The main objective of the thesis is to investigate how the price of a credit default swap is determined. We try to determine which factors that are the most influential when determining the level of the credit spread. The thesis starts off by giving an outline of the market for credit derivatives and a definition of credit risk. Then we indentify the characteristics of the credit default swap contract and the credit spread. The empirical research model is built on Merton’s traditional model for pricing of credit risk, as well as relevant previous research by Benkert, Ericsson et al., Collin-Dufresne et al., and Campbell & Taksler. Ordinary least squares regressions are used to describe the relationship between the credit spread and the different independent variables. The companies represented in the dataset has been collected from CDX NA IG index and the S&P 500 index using Bloomberg, and the time horizon for our analysis is from January 2006 to January 2012. Both macroeconomic and firm-specific factors are important when determining the credit default swap premium. The result suggests that equity volatility, both implied and historical, are essential for the level of credit risk. Equity volatility alone explains about 40 percent of the price on the CDS. As expected, credit rating has a significant impact on the credit spread. The three theoretical variables suggested by Merton, the risk free rate, debt ratio and volatility, also have a significant impact on the credit spread. We found that growth in gross domestic product and liquidity also influenced the spread. These factors were however, to some extent, influenced by the volatility measures. Unlike previous research, we managed to find a significant relationship between the credit spread and liquidity. When equity return was used as a lagged variable it had a greater impact on the credit spread compared to when it was represented as the daily change in the stock price. Since the model has a constant explanatory power on a yearly basis, and the estimated parameters are highly volatile during the time period, the robustness checks suggest that the model comes to a better use on a yearly level than for a longer time period. The reason is perhaps that the time period in question contains several years of financial distress and economic downturns.
|Educations||MSc in Finance and Accounting, (Graduate Programme) Final Thesis|
|Number of pages||132|