Credit Default Swap Spread (CDs) to Predict a Default

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dc.Location2012 HG 1601 S23
dc.SupervisorDr Elango Rengasamy
dc.contributor.authorAl Saadi, Khulood Salem
dc.date.accessioned2014-03-19T11:00:39Z
dc.date.available2014-03-19T11:00:39Z
dc.date.issued2012-12
dc.description.abstractThis paper investigates the ability of the Credit Default Swap Spread (CDSs) to predict a default. As a result, I started to build a regression and correlation model to examine and check if there is a relation between two important variables, which are Credit Default Swap (CDS) and Expected Default Frequency KMV (EDF) KMV. The study concentrates on the degree of variation on the prices for both variables as I believe that if one variable, which should be a predictor, changes the other variable, it should respond to this predication and change its price too. The study concentrates on five U.S. financial institutions, which are Citigroup Inc., JP Morgan Chase & Co., Goldman Sachs Group, Lehman Brother, and Morgan Stanley from 16 January 2007 to 23 May 2011. In conclusion, my analysis approves that the CDSs is classified as either risk exposures accumulator or predictor from year 2007 based on the findings, which prove that there is a relationship between credit default swaps and KMV EDFs.en_US
dc.identifier.other90074
dc.identifier.urihttp://bspace.buid.ac.ae/handle/1234/559
dc.language.isoenen_US
dc.publisherThe British University in Dubai (BUiD)en_US
dc.subjectcredit default swapen_US
dc.subjectExpected Default Frequency (EDF)en_US
dc.subjectcredit risken_US
dc.subjectcounterparty risken_US
dc.subjectclearing houseen_US
dc.subjectcredit ratingen_US
dc.titleCredit Default Swap Spread (CDs) to Predict a Defaulten_US
dc.typeDissertationen_US
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