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

Giorgia Callegaro () and Abass Sagna ()
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Giorgia Callegaro: SNS - Scuola Normale Superiore di Pisa
Abass Sagna: LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique

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Abstract: 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.

Keywords: credit risk; structural approach; survival probabilities; partial information; filtering; optimal quantization; Monte Carlo method; Monte Carlo method. (search for similar items in EconPapers)
Date: 2013
Note: View the original document on HAL open archive server: https://hal.science/hal-00400666
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Published in The Journal of Computational Finance, 2013, 16 (123-156)

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