I'm reading some materials about "stable convergence" and have been stuck with proof for the following proposition.
Let $(\Omega, \mathscr{F}, \mathbb{P})$ be a probability space, on which a sequence of random variables $\{X_n\}$ is defined. Let $(\Omega_1, \mathscr{F}_1, \mathbb{P}_1)$ be another probability space, and define the "extended probability space" $(\tilde{\Omega}, \tilde{\mathscr{F}}, \tilde{\mathbb{P}})$ of $(\Omega, \mathscr{F}, \mathbb{P})$ by setting $(\tilde{\Omega}, \tilde{\mathscr{F}}, \tilde{\mathbb{P}}) = (\Omega, \mathscr{F}, \mathbb{P}) \times (\Omega_1, \mathscr{F}_1, \mathbb{P}_1)$. Let $X$ be a random variable defined on $(\tilde{\Omega}, \tilde{\mathscr{F}}, \tilde{\mathbb{P}})$. Now suppose given any $k \geq 1$, for all Borel set $A \in \mathscr{B}(\mathbb{R})$ and $B \in \sigma(X_1, X_2, \cdots, X_k)$, it holds $$ \mathbb{P}((X_n \in A) \cap B) \longrightarrow \tilde{\mathbb{P}}(X \in A) \mathbb{P}(B) $$ Assertion: we have that for all Borel set $A \in \mathscr{B}(\mathbb{R})$ and $B \in \sigma(X_k, k \geq 1)$, $$ \mathbb{P}((X_n \in A) \cap B) \longrightarrow \tilde{\mathbb{P}}(X \in A) \mathbb{P}(B) $$
I attempted by dint of monotone class theorem: set $$\mathscr{H}=\{B \in \sigma(X_k, k \geq 1): \mathbb{P}((X_n \in A) \cap B) \longrightarrow \tilde{\mathbb{P}}(X \in A) \mathbb{P}(B) \} $$ and try to prove it's a $\sigma$-algebra, but didn't manage to achieve that. Actually I doubt that this proposition is not true... Any hint will be greatly appreciated!