{"title":"信用违约互换期限结构形状的信号特性","authors":"J. Castellanos, N. Constantinou, W. Ng","doi":"10.21314/JOR.2015.298","DOIUrl":null,"url":null,"abstract":"This paper studies the predictive power of the time-varying shape of the credit default swap (CDS) term structure to explain changes in future implied and excess implied volatility (implied volatility of the company over and above the market volatility) and therefore provide a leading sign of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (shape indicator) to distinguish between \"good\" and \"bad\" CDS curves. Applying the methodology to twenty US-traded companies from the financial and non-financial sectors, we find that the credit market is generally a leading indicator for movements in the volatility market during the subprime crisis. After confirming the strong link between CDSs and implied volatility markets (the average R2 per sector between 36% and 63% is obtained using the Nelson-Siegel parameter and shape indicator), a partial F -test is executed to see if additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names, and it is particularly significant for Lehman Brothers.","PeriodicalId":46697,"journal":{"name":"Journal of Risk","volume":"1 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2015-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The Signalling Properties of the Shape of the Credit Default Swap Term Structure\",\"authors\":\"J. Castellanos, N. Constantinou, W. Ng\",\"doi\":\"10.21314/JOR.2015.298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the predictive power of the time-varying shape of the credit default swap (CDS) term structure to explain changes in future implied and excess implied volatility (implied volatility of the company over and above the market volatility) and therefore provide a leading sign of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (shape indicator) to distinguish between \\\"good\\\" and \\\"bad\\\" CDS curves. Applying the methodology to twenty US-traded companies from the financial and non-financial sectors, we find that the credit market is generally a leading indicator for movements in the volatility market during the subprime crisis. After confirming the strong link between CDSs and implied volatility markets (the average R2 per sector between 36% and 63% is obtained using the Nelson-Siegel parameter and shape indicator), a partial F -test is executed to see if additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names, and it is particularly significant for Lehman Brothers.\",\"PeriodicalId\":46697,\"journal\":{\"name\":\"Journal of Risk\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2015-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.21314/JOR.2015.298\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/JOR.2015.298","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
The Signalling Properties of the Shape of the Credit Default Swap Term Structure
This paper studies the predictive power of the time-varying shape of the credit default swap (CDS) term structure to explain changes in future implied and excess implied volatility (implied volatility of the company over and above the market volatility) and therefore provide a leading sign of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (shape indicator) to distinguish between "good" and "bad" CDS curves. Applying the methodology to twenty US-traded companies from the financial and non-financial sectors, we find that the credit market is generally a leading indicator for movements in the volatility market during the subprime crisis. After confirming the strong link between CDSs and implied volatility markets (the average R2 per sector between 36% and 63% is obtained using the Nelson-Siegel parameter and shape indicator), a partial F -test is executed to see if additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names, and it is particularly significant for Lehman Brothers.
期刊介绍:
This international peer-reviewed journal publishes a broad range of original research papers which aim to further develop understanding of financial risk management. As the only publication devoted exclusively to theoretical and empirical studies in financial risk management, The Journal of Risk promotes far-reaching research on the latest innovations in this field, with particular focus on the measurement, management and analysis of financial risk. The Journal of Risk is particularly interested in papers on the following topics: Risk management regulations and their implications, Risk capital allocation and risk budgeting, Efficient evaluation of risk measures under increasingly complex and realistic model assumptions, Impact of risk measurement on portfolio allocation, Theoretical development of alternative risk measures, Hedging (linear and non-linear) under alternative risk measures, Financial market model risk, Estimation of volatility and unanticipated jumps, Capital allocation.