Conditional survival probabilities under partial information: a recursive quantization approach with applications

Cheikh Mbaye (1) , Abass Sagna (2) , Frédéric Vrins (1)

1 UCL - Université Catholique de Louvain = Catholic University of Louvain
2 LaMME - Laboratoire de Mathématiques et Modélisation d'Evry

We consider a structural model where the survival/default state is observed together with a noisy version of the firm value process. This assumption makes the model more realistic than most of the existing alternatives, but triggers important challenges related to the computation of conditional default probabilities. In order to deal with general diffusions as firm value process, we derive a numerical procedure based on the recursive quantization method to approximate it. Then, we investigate the error approximation induced by our procedure. Eventually, numerical tests are performed to evaluate the performance of the method, and an application is proposed to the pricing of CDS options.

Keywords: default model; structural model; noisy information; non-linear filtering; credit risk

Domains: Probability [math.PR]

Cheikh Mbaye, Abass Sagna, Frédéric Vrins. Conditional survival probabilities under partial information: a recursive quantization approach with applications. The Journal of Computational Finance, 2022, 22 (1). ⟨hal-02281006v2⟩