信用计量方法和风险信用价值(Credit VaR)

Y. Malhotra
{"title":"信用计量方法和风险信用价值(Credit VaR)","authors":"Y. Malhotra","doi":"10.2139/ssrn.3783490","DOIUrl":null,"url":null,"abstract":"Described by Hull (2011, 2012) as ‘a procedure for calculating credit value at risk’, CreditMetrics methodology (RiskMetrics Group 2007) is used for assessing portfolio risk due to changes in bond or debt value caused by credit quality changes including credit migration (upgrades and downgrades), as well as, default. It measures the uncertainty in forward value of the bond portfolio at the risk horizon caused by such credit events. Changes in debt value could be small in case of credit quality ratings change; however, they could be enormous, 50% to 90%, in case of default. Characterized by a long downside tail, credit-returns are highly-skewed and fat-tailed and thus far from the Gaussian normal distribution assumptions about market risk in VaR (Fig. 1). In the portfolio context, based upon correlation of credit quality moves across obligors, CreditMetrics assesses both value-at-risk (VaR), i.e., the volatility of value, as well as expected losses (EL). By distinguishing high quality well-diversified portfolios from low-quality concentrated portfolios, it offers better understanding of credit risk in terms of diversification benefits and concentration risk compared to mandated standard capital adequacy measures.","PeriodicalId":284021,"journal":{"name":"International Political Economy: Investment & Finance eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CreditMetrics Methodology and Credit Value at Risk (Credit VaR)\",\"authors\":\"Y. Malhotra\",\"doi\":\"10.2139/ssrn.3783490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Described by Hull (2011, 2012) as ‘a procedure for calculating credit value at risk’, CreditMetrics methodology (RiskMetrics Group 2007) is used for assessing portfolio risk due to changes in bond or debt value caused by credit quality changes including credit migration (upgrades and downgrades), as well as, default. It measures the uncertainty in forward value of the bond portfolio at the risk horizon caused by such credit events. Changes in debt value could be small in case of credit quality ratings change; however, they could be enormous, 50% to 90%, in case of default. Characterized by a long downside tail, credit-returns are highly-skewed and fat-tailed and thus far from the Gaussian normal distribution assumptions about market risk in VaR (Fig. 1). In the portfolio context, based upon correlation of credit quality moves across obligors, CreditMetrics assesses both value-at-risk (VaR), i.e., the volatility of value, as well as expected losses (EL). By distinguishing high quality well-diversified portfolios from low-quality concentrated portfolios, it offers better understanding of credit risk in terms of diversification benefits and concentration risk compared to mandated standard capital adequacy measures.\",\"PeriodicalId\":284021,\"journal\":{\"name\":\"International Political Economy: Investment & Finance eJournal\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Political Economy: Investment & Finance eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3783490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Political Economy: Investment & Finance eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3783490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

赫尔(2011年、2012年)将CreditMetrics方法描述为“计算风险中的信用价值的程序”,该方法(RiskMetrics Group 2007年)用于评估因信用质量变化(包括信用迁移(升级和降级)以及违约)引起的债券或债务价值变化而导致的投资组合风险。它衡量由此类信用事件引起的风险水平上债券投资组合远期价值的不确定性。如果信用质量评级发生变化,债务价值的变化可能很小;然而,在违约的情况下,它们可能是巨大的,50%到90%。以长下行尾部为特征,信贷回报是高度倾斜和厚尾的,因此与VaR中市场风险的高斯正态分布假设相距甚远(图1)。在投资组合背景下,基于债务人之间信贷质量移动的相关性,CreditMetrics评估风险价值(VaR),即价值的波动性,以及预期损失(EL)。通过区分高质量的分散投资组合和低质量的集中投资组合,与强制性标准资本充足率指标相比,它可以更好地理解分散收益和集中风险方面的信用风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CreditMetrics Methodology and Credit Value at Risk (Credit VaR)
Described by Hull (2011, 2012) as ‘a procedure for calculating credit value at risk’, CreditMetrics methodology (RiskMetrics Group 2007) is used for assessing portfolio risk due to changes in bond or debt value caused by credit quality changes including credit migration (upgrades and downgrades), as well as, default. It measures the uncertainty in forward value of the bond portfolio at the risk horizon caused by such credit events. Changes in debt value could be small in case of credit quality ratings change; however, they could be enormous, 50% to 90%, in case of default. Characterized by a long downside tail, credit-returns are highly-skewed and fat-tailed and thus far from the Gaussian normal distribution assumptions about market risk in VaR (Fig. 1). In the portfolio context, based upon correlation of credit quality moves across obligors, CreditMetrics assesses both value-at-risk (VaR), i.e., the volatility of value, as well as expected losses (EL). By distinguishing high quality well-diversified portfolios from low-quality concentrated portfolios, it offers better understanding of credit risk in terms of diversification benefits and concentration risk compared to mandated standard capital adequacy measures.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Impact of Socioemotional Wealth on Corporate Reporting Readability in a Multinational Family-Controlled Firm Stock Ownership of Federal Judges and its Impact on Corporations Place-Based Policies and the Geography of Corporate Investment Foreign bias in equity portfolios: Informational advantage or familiarity bias? Quantifying the Impact of Impact Investing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1