Embedding laws in diffusions by functions of time
We present a constructive probabilistic proof of the fact that if $B=(B_t)_{t\ge0}$ is standard Brownian motion started at $0$, and $μ$ is a given probability measure on $\mathbb{R}$ such that $μ(\{0\})=0$, then there exists a unique left-continuous increasing function $b:(0,\infty)\rightarrow\mathbb{R}\cup\{+\infty\}$ and a unique left-continuous decreasing function $c:(0,\infty)\rightarrow\mathbb{R}\cup\{-\infty\}$ such that $B$ stopped at $τ_{b,c}=\inf\{t>0\vert B_t\ge b(t)$ or $B_t\le c(t)\}$ has the law $μ$. The method of proof relies upon weak convergence arguments arising from Helly's selection theorem and makes use of the Lévy metric which appears to be novel in the context of embedding theorems. We show that $τ_{b,c}$ is minimal in the sense of Monroe so that the stopped process $B^{τ_{b,c}}=(B_{t\wedgeτ_{b,c}})_{t\ge0}$ satisfies natural uniform integrability conditions expressed in terms of $μ$. We also show that $τ_{b,c}$ has the smallest truncated expectation among all stopping times that embed $μ$ into $B$. The main results extend from standard Brownian motion to all recurrent diffusion processes on the real line.