Valuation of default sensitive claims under imperfect information.

We propose an evaluation method for financial assets subject to default risk, when investors face imperfect information about the state variable triggering the default. The model we propose generalizes the one by Duffie and Lando (2001) in the following way:(i)it incorporates informational noise in continuous time, (ii) it respects the (H) hypothesis, (iii) it precludes arbitrage from insiders. The model is sufficiently general to encompass a large class of structural models. In this setting we show that the default time is totally inaccessible in the market’s filtration and derive the martingale hazard process. Finally, we provide pricing formulas for default-sensitive claims and illustrate with particular examples the shapes of the credit spreads and the conditional default probabilities. An important feature of the conditional default probabilities is they are non Markovian. This might shed some light on observed phenomena such as the ”rating momentum”.hybrid models; default sensitive claims;

Valuation of default-sensitive claims under imperfect information (Publisher's Erratum)

We propose a valuation method for financial assets subject to default risk, where investors cannot observe the state variable triggering the default but observe a correlated price process. The model is sufficiently general to encompass a large class of structural models and can be seen as a generalization of the model of Duffie and Lando (Econometrica 69:633-664, [2001]). In this setting we prove that the default time is totally inaccessible in the market's filtration and derive the conditional default probabilities and the intensity process. Finally, we provide pricing formulas for default-sensitive claims and illustrate in particular examples the shapes of the credit spread

Information Asymmetry in Pricing of Credit Derivatives

We study the pricing of credit derivatives with asymmetric information. The managers have complete information on the value process of the firm and on the default threshold, while the investors on the market have only partial observations, especially about the default threshold. Different information structures are distinguished using the framework of enlargement of filtrations. We specify risk neutral probabilities and we evaluate default sensitive contingent claims in these cases

Credit Spreads and Incomplete Information

A new model is presented which produces credit spreads that do not converge to zero for short maturities. Our set-up includes incomplete, i.e., delayed and asymmetric information. When the financial market observes the company's earnings with a delay, the effect on both default policy and credit spreads is negligible, compared to the Leland (1994) model. When information is asymmetrically distributed between the management of the company and the financial market, short credit spreads do not converge to zero. This is result is similar to the Duffie and Lando (2001) model, although our simpler model improves some limitations in their set-up. Short interest rates from our model are used to illustrate effects similar to the dry-up in the interbank market experienced after the summer of 2007.Credit risk; credit spreads; delayed information; asymmetric information

Conditional hitting time estimation in a nonlinear filtering model by the Brownian bridge method

The model consists of a signal process $X$ which is a general Brownian diffusion process and an observation process $Y$, also a diffusion process, which is supposed to be correlated to the signal process. We suppose that the process $Y$ is observed from time 0 to $s>0$ at discrete times and aim to estimate, conditionally on these observations, the probability that the non-observed process $X$ crosses a fixed barrier after a given time $t>s$. We formulate this problem as a usual nonlinear filtering problem and use optimal quantization and Monte Carlo simulations techniques to estimate the involved quantities