Randomization in the First Hitting Time Problem∗
نویسندگان
چکیده
In this paper we consider the following inverse problem for the first hitting time distribution: given a Wiener process with a random initial state, probability distribution, F (t), and a linear boundary, b(t) = μt, find a distribution of the initial state such that the distribution of the first hitting time is F (t). This problem has important applications in credit risk modeling where the process represents, so-called, distance to default of an obligor, the first hitting time represents a default event and the boundary separates the healthy states of the obligor from the default state. We show that randomization of the initial state of the process makes the problem analytically tractable. Primary Subjects: 60G40 Secondary Subjects: 91B70
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In this paper we consider the following inverse problem for the first hitting time distribution: given a Wiener process with a random initial state, probability distribution, F (t), and a linear boundary, b(t) = μt, find a distribution of the initial state such that the distribution of the first hitting time is F (t). This problem has important applications in credit risk modeling where the pro...
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