A statistical modeling approach to building an expert credit risk rating system

2010 ◽  
Vol 6 (2) ◽  
pp. 81-94
Author(s):  
Rasmus Waagepetersen
Keyword(s):  
Credit Risk ◽  
Statistical Modeling ◽  
Rating System ◽  
Risk Rating ◽  
Modeling Approach

scholarly journals Credit Risk Rating System of Small Enterprises Based on the Index Importance

2017 ◽  
Vol 11 (6) ◽  
pp. 35-52 ◽  
Author(s):  
Chi Guotai ◽  
Zhao Zhichong ◽  
Mohammad Zoynul Abedin
Keyword(s):  
Credit Risk ◽  
Rating System ◽  
Small Enterprises ◽  
Risk Rating

scholarly journals Empirical Credit Risk Ratings of Individual Corporate Bonds and Derivation of Term Structures of Default Probabilities

2019 ◽  
Vol 12 (3) ◽  
pp. 124 ◽  
Author(s):  
Takeaki Kariya ◽  
Yoshiro Yamamura ◽  
Koji Inui
Keyword(s):  
Credit Risk ◽  
Term Structure ◽  
Credit Rating ◽  
Default Probability ◽  
Corporate Bond ◽  
Rating System ◽  
Financial Industry ◽  
Cross Sectional ◽  
Risk Rating ◽  
Rating Method

Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system with rating intervals for the standardized credit risk price spread (S-CRiPS) measure presented by Kariya et al. (2015), where credit information is based on the CRiPS measure, which is the difference between the CB price and its government bond (GB)-equivalent CB price. Second, for each Crisk-homogeneous class obtained through the Crisk-rating system, a term structure of default probability (TSDP) is derived via the CB-pricing model proposed in Kariya (2013), which transforms the Crisk level of each class into a default probability, showing the default likelihood over a future time horizon, in which 1545 Japanese CB prices, as of August 2010, are analyzed. To carry it out, the cross-sectional model of pricing government bonds with high empirical performance is required to get high-precision CRiPS and S-CRiPS measures. The effectiveness of our GB model and the S-CRiPS measure have been demonstrated with Japanese and United States GB prices in our papers and with an evaluation of the credit risk of the GBs of five countries in the EU and CBs issued by US energy firms in Kariya et al. (2016a, b). Our Crisk-rating system with rating intervals is tested with the distribution of the ratings of the 1545 CBs, a specific agency’s credit rating, and the ratings of groups obtained via a three-stage cluster analysis.

Relation between operating parameters and desalination performance of capacitive deionization with activated carbon electrodes

2015 ◽  
Vol 1 (4) ◽  
pp. 516-522 ◽  
Author(s):  
Danyang Liu ◽  
Kuan Huang ◽  
Leijie Xie ◽  
Hao L. Tang
Keyword(s):  
Activated Carbon ◽  
Statistical Modeling ◽  
Carbon Electrodes ◽  
Operating Parameters ◽  
Capacitive Deionization ◽  
Modeling Approach

This work presents a novel attempt at using a statistical modeling approach to predict the desalination performance of CDI.

Adsorptive removal of surfactant using dolochar: A kinetic and statistical modeling approach

2019 ◽  
Vol 92 (2) ◽  
pp. 222-235 ◽  
Author(s):  
Shreya Shami ◽  
Rajesh Roshan Dash ◽  
Akshaya Kumar Verma ◽  
Aditya Kishore Dash ◽  
Abanti Pradhan
Keyword(s):  
Statistical Modeling ◽  
Adsorptive Removal ◽  
Modeling Approach
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