基于改进Credit Metrics模型的商业银行信用风险度量及实证研究

信用风险是我国商业银行面临的主要风险。随着美国金融危机的蔓延,各国银行业已意识到加强信用风险监管的必要性。研究信用风险特征,建立合适的度量模型准确地度量我国商业银行的信用风险,是降低信用风险的必然要求,而Credit Metrics模型以其擅长度量非交易性资产的信用风险而著称。作者首先对Credit Metrics模型加以改进,使用我国的信用评级转移矩阵,其次考虑宏观经济和企业本身的非系统性风险,重新调整信用评级转移矩阵。最后以某家银行为基础,使用Credit Metrics模型进行实证研究,同时对于模型中的部分参数进行修正并对模型加以改进,从而完善Credit Metrics模型在我国商业银行业的应用。

Value of big data to finance:observations on an internet credit Service Company in China

Background:his paper presents a case study on 100Credit,an Internet credit service provider in China.100Credit began as an IT company specializing in e-commerce recommendation before getting into the credit rating business.The company makes use of Big Data on multiple aspects of individuals’online activities to infer their potential credit risk.Methods:Based on 100Credit’s business practices,this paper summarizes four aspects related to the value of Big Data in Internet credit services.Results:1)value from large data volume that provides access to more borrowers;2)value from prediction correctness in reducing lenders’operational cost;3)value from the variety of services catering to different needs of lenders;and 4)value from information protection to sustain credit service businesses.Conclusion:The paper also discusses the opportunities and challenges of Big Databased credit risk analysis,which needs to be improved in future research and practice.

Portfolio optimization of credit risky bonds: a semi-Markov process approach

This article presents a semi-Markov process based approach to optimally select a portfolio consisting of credit risky bonds.The criteria to optimize the credit portfolio is based on l_(∞)-norm risk measure and the proposed optimization model is formulated as a linear programming problem.The input parameters to the optimization model are rate of returns of bonds which are obtained using credit ratings assuming that credit ratings of bonds follow a semi-Markov process.Modeling credit ratings by semi-Markov processes has several advantages over Markov chain models,i.e.,it addresses the ageing effect present in the credit rating dynamics.The transition probability matrices generated by semi-Markov process and initial credit ratings are used to generate rate of returns of bonds.The empirical performance of the proposed model is analyzed using the real data.Further,comparison of the proposed approach with the Markov chain approach is performed by obtaining the efficient frontiers for the two models.

A Study on The Timeliness of Credit Rating on Bond Defaults--Evidence from Chinese Bond Market

With the increase of China’s bond issuance and slowdown of the economic growth,the potential credit risks such as bond default in the bond market are gradually emerging.The frequent occurrence of bond defaults and the problem of false credit ratings make bond investors and market participants more cautious about the credit ratings issued by rating agencies.Based on the default bonds from 2016 to 2019,this paper analyzes the adjustment of rating of defaulted bonds by rating agencies before default.It also compares the impact of both the regulatory events and the entrance of international agencies on timeless of credit ratings on default bonds.At the same time,the divergence of rating timeliness between different rating agencies is compared.The research shows that after the unified supervision of regulators and the punishment of Dagong Global Credit Rating Co.Ltd in 2018,the timeliness of rating agencies'downgrading of defaulted bonds has increased significantly;Compared with other rating agencies,the timeliness of rating agencies owned by international rating agencies are better.

The valuation of multi-counterparties CDS with credit rating migration

In this paper,the pricing of a Credit Default Swap(CDS)contract with multiple counterparties is considered.The pricing model takes into account the credit rating migration risk of the reference.It is a new model established under the reduced form framework,where the intensity rates are assumed to have structural styles.We derive from it a non-linear partial differential equation system where both positive and negative correlations of counterparties and the references are considered via a single factor model.Then,an ADI(Alternating Direction Implicit)difference method is used to solve the partial differential equations by iteration.From the numerical results,the comparison of multi-counterparty CDS contract and the standard one are analyzed respectively.Moreover,the impact of default parameters on value of the contracts are discussed.

The impact of working capital management on credit rating

This study investigates the possible nonlinear relationship between working capital and credit rating.Furthermore,it examines the relationship between the three components of working capital(inventory,accounts receivable,and accounts payable)and a firm’s credit rating.Employing data for U.S listed firms for the period between 1985 and 2017,the results of our ordered probit model show a nonlinear relationship between working capital and its components and credit rating.Finally,we find that the deviation from the optimal working capital adversely affects the credit rating.The results of this study are of significant importance for policy makers,managers,decision makers,and credit-rating agencies,as they help highlight the importance of working capital management for a firm’s credit rating.

Detecting conflicts of interest in credit rating changes:a distribution dynamics approach

In this study,we compare the adjustments of credit ratings by an investor-paid credit rating agency(CRA),represented by Egan-Jones Ratings Company,and an issuer-paid CRA,represented by Moody’s Investors Service,vis-à-vis conflict of interest and reputation.A novel distribution dynamics approach is employed to compute the probability distribution and,hence,the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S.issuers between 2011 and 2018,that is,after the passage of the Dodd–Frank Act.It is found that investor-paid ratings are more likely to be downgraded than issuerpaid ratings only in the lower rating grades,which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation.We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings,implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests,while issuerpaid CRAs are more concerned about providing accurate ratings.

钢铁行业信贷风险评估分析--基于改进的Credit Metrics模型

在研究信用风险评估中借鉴传统信用评级模型,结合十四五规划中绿色发展的绿色生态指标,充分考虑到钢铁行业的特殊性,对Credit Metrics模型进行改进,通过对3家传统信用评级相同的钢铁企业进行实证分析,形成不同的VaR值并进行比较,分析可知ESG等级越高的钢铁企业越符合时代要求下的绿色发展。该方法更贴近当今时代的要求,对于公司有很好的警示性和方向性,利于银行把控资金回收的风险。

From Credit Fraud to Meaningful Recovery： The Role of Credit Rating Agencies and How Auditors Might Be Affected by the Dodd-Frank Act

The way investors, banks and constituents rely on rating agencies will drastically change with the implementation of the Dodd-Frank Act. The historical background of rating agencies including potential changes in the process of issuing their reports after the Dodd-Frank act is explored by the authors. CPAs （Certified Public Accountant） audit the financial statements of Securities and Exchange Commission [SEC] regulated issuers and are subject to the provisions of the Dodd-Frank act. Accountants may have new potential liabilities with clients that rely on credit agencies representations in financial statements. Analysis is made and conclusions are drawn on the effects of new credit rating agency responsibilities and that of auditors.

The Development of an Alternative Method for the Sovereign Credit Rating System Based on Adaptive Neuro-Fuzzy Inference System

The main purpose of this article is to determine the factors affecting credit rating and to develop the credit rating system based on statistical methods, fuzzy logic and artificial neural network. Variables used in this study were determined by the literature review and then the number of them was reduced by using stepwise regression analysis. Resulting variables were used as independent variables in the logistic model and as input variables for ANN and ANFIS model. After evaluating the models and comparing with each other, the ANFIS model was chosen as the best model to forecast credit rating. Rating determination was made for the countries that haven’t had a credit rating. Consequently, the ANFIS model made consistent, reliable and successful rating forecasts for the countries.

Research on the Influencing Factors of Personal Credit Based on a Risk Management Model in the Background of Big Data

Between states, between enterprises and enterprises, between people, it can be stated that credit is full of every corner of our lives. But the current lack of social credit is fundamental. Credit risk is particularly prominent. In the extensive data generation today, the information on personal credit statistics is very large, but still lack the data system processing and screening. Through the information retrieval of 200 credit information reports, this paper constructs the evaluation system of personal credit by using the basic information of the individual. The basic information of these individuals has great convenience in information collection and information statistics, and this basic information covers all aspects that are likely to result in the breach of contract. Through the use of single factor analysis and logistic model to solve the index system, you can not only find the impact of individual indicators on the degree of personal credit, but also see the overall impact of indicators on the degree of credit, that is, the weight of the indicators. Finally, four different credit ratings are divided by assigning the indicators to the scores. Credit rating can clearly measure the respective credit situation. Through the classification of these levels, measuring the credit line when a person in the individual credit operation, at the same time, it can provide reference and proval to administrative departments, which is benefit for managing credit risks. It has a substantial meaning and value in use. The solution to the rating system cannot only be applied to individuals, but also to the enterprises, with a wide range of versatility.

The Impact of Credit Ratings on Financial Performance (ROA) and Value Creation (Tobin’s Q)

This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge gap as only two researches were found,one suggesting and another using credit ratings to measure financial performance.Most researches use leverage,profitability,liquidity,and Share Return measures to explain financial performance.The empirical analysis uses the data of 2,398 observations of 240 companies rated by S&P Global Ratings for the period 2009-2013,applying a Generalized Method of Moments(GMM)methodology to estimate the models due to its ability to address potential endogeneity issues.The study considers Return on Assets(ROA)and Tobin’s Q as dependent variables.It incorporates credit ratings(CRWLTA)along with variables such as Total Debt to Total Assets(TDTA),Total Shareholder Return(TSR),EBITDA Interest coverage(EBITDAICOV),Quick Ratio(QR),Altman’s Z-Score(AZS),as well as macroeconomic factors like Gross Domestic Product(GDP)growth,inflation(Consumer Price Index-CPI),and the Federal Reserve Interest Rate(FDRI)as independent variables.The study argues that credit ratings,which incorporate historical data and confidential information about companies’strategies,provide reliable forward-looking creditworthiness assessments to the market.It is supported by specialized rating agencies that employ their methodologies.However,the findings suggested that CRWLTA,had a negative relationship with Q Tobin,although it was not statistically significant,and a negative relationship with ROA that was on the verge of significance.

Research on the Pricing of Convertible bonds in China Migration risk based on credit rating

At present,further research and exploration on credit risks are being carried out in the global field,and increasingly profound modem credit risks are exposed to the bond market.This requires that we cannot ignore the impact of credit rating migration risk on bond pricing,so as to adapt to the sustainable and healthy development of the bond market under the new normal of China's economy.The innovation point of this paper is to try to analyze the pricing of Convertible bonds in China from the perspective of credit rating migration risk.Tsiveriotis and Femandes(1998)model is selected,and the credit risk in the model is assumed to be caused by the credit rating migration risk,and the credit spread is used to measure the credit rating migration risk.The research conclusion of this paper is as follows:First,it is valid to consider the risk of credit rating migration in the TF(1998)model.The market price of convertible bonds is on average 1.22% higher 1han the theoretical value of the model.In general,the theoretical value obtained from the model has little deviation from the market price,and has a good fitting degree.Second,from the Angle of credit rating,the selection of 32 samples of convertible bonds only empirical research shows that the credit rating of AA-convertible bonds average deviation rate is negative,suggest that the credit rating of AA-the phenomenon of convertible bonds value is underestimated,and AAA credit rating to AA,AA+,the average deviation rate of convertible bonds is positive,that credit rating AA(containing AA)more convertible bond value is overrated phenomenon,and the higher the credit rating of the average deviation rate of convertible bond,the greater the overvalued levels.It has certain guiding significance for participants in the convertible bond market.

企业资源配置战略与债券信用评级

企业战略作为企业全局性、长期性资源配置的重要规划,对企业经营活动具有重要影响,也必然会影响企业的融资行为。本文从企业战略视角出发,以2008—2020年中国A股上市公司为研究对象,运用固定效应模型探究了企业资源配置战略对债券信用评级的影响。研究发现:相对于经营主导型企业,投资主导型企业的债券信用评级更低,并且该结论在处理内生性问题和进行一系列稳健性检验后依然成立。异质性分析发现,企业资源配置战略对债券信用评级的影响在非国有企业和分析师跟踪人数多的企业中更明显。中介效应检验结果表明,企业资源配置战略通过作用于企业违约风险而影响债券信用评级。本文的研究结论对发债企业、信用评级机构和债券市场投资者具有重要启示意义。

我国不同付费模式信用评级校验机制研究

我国债券市场刚性兑付被打破后,不断出现高评级债券违约事件。为此,监管部门积极发展多种评级,以期提高债券评级质量。通过理论建模与实证分析,研究了不同付费模式信用评级如何综合发挥校验作用。基于博弈模型的理论分析发现,不同付费模式评级发挥校验作用的机制在于投资者的反应:当投资者付费和发行人付费两种模式评级差值增大,投资者不以单一评级结果进行债券定价,而是根据评级差值调整债券价格。基于2011—2020年企业债评级数据的经验证据显示,随着评级差值增大,发行人付费评级机构会降低后续评级,且评级差值对单一信用评级与债券信用利差之间的负向关系具有抑制作用。进一步检验发现,发行人付费评级机构提供的偏正面的私有信息会降低债券信用利差,而以中债资信为代表的投资者付费评级机构提供的私有信息则不会显著影响债券信用利差,均体现出单一评级模式在定价方面的弊端。因此,监管部门应继续鼓励发展投资者付费评级模式,并鼓励机构投资者发展内部评级,以充分发挥多种评级模式的交叉校验作用。

Methods for Increasing Creditability of Anomaly Detection System

Based on Bayes' theorem we point out that the false positive rate must be lower than the intrusion base rate in order to make the Alarm Credibility Probability of the intrusion detection system exceed 50%. We present the methods that have been used in our developing intrusion detection system AIIDS (artificial immune intrusion detection systems) to increase the creditability of anomaly detection system. These methods include increasing the regularities of the system call trace by use of Hidden Markov Model (HMM), making every antibody or detector has finite lifetime, offering the detector a co-stimulate signal to illustrate whether there is damage in the system according to the integrity, confidentiality, or availability of the system resource.

基于Credit Metrics模型的地方政府债券保险费率厘定

在发达债券市场,债券保险是一种为发行者提供增信服务和为投资者提供风险保障的重要工具。债券保险产品创新的核心是费率的厘定。借鉴贷款保证保险的定价思路,选用Credit Metrics模型为地方政府债券保险进行定价,在实证分析时借用美国市政债发行主体的信用等级迁移概率、历史违约率等数据,分别计算了一般责任债券和收益类债券中投资级别和投机级别债券3年期和5年期的费率水平。并提出从建立信用风险数据库、提高信用评级技术水平、选择合适的运营模式、完善监管制度四个方面来推动实施地方政府债券保险。

A Method for Forecasting Credit Risk of Global Device Purchasing

With the development of the Internet and E commerce, enterprises can achieve global device purchasing with a good cost performance. But the credit risk is the key factor in selecting a device provider. Credit risk involves many qualitative and quantitative factors. We construct a multi agent credit rating model system based on CSCW, which organically combines the people's aptitude and the capability of machines. Enterprises can use this credit rating system for forecasting and defeating the credit risk of global device purchasing.

Application of a Multi-Agent System (MAS) to Rational Credit Rating

A Multi-Agent System （ MAS ） is a promising approach to build complex system. This paper introduces the research of the Inner-Enterprise Credit Rating MAS （ IECRMAS）. To raise the rating accuracy, we not only consider the rating-target＇s information, but also focus on the evaluators＇ feature information and propose the rational rating-group formation algorithm based on an anti-bias measurement of the group. We also propose the rational rating individual, which consists of the evaluator and the assistant rating agent. A rational group formation protocol is designed to coordinate autonomous agents to perform the rating job.

Does the Financial Status of Company Affect the Bond Credit Rating?--Empirical Evidence from China's Shanghai and Shenzhen Stock Exchanges

This article takes the companies that publicly issued corporate bonds on the Shanghai and Shenzhen Stock Exchanges from 2006 to 2018 as the research objects selecting six aspects that comprehensively reflect the 17 financial variables in 6 aspects:profitability,operating ability,bond repayment ability,development ability,cash flow and market value of the company.Principal component analysis method and factor analysis method are used to extract the principal factors of these financial indicator variables.That is how an ordered multi-classification Logistic regression model is constructed to test the impact of the Shanghai and Shenzhen Stock Exchanges’financial status on the corporate bond credit rating.It turns out that the financial status of the Shanghai and Shenzhen Stock Exchanges have an important impact on the credit rating of corporate bonds.The financial status has a greater impact on corporate bonds with credit ratings of A-and AA-,while it has a smaller impact on corporate bonds with credit ratings above AA.The results of this article can help individual and institutional investors prevent risks from investing.