Here we study $$M_{t}=B_{A_{t}}\stackrel{d}{=}\int_{0}^{t}\sqrt{1+e^{W_{s}}}dW_{s}.$$ First, as mentioned [Martingale Convergence][1] here >Theorem 4 Let X be a continuous martingale. Then, almost surely, one of the following is satisfied >- $X_\infty=\lim_{t\rightarrow\infty}X_t$ exists and is finite. >- $\limsup_{t\rightarrow\infty}X_t=\infty$ and $\liminf_{t\rightarrow\infty}X_t=-\infty$. In this case, the process hits every value in $\mathbb R$ at arbitrarily large times. By Itô isometry we have $$E[M^{2}_{t}]=\int^t 1+Ee^{W_{s}}ds=\int^t 1+e^{\frac{s}{2}}ds \to +\infty,$$ which also shows that $<M>_{\infty}=\infty$. In general for continuous martingales we have that "$X_\infty=\lim_{t\rightarrow\infty}X_t$ exists and is finite" iff $<X>_{\infty}<\infty.$ The left-right direction that is relevant here is as follows: we use the stopping time $\tau_{n}:=\inf\{t\geq 0: |X_{t}|\geq n\}$ and the bound $$E[<X>_{t\wedge \tau_{n}}]=E[X^{2}_{t\wedge \tau_{n}}]\leq n^{2}$$ to get that the event $\{\sup|X_t|<\infty\}=\bigcup_{n}\{\sup|X_t|<n\}$ implies that the finiteness $<X>_{\infty}<\infty$. (For the other direction we can use instead $\tau_{n}:=\inf\{t\geq 0: <X>_{t}\geq n\}$.) So we can't have the first case in the above theorem, because it would give a contradiction and so we have the second case. For the "in probability" part, we will use a reverse tail inequality: when $\mathbb {E} [X]=0,\,\mathbb {E} [X^{2}]=1$ then $$\Pr(X\geq 0)\geq {\frac {2{\sqrt {3}}-3}{\mathbb {E} [X^{4}]}},$$ from [Berger's "The Fourth Moment Method][2]. By symmetry of Brownian motion we write $$P[M_{t}\leq 0]=P[0\leq \tilde{M}_{t}:=\int_{0}^{t}\sqrt{1+e^{-W_{s}}}dW_{s}].$$ We still have $E[\tilde{M}_{t}]=0$ and we will need the fourth moment bound $$E\left(\int f dW\right)^{4}\leq c_{2}\left(\int Ef^{2} ds\right)^{2},$$ from Corollary 4 in ["Notes on the Itô Calculus" by Steven P. Lalley][3]. Therefore, for $X_{t}:=\tilde{M}_{t}\frac{1}{\sqrt{E[\tilde{M}_{t}^{2}]}}$ and using the above bound we get $$P[\tilde{M}_{t}\geq 0]\geq {\frac {2{\sqrt {3}}-3}{\mathbb {E} [X^{4}]}}\geq \frac {2{\sqrt {3}}-3}{c_{2}}>0$$ for all $t>0$. [1]: https://almostsuremath.com/2009/12/20/martingale-convergence/ [2]: https://en.wikipedia.org/wiki/Cantelli%27s_inequality [3]: http://galton.uchicago.edu/~lalley/Courses/385/ItoIntegral.pdf