For a BSDE:
$$y_t = \xi + \int_{t}^{T}g_0(s)ds - \int_{t}^{T}z_sdB_s$$
Which has a fixed $\xi \in L^2(\mathscr{F}_T)$ and $g_0(\cdot)$ satisfying $E(\int_{0}^{T}|g_0(t)|dt)^2 < \infty$. There exists a unique pair of process $(y., z.)\in L_{\mathscr{F}}^2(0,T;R^{1+d})$ satisfies the BSDE shown before.
In addition, if $g_0(\cdot)\in L_{\mathscr{F}}^2(0,T)$, then $(y., z.)\in S_{\mathscr{F}}^2(0,T) \times L_{\mathscr{F}}^2(0,T;R^d)$.
Here comes the question: Why $y.\in S_{\mathscr{F}}^2(0,T)$?
We know that:
$L_{\mathscr{F}}^2(0,\tau;R^m)$={$R^m$-valued and $\mathscr{F}_t$-adapted and stochastic processes such that $E[\int_0 ^\tau|\phi_t|^2dt]<\infty$}
$D_{\mathscr{F}}^2(0,\tau;R^m)$={all RCLL(right continuous with left limit) processes in $L_{\mathscr{F}}^2(0,\tau;R^m)$ such that $E[\sup_{0 \leq t \leq \tau}|\phi_t|^2]< \infty$}
$S_{\mathscr{F}}^2(0,\tau;R^m)$ = {all continuous processes in $D_{\mathscr{F}}^2(0,\tau;R^m)$}
Therefore, in order to prove the question, we need to show that $E[\sup_{0\leq t \leq T}|y_t|^2] < \infty$.
The paper suggests to use B-D-G inequality to prove that, so I go to look for it and find something different with the question.
The B-D-G inequality is that: for $g\in L^2(R)$:
$$E[\sup_{0\leq t \leq T}|\int _0 ^t g(s)dB_s|^2]\leq 4E[\int _0 ^T |g(s)|^2 ds]$$
So, how to use B-D-G inequality to prove the question? Do I need to use Jensen’s inequality to transform it first?