Let $B=(B_t)_{t \g 0}$ be standard Brownian motion started at 0 under P, let $S_t=\max_{ 0 \l r \l t} B_r$ be the maximum process associated with B, and let $g: {\bf R}_+ \rightarrow {\bf R}$ be a (strictly) monotone continuous function satisfying $g(s) 0 \vert B_t \l g(S_t) \big \}. $$ Let G be the function defined by $$ G(y) = \exp \bigg(-\int_0^{g^{-1}(y)} {{ds} \over {s-g(s)}} \bigg) $$ for $y \in \bf R$ in the range of g. Then, if g is increasing, we have $$ \lim_{t \rightarrow \infty} \sqrt{t} \bP\{\tau \g t \} = \sqrt{2 \over \pi } \Bigg(-g(0) -\int_{g(0)}^{g(\infty)} G(y)\,dy \Bigg) $$ and this number is finite. Similarly, if g is decreasing, we have $$ \lim_{t \rightarrow \infty} \sqrt{t} \bP\{\tau \g t \} = \sqrt{2 \over \pi } \Bigg(-g(0) + \int_{g(\infty)}^{g(0)} G(y) \,dy \Bigg) $$ and this number may be infinite. These results may be viewed as a {\it stochastic boundary} ext...
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