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Abstract:
We suggest a methodology for valuing corporate securities that allows the straightforward derivation of closed form solutions for complex capital structure scenarios. The tractability of the approach stems from its modularity - we provide a number of intuitive building blocks that are sufficient for valuation in most typical situations. A further advantage of our approach is that it makes economic interpretation far easier than what is typically possible with other approaches such as solving partial differential equations. As examples we consider a corporate coupon bond with discrete payments and debt subject to strategic debt service.

Abstract:
We suggest a methodology for valuing corporate securities that allows the straightforward derivation of closed form solutions for complex capital structure scenarios. The tractability of the approach stems from its modularity - we provide a number of intuitive building blocks that are sufficient for valuation in most typical situations. A further advantage of our approach is that it makes economic interpretation far easier than what is typically possible with other approaches such as solving partial differential equations. As examples we consider a corporate coupon bond with discrete payments and debt subject to strategic debt service.

Abstract:
A difficulty which arises when implementing structural bond pricing models is the estimation of the value and risk of the firm's assets - neither of which is directly observable. We perform a simulation experiment in order to evaluate a maximum likelihood method applicable to this problem. Contrasting the performance of the maximum likelihood estimators to that of estimators traditionally used in academia and industry, we find strong support for the maximum likelihood approach. In fact, the inefficiency of the traditional estimator may help to explain the failure of past attempts to implement structural bond pricing models.

Default risk, corporate bonds, credit spreads, maximum likelihood

Abstract:
A difficulty which arises when implementing structural bond pricing models is the estimation of the value and risk of the firm's assets - neither of which is directly observable. We perform a simulation experiment in order to evaluate a maximum likelihood method applicable to this problem. The properties of the bond price estimators are examined using four theoretical bond pricing models: the Black & Scholes (1973) / Merton (1974) model, the Leland & Toft (1996) model, the Briys & de Varenne (1997) model, as well as the Ericsson & Reneby (2001) model. We contrast the performance of the maximum likelihood estimators to that of estimators traditionally used in academia and industry. The results are strongly supportive of the maximum likelihood approach. In fact, the inefficiency of the traditional estimator may explain the failure of past attempts to implement structural bond pricing models.

Credit Risk, Maximum Likelihood, Corporate Bonds

Abstract:
Using a set of structural models, we evaluate bond yield spreads and the price of default protection for a sample of US corporations. Theory predicts that if credit risk alone explains these two quantities, their magnitudes should be similar. Our findings concur with previous results that bond yield spreads are underestimated. However, this is not systematically the case for CDS premia, which in our dataset are much lower than bond spreads. Furthermore, our results highlight the strong relationship between bond residuals and nondefault proxies, in particular illiquidity. CDS residuals exhibit no such relations. This suggests that the bond spread underestimation by our structural models may not stem from their inability to properly account for default risk, but rather from the importance of the omitted risk factors.

Credit risk, credit derivatives, corporate bonds, structural models

Abstract:
We suggest a comprehensive model that values securities as options and consequently ordinary stock options as compound options. Extending the basic Black-Scholes model, we can incorporate common contractual features and stylized facts.

More specifically, we derive a closed form solution for the price of a call option on a down-and-out call. We then show how the obtained result can be generalized in order to price options on complex corporate securities, allowing among other things for corporate taxation, costly financial distress and deviations from the absolute priority rule. The characteristics of the model are illustrated with numerical examples.

Abstract:
We develop a structural bond pricing approach and implement it
on a large panel of US industrial bonds using an efficient maximum
likelihood methodology. We evaluate the model's ability to predict
yield spread levels and changes out-of-sample. Errors are smaller and
distinctly less variable than those found in previous implementations
of structural as well as reduced form models. Furthermore, our analysis
provide evidence that bond yield spreads incorporate a substantial
liquidity component on top of the default spread structural models are
designed to capture.

Abstract:
Reduced form credit risk models are often thought to be better suited for pricing corporate bonds than structural models. In this paper we challenge this view; by conditioning not only on equity but also on bond and dividend information, our structural model performs well in comparison to previously tested reduced form models. Moreover, we consider pricing of bond portfolios and show that model errors are to a large extent diversifiable.

Credit risk, yield spreads, structural models