City Research Online

Abstract

The study of credit derivatives is one of the most popular and controversial issues that concerns the entire financial industry. Increases of defaults and bankruptcies during the recent credit crunch has stipulated a heated debate about the adequacy of the existing pricing and hedging methodologies for credit derivatives portfolios. The main objective of this thesis is to propose and evaluate a treatable framework that addresses many of the deferences of the standard market model for portfolios of credit instruments. After review and product introductions in CHAPTER 1 we first summarize the common simulation methods for pricing portfolio credit derivatives, then we propose an alternative methodology that is based on an economical sense of the models and market observables in CHAPTER 2. Such simulation method provides a testing environment which houses the asset value based models with reliable assumptions. Meanwhile, a PCA analysis on CDO market spreads is performed on market data in CHAPTER 3. In CHAPTER 4, we develop an old school dynamic model for credit derivative valuation, it match the market needs, fit quoted spreads while providing time evolution using historical market observable measure. Finally, combining together the model and simulation framework, we are able to construct hedging strategies based on simulation results in CHAPTER 5. We mainly focus on the utilization of default probabilities in pricing techniques and a close-form formula is provided to calculate probability of default from the proposed growth rate factor.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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