University of Twente Student Theses


Credit default swap spread model : descriptive and predictive, insight in the determinants of cds spreads

Wemmenhove, Danny (2009) Credit default swap spread model : descriptive and predictive, insight in the determinants of cds spreads.

[img] PDF
Abstract:Credit default swaps have started trading at the beginning of this century. There is still a lot to be discovered on the subject of credit default swaps and especially their spreads. The spreads are considered to be a price indication of the risk associated to the credit default swap. Or so to say; the risk premium one is willing to pay. How this risk premium is determined and what makes it go up and down are questions which are mostly still unanswered. This study investigates the determinants of credit default swap spreads. The aim of this project is to find out which factors describe a credit default swap spread, and which factors can give an indication in terms of forecast. The factors taken into account are divided into fundamental, market and macro variables. Each variable is weekly based over the period from 2004 Q1 to 2008 Q2. In this research 146 non-financial European companies have been used for firm-specific data. To find the determinants, the ordinary least-squares methodology has been applied. Through the usage of correlation matrices, univariate regressions and multivariate regressions the variables which are used in the final model have been determined. Together with the requirements set by Kempen Capital Management, the variables that show its worth in describing the spread are: Net Debt divided by EBITDA, Return On Assets, ln(total Assets), Implied volatility over 3 months, the yield difference between AAA corporates and BBB corporates, and as a correlation factor with the market; Beta. This model seems to perform quite well. Applied to several companies, the model gives an indication of where the spread should be. Testing the model the out-of-sample period of 2008 Q3, resulted in increasing confidence in the performance of the describing model. For the forecasting model, the same variables turned out to be the most suitable to use, with Beta left out of the determinants. Although the R² of the forecasting model is lower than the describing model, it still seems to perform well. Applying the forecasting model to the period of 2007 Q1 to 2008 Q3 with a one month forecast, companies proved to be profitable. This profit is achieved by setting a short/long trading rule determined by the forecasting model. Using the forecast model only on investment grade companies results in higher profits. Although the profits look very promising, one has to be careful in putting all his faith in the forecasting model. Credit default swap spreads are difficult to interpret. However, the describing model and the forecasting model are a step in the right direction.
Item Type:Essay (Master)
Kempen Capital Management
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page