the optimal weighting. So this can solve the problem that the current researches can’t fix the optimal weighting. There are five weighting methods analyzed in this research such as AMP and G1of subjective weighting and maximum deviation, variation coefficient method and entropy method of objective weighting. The rating results of Moody’s and Dagong Global Credit Rating Co. are contrasted and proved; we can fix the optimal weighting problem. The empirical research shows that the entropy weighting is optimum when rating the commercial bank credit.(3) The commercial bank rating model based on small sample testing-simulating is established. Through testing the distribution of rating scores, we can find the distribution law of rating scores and provide the basis of data amplification, which differentiate this research with current other researches. According to the distribution parameters that passed the distribution tests, we can simulate and generate the random data in step with the rating score distribution. The number of samples is expanded. So the expanded sample data and the original data have the same distribution characteristic, which makes small samples be rated. The empirical research shows that the rating scores of the commercial banks in China follow neither the normal distribution nor the exponential normal distribution and the logarithmic normal distribution, but follow a special distribution, that is, the natural logarithms’ squares of the rating scores follow the normal distribution. And then we can simulate and amplify the rating score data to meet the requirements of large samples, which avoids the inaccuracy of small sample rating.