Parametrization in the progressively enlarged filtration
Abstract
In this paper, we assume that the filtration F is generated by a d-dimensional Brownian motion W=(W1,·s,Wd)' as well as an integer-valued random measure μ(du,dy). The random variable is the default time and L is the default loss. Let G=\ Gt;t≥ 0\ be the progressive enlargement of F by (,L), i.e, G is the smallest filtration including F such that is a G-stopping time and L is G-measurable. We parameterize the conditional density process, which allows us to describe the survival process G explicitly. We also obtain the explicit G-decomposition of a F martingale and the predictable representation theorem for a (P, G)-martingale by all known parameters. Formula parametrization in the enlarged filtration is a useful quality in financial modeling.
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