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Exploring the Factors of the Credit Default Swap Spread in Different Business Sectors
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Marknadsfaktorers inverkan pa spreaden for kreditswappar inom olika aarsomraden (Swedish)
Abstract [en]

In this study, we investigate the effect of market factors on credit default swap spreads aggregated by specific business sectors. The market factors include commodity spot prices, foreign exchange spot prices, equity index prices and interest swap rates. Using linear regression modelling, we find that many of the factors are correlated to the credit default swap spreads. To examine the collective effect of the factors on the credit default swap spread, we produce linear models using best subsets regression.

The empirical results suggest that many of the factors are significant in explaining the credit default swap. Our models show significance of regression on a 99% level, and most variables have correlations that are consistent with previous research. Notably, we find that the factors show different levels of significance for each of the sectors. Based on this investigation we conclude that there in fact exist relationships between the market factors and the credit default swap spread changes, and that these relationships are business sector specific.

Abstract [sv]

I denna studie undersöker vi marknadsfaktorers inverkan på spreaden för kreditswappar aggregerade med avseende på utvalda affärsområden. Marknadsfaktorerna som inkluderas i studien är avistapriser för råvaror, avistapriser för utländska valutakurser, aktieindex priser och ränteswapkurser. Genom modellering med linjärregression finner vi att många av faktorerna påvisar korrelation med spreaden för kreditswappar. För att unders öka den gemensamma effekten som faktorerna har på spreaden för kreditswappar skapar vi linjära modeller genom att testa alla möjliga permutationer av variablerna.

De empiriska resultaten antyder att många av faktorerna uppvisar signifikans i sin förklarande förmåga av spreaden för kreditswappar. Regressionsmodellerna påvisar signifikans på en 99%-nivå och majoriteten av variablerna visar på korrelationer som återspeglar tidigare forskning inom området. I synnerhet ser vi att faktorerna visar olika signifikansnivåer för de olika affärsområdena. Därav dras slutsatsen att det finns ett samband mellan marknadsfaktorerna och spreaden för kreditswappar, samt att dessa är affärsområdesspecifika.

Place, publisher, year, edition, pages
2017.
Series
TRITA-MAT-K ; 2017:
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-210161OAI: oai:DiVA.org:kth-210161DiVA, id: diva2:1117002
External cooperation
SEB
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2017-06-28 Created: 2017-06-28 Last updated: 2017-06-28Bibliographically approved

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