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Journal of Credit Risk最新文献

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A survey of machine learning in credit risk 信用风险中的机器学习研究
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2021-01-01 DOI: 10.21314/jcr.2021.008
J. Breeden
{"title":"A survey of machine learning in credit risk","authors":"J. Breeden","doi":"10.21314/jcr.2021.008","DOIUrl":"https://doi.org/10.21314/jcr.2021.008","url":null,"abstract":"","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67703765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Bankcard performance during the Great Recession 大衰退时期的银行卡表现
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-12-01 DOI: 10.21314/jcr.2020.271
P. Calem, Julapa Jagtiani, Loretta J. Mester
{"title":"Bankcard performance during the Great Recession","authors":"P. Calem, Julapa Jagtiani, Loretta J. Mester","doi":"10.21314/jcr.2020.271","DOIUrl":"https://doi.org/10.21314/jcr.2020.271","url":null,"abstract":"","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"274 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75071481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The economics of debt collection 债务催收的经济学
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-12-01 DOI: 10.21314/jcr.2020.274
Erik Durbin, Charles J. Romeo
{"title":"The economics of debt collection","authors":"Erik Durbin, Charles J. Romeo","doi":"10.21314/jcr.2020.274","DOIUrl":"https://doi.org/10.21314/jcr.2020.274","url":null,"abstract":"","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"5 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73179405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
From incurred loss to current expected credit loss: a forensic analysis of the allowance for loan losses in unconditionally cancelable credit card portfolios 从已发生的损失到当前预期的信用损失:对无条件可取消信用卡投资组合中贷款损失准备的取证分析
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-12-01 DOI: 10.21314/jcr.2020.273
Jose Canals-Cerda
{"title":"From incurred loss to current expected credit loss: a forensic analysis of the allowance for loan losses in unconditionally cancelable credit card portfolios","authors":"Jose Canals-Cerda","doi":"10.21314/jcr.2020.273","DOIUrl":"https://doi.org/10.21314/jcr.2020.273","url":null,"abstract":"","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"30 4","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The impact of data aggregation and risk attributes on stress testing models of mortgage default 数据聚合和风险属性对抵押贷款违约压力测试模型的影响
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-11-01 DOI: 10.21314/jcr.2020.269
Feng Li,Yan Zhang
{"title":"The impact of data aggregation and risk attributes on stress testing models of mortgage default","authors":"Feng Li,Yan Zhang","doi":"10.21314/jcr.2020.269","DOIUrl":"https://doi.org/10.21314/jcr.2020.269","url":null,"abstract":"Stress testing models have been developed at various levels of data aggregation with or without risk attributes, but there is limited research on the joint impact of these modeling choices. In this paper, we investigate how data aggregation and risk attributes affect the development and performance of stress testing models by studying residential mortgage loan defaults. We develop mortgage default models at various data aggregation levels including loan-level, segment-level, and top-down. We also compare the models with and without risk attributes as control variables. We assess model performance for goodness-of-fit, prediction accuracy, and projection sensitivity for stress testing purposes. We find that the loan-level models do not always win among models with various data aggregation levels, and including risk attributes greatly improves goodness-of-fit and projection accuracy for models of all data aggregation levels. The findings suggest that it is important to consider data aggregation and risk attributes in developing stress testing models.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"104 4","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The loss optimization of loan recovery decision times using forecast cashflows 利用预测现金流对贷款回收决策时间进行损失优化
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-10-12 DOI: 10.21314/JCR.2020.275
A. Botha, Conrad Beyers, P. D. Villiers
{"title":"The loss optimization of loan recovery decision times using forecast cashflows","authors":"A. Botha, Conrad Beyers, P. D. Villiers","doi":"10.21314/JCR.2020.275","DOIUrl":"https://doi.org/10.21314/JCR.2020.275","url":null,"abstract":"A theoretical method is empirically illustrated in finding the best time to forsake a loan such that the overall credit loss is minimised. This is predicated by forecasting the future cash flows of a loan portfolio up to the contractual term, as a remedy to the inherent right-censoring of real-world `incomplete' portfolios. Two techniques, a simple probabilistic model as well as an eight-state Markov chain, are used to forecast these cash flows independently. We train both techniques from different segments within residential mortgage data, provided by a large South African bank, as part of a comparative experimental framework. As a result, the recovery decision's implied timing is empirically illustrated as a multi-period optimisation problem across uncertain cash flows and competing costs. Using a delinquency measure as a central criterion, our procedure helps to find a loss-optimal threshold at which loan recovery should ideally occur for a given portfolio. Furthermore, both the portfolio's historical risk profile and forecasting thereof are shown to influence the timing of the recovery decision. This work can therefore facilitate the revision of relevant bank policies or strategies towards optimising the loan collections process, especially that of secured lending.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46796112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
How a credit run affects asset correlation 信贷挤兑如何影响资产相关性
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-04-23 DOI: 10.2139/SSRN.3582995
Christopher Paulus Imanto
{"title":"How a credit run affects asset correlation","authors":"Christopher Paulus Imanto","doi":"10.2139/SSRN.3582995","DOIUrl":"https://doi.org/10.2139/SSRN.3582995","url":null,"abstract":"This paper analyses the effect of soaring demand in the lending market shortly before a fi nancial crisis (hereinafter \"credit run\"). A credit run affects the asset correlation, which is one of the main parameters in the Internal Ratings-Based Approach (IRBA) of the Basel III framework. In the framework, these coefficients are predetermined and have not been recalibrated since their introduction in the Basel II Accord. This paper not only questions the assumption of a constant asset correlation, which is a fundamental part of the theoretical foundation of the IRBA, but also shows that a credit run increases the asset correlation value through a new approach. Thereby, this paper offers evidence that the asset correlations given in the IRBA are underestimated. In contrast to other asset correlation studies, this paper provides a new approach which is compatible with the foundation of the IRBA. Assuming asset correlations are calibrated correctly in the IRBA, a 2% downturn add-on may be adequate.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"33 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73497861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Contagious defaults in a credit portfolio: a Bayesian network approach 信贷组合中的传染性违约:贝叶斯网络方法
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-03-01 DOI: 10.21314/jcr.2020.257
Ioannis Anagnostou,Javier Sanchez Rivero,Sumit Sourabh,Drona Kandhai
{"title":"Contagious defaults in a credit portfolio: a Bayesian network approach","authors":"Ioannis Anagnostou,Javier Sanchez Rivero,Sumit Sourabh,Drona Kandhai","doi":"10.21314/jcr.2020.257","DOIUrl":"https://doi.org/10.21314/jcr.2020.257","url":null,"abstract":"The robustness of credit portfolio models is of great interest for financial institutions and regulators, since misspecified models translate into insufficient capital buffers and a crisis-prone financial system. In this paper, the authors propose a method to enhance credit portfolio models based on the model of Merton by incorporating contagion effects. While, in most models, the risks related to financial interconnectedness are neglected, the authors use Bayesian network methods to uncover the direct and indirect relationships between credits while maintaining the convenient representation of factor models. A range of techniques to learn the structure and parameters of financial networks from real credit default swaps data are studied and evaluated. Their approach is demonstrated in detail in a stylized portfolio, and the impact on standard risk metrics is estimated.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"215 ","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Covid-19 and the credit cycle Covid-19与信贷周期
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2020-01-01 DOI: 10.21314/jcr.2020.262
Edward Altman
{"title":"Covid-19 and the credit cycle","authors":"Edward Altman","doi":"10.21314/jcr.2020.262","DOIUrl":"https://doi.org/10.21314/jcr.2020.262","url":null,"abstract":"The Covid-19 health crisis has dramatically affected just about every aspect of the economy, including the transition from a record long benign credit cycle to a stressed one, with still uncertain dimensions This paper seeks to assess the credit climate from just before the unexpected global health crisis catalyst to its immediate and extended impact We analyze the performance of several key indicators of the nature of credit cycles: default and recovery rates on high-yield bonds, and the number of large firm bankruptcies that we expect over the next twelve months and beyond;yield spreads and distress ratios;and liquidity Our focus is primarily on the nonfi-nancial corporate debt market in the United States, which reached a record percent-age of gross domestic product at the end of 2019 as firms increased their debt to take advantage of record low interest rates, and investor appetite grew for higher promised yields on risky fixed-income assets We also examine the leveraged loan and collater-alized loan obligation markets, as well as the increasingly large and important BBB tranche of the corporate bond market Specifically, we discuss the latter’s vulnerabil-ity to downgrades over the expected downturn in the real economy and this vulnera-bility’s potential impact on expected default rates by “crowding out” low-quality debt of other firms (some of which we believe are “zombies”) Using Z-scores for a sample of BBB companies between 2007 and 2019, we analyze this largest component of the corporate bond market to provide some evidence on the controversial debate as to whether there has been ratings inflation or, perhaps, persistent overvaluation of the nonfinancial corporate debt market since the last financial crisis © 2020 Infopro Digital Risk (IP) Limited","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"46 ","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Elliptical and Archimedean Copula Models: An Application to the Price Estimation of Portfolio Credit Derivatives 椭圆和阿基米德联结模型:在组合信用衍生品价格估计中的应用
IF 0.3 4区 经济学
Journal of Credit Risk Pub Date : 2019-11-24 DOI: 10.21314/jcr.2020.263
Matthias Ehrhardt, Nneka Umeorah, Phillip Mashele
{"title":"Elliptical and Archimedean Copula Models: An Application to the Price Estimation of Portfolio Credit Derivatives","authors":"Matthias Ehrhardt, Nneka Umeorah, Phillip Mashele","doi":"10.21314/jcr.2020.263","DOIUrl":"https://doi.org/10.21314/jcr.2020.263","url":null,"abstract":"This paper explores the impact of elliptical and Archimedean copula models on the valuation of basket default swaps. We employ Monte Carlo simulation, in connection with the copula models, to estimate the default times and to calculate the swap payment legs and the cumulative swap premium. The numerical experiments reveal some sensitivity analysis on the impact of swap parameters on the fair prices of the 𝑛th-to-default swaps. Finally, using the results presented, an appropriate choice of copula model can be made based on the computation time of the valuation process, and such a choice hugely affects the quantitative risk analysis of the portfolio.","PeriodicalId":44244,"journal":{"name":"Journal of Credit Risk","volume":"6 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82397881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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