BSM and theoretical elements of Credit spreads changes

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Credit risk models & credit rating

According to Van Denenter of Kamakura Corporation, a vendor of credit risk models is not to simply rely on credit ratings as a forecaster of default. This is due to the following reasons which include; ratings are discrete with a limited number of rating grades. In contrast, default probability continues and ranges from 0% to 100%. While ratings are updated very infrequently, default probabilities can be estimated on real-time basis. Finally, there is no clear maturity for a credit rating. While there is a separate short-and long-term credit rating, credit risk models provide a default probability by maturity, for instance, term structure of default probabilities. (Fabozzi, 2006)

 Credit risk models

Credit risk models are used in fixed income analysis. These models are categorized as either structural models or reduced-form models. Structural model is also called (BSM)2 due to grounders of these models; Black- Scholes-Merton (1973These models are used for controlling, measuring and predicting portfolio’s credit risk. Both structural models and reduced-form models assume that the information reported by the issuing corporations is accurate. However, corporate bankruptcies in recent years that have been attributable to fraud and opaque/inaccurate financial accounting data have made practitioners aware that when modeling credit risk, there must be consideration of the possibility that information is imperfect. This has led to the development of incomplete information models. One such model that combines the structural and reduced-form models but incorporates incomplete information has been proposed by Giesecke and Goldberg. (Fabozzi, 2006)

Historical background of BSM

Structural models were developed by Merton (1974) and the model is based on a previous model for the pricing of options on stock by Fischer Black and Myron Scholes (1973). In the irst half of the 1970s, Black, Scholes and Merton presented the fundamental theory to explain structural models (BSM). The basic idea is that a company defaults on its debt if the value of its assets falls below a certain default point and that the value of a corporate bond can be modeled as an option on these assets. Because of this, structural models are also known as “firm-value models. (Fabozzi, 2006) For further information about structural models, see (Fischer Black and Myron Scholes, “the pricing of option and Corporate Liabilities, “Journal of Political Economy, 81 (1973), pp.637-654)
According to Wesley Phoa of Capital Groups Companies, structural models have been used by bond portfolio mangers in one or more of the following ways: to forecast changes in corporate bond credit spreads, to evaluate sensitivity of corporate bond credit spreads to equity prices and to estimate a corporate bond’s default risk, to predict rating changes. (Westly Phoa, “Implications of Merton Models for Corporate Bond Investors,” Chapter 16 in Fabozzi, 2006)

Extension of (BSM) and previously made studies

Structural models were developed by Merton (1974), BSM model has been extended and modified. Studies showed that BSM model can occur not only at maturity but at any time before maturity date. The underlying legal principle here is that there are typically covenants in a typical bond indenture granting the bondholders the right to restructure the corporation should the value of corporate assets fall below a given amount, referred to as a default barrier and this explained by Black and Cox (1976). (Fabozzi, 2006) In all of these models, a company is supposed to default when the value of its assets reaches a certain threshold level.
Litterman and Scheinkman (1991) explained that most differences in the term structure of American Treasury yields could be illustrated by terms of the level of the yield curve and its slope. Here, they used a measurement of the yield curve by the three-month T-bill yield.

1 Introduction 
1.1 Background
1.2 Problem Discussion
1.3 Research question
1.5 Delimitations
1.6 The structure of this thesis
2 Theoretical Framewor
2.1 Credit risk
2.1.1 Risks related to investments of bonds.
2.1.2 Credit market and credit spread
2.1.3 Credit rating
2.1.4 Credit risk models & credit rating
2.1.5 Credit risk models
2.2 Historical background of BSM .
2.3 Extension of (BSM) and previously made studies .
2.4 BSM and theoretical elements of Credit spreads changes
3 Method.
3.1 Quantitative and qualitative methods
3.2 Linear Regression Analysis .
3.3 Statistical Metho
3.4 Overview of Data used in the study
In order to be able to run a regression analysis we needed to define the
dependent variables and independent variabl
3.5 Dependent and Independent variables.
3.5.1 The dependent variable
3.5.2 The independent variables
3.6 Reliability and Validi
3.6.1 Reliability
3.6.2 Validity .
4 Empirical study
4.1 Hypothesi
4.2 Model
4.3 Credit spread change
5 Analysis..
6 Conclusions

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What factors are driving forces for credit spreads?