An application to credit risk of a hybrid Monte Carlo-Optimal quantization method

Giorgia Callegaro (1) , Abass Sagna (2)

1 SNS - Scuola Normale Superiore di Pisa
2 LPMA - Laboratoire de Probabilités et Modèles Aléatoires

In this paper we use a hybrid Monte Carlo-Optimal quantization method to approximate the conditional survival probabilities of a firm, given a structural model for its credit defaul, under partial information. We consider the case when the firm's value is a non-observable stochastic process $(V_t)_{t \geq 0}$ and inverstors in the market have access to a process $(S_t)_{t \geq 0}$, whose value at each time t is related to $(V_s, s \leq t)$. We are interested in the computation of the conditional survival probabilities of the firm given the "investor information". As a application, we analyse the shape of the credit spread curve for zero coupon bonds in two examples.

Mots clés: credit risk; structural approach; survival probabilities; partial information; filtering; optimal quantization; Monte Carlo method

Mots clés: Monte Carlo method.

Domaines: Finance quantitative [q-fin.CP]; Probabilités [math.PR]; Gestion des risques [q-fin.RM]

Giorgia Callegaro, Abass Sagna. An application to credit risk of a hybrid Monte Carlo-Optimal quantization method. The Journal of Computational Finance, 2013, 16 (123-156). ⟨hal-00400666⟩