I am trying to show the following: $X_n \Rightarrow X$ and $Y_n \Rightarrow c$, c a constant, implies $X_nY_n \Rightarrow Xc$.
Using the fact that $X_n \Rightarrow X$ and $Y_n \Rightarrow c$, c a constant, implies $X_n + Y_n \Rightarrow X+ c$ (which I know how to prove) I found in another post (Proving Slutsky's theorem) a way to prove what I want to prove :
"We have $$X_nY_n=X_n(Y_n-c)+cX_n;$$ defining $Z_n:=cX_n$ and $Z'_n:=X_n(Y_n-c)$, we reach the wanted conclusion provided that we manage to show that $X_n(Y_n-c)\to 0$ in probability. But for a fixed $\varepsilon$, and each $R$ $$\mathbb P\{| X_n(Y_n-c)|\gt \varepsilon\}\leqslant\mathbb P\{|X_n|\gt R\}+\mathbb P\{|Y_n-c|\gt \varepsilon/R \}.$$ Choosing $R$ as a limiting point of the distribution function of $|X|$, we obtain from the convergence of $Y_n$ to $c$ in probability that $$\limsup_{n\to +\infty} \mathbb P\left\{| X_n(Y_n-c)|\gt \varepsilon\right\}\leqslant \mathbb P\{|X|\gt R\}.$$ Since $R$ can be chosen arbitrarily large, we are done. "
I agree with the proof except the last step, to conclude that $P\{|X|\gt R\}$ goes to zero when R is arbitrary large we need the hypothesis that X is finite almost surely but I have no such hypothesis. Is there a way to modify the proof to work without any such hypothesis on X ?
P.S: I want to prove my statement without using the fact that $(X_n,Y_n) \Rightarrow (X,c)$.