On the pricing and measuring corporate credit risk : A Comparative analysis on the structural and reduced form credit risk models

Corporate credit risk in fixed income markets refers to risk that debt issuing company will default before the maturity of the debt or to decrease in the market value of debt due to decreasing credit quality. A number of quantitative credit risk models have been developed to measure probability of default and/or credit spreads of fixed income investments. These models can be roughly divided into two categories based on their approach to credit risk modelling; structural and reduced form models. Several commercial applications have been developed based on both model branches and used in financial markets as tool for analyzing real life investment decisions. The aim of this thesis is to introduce the theoretical framework behind structural and reduced form credit risk models and present a comparative analysis on the strengths and weaknesses of different models. A base case model for structural (Merton 1974) and for reduced form (Jarrow-Turnbull 1995) is presented in more detail and differences are discussed based on earlier academic research in the area. Even the objectives of the models are similar the two approaches are totally different from the theoretical point of view. Structural models are based on Merton´s model and use Black- Scholes option pricing framework as foundation of credit risk analysis. Reduced form models instead can be considered as a statistical approach to credit risk modelling using market data on bond prices and credit spreads to measure probability of default. Empirical part of the thesis consists of review of several empirical studies testing the empirical soundness of different structural and reduced form models. The aim of this part is to find reasoning to recommend either structural or reduced form models for investor use. Main findings suggest that when choosing credit risk model the purpose of the use becomes a decisive factor. It can be argued that structural models in general are more suitable for analyzing credit risk of individual companies with company specific needs due to their ability to offer economic causality. In the other hand the reduced form models could be recommended to use for trading and hedging purposes for traders and credit managers working with liquid bond markets. Reduced form models are highly data sensitive and need high quality market data. Several studies suggest that structural models perform better when working with lower rated bonds (below investment grade) whereas reduced form models are more suitable for higher rated bonds (investment grade). Reduced form models can be seen as more modern approach to credit risk modelling