Pricing credit derivatives under incomplete information: a nonlinear-filtering approach |
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Authors: | Rüdiger Frey Wolfgang Runggaldier |
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Institution: | 1. Department of Mathematics, University of Leipzig, 04009, Leipzig, Germany 2. Department of Mathematics, University of Padua, Via Trieste 63, 35121, Padova, Italy
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Abstract: | This paper considers a general reduced-form pricing model for credit derivatives where default intensities are driven by some
factor process X. The process X is not directly observable for investors in secondary markets; rather, their information set consists of the default history
and of noisy price observations for traded credit products. In this context the pricing of credit derivatives leads to a challenging
nonlinear-filtering problem. We provide recursive updating rules for the filter, derive a finite-dimensional filter for the
case where X follows a finite-state Markov chain, and propose a novel particle-filtering algorithm. A numerical case study illustrates
the properties of the proposed algorithms. |
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Keywords: | |
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