The inverse first passage time problem asks whether, for a Brownian motion $B$ and a nonnegative random variable $\zeta$, there exists a time-varying barrier $b$ such that $\mathbb{ P}\{ B_s>b(s),0\leq s\leq t\}=\mathbb{ P}\{ \zeta>t\}$. We study a "smoothed" version of this problem and ask whether there is a "barrier" $b$ such that $ \mathbb{ E}[\exp(-\lambda\int_0^t\psi(B_s-b(s))\,ds)]=\mathbb{ P}\{ \zeta >t\}$, where $\lambda$ is a killing rate parameter, and $\psi:\mathbb{ R}\to[0,1]$ is a nonincreasing function. We prove that if $\psi$ is suitably smooth, the function $t\mapsto \mathbb{ P}\{ \zeta>t\}$ is twice continuously differentiable, and the condition $0<-\frac{ d\log\mathbb{ P}\{ \zeta>t\}}{ dt}<\lambda$ holds for the hazard rate of $\zeta$, then there exists a unique continuously differentiable function $b$ solving the smoothed problem. We show how this result leads to flexible models of default for which it is possible to compute expected values of contingent claims.
Categories: q-fin.RM math.PR