Let $Y$ be an infinitely divisible random variable. Suppose that $Y \sim (0, \nu,0)_0$ according to the notation on Page 39, Equation (8.7), from <cite authors="Sato, Ken-Iti">_Sato, Ken-Iti_, Lévy processes and infinitely divisible distributions, [ZBL0973.60001](https://zbmath.org/?q=an:0973.60001).</cite> That is, the Lévy-Khintchine representation of the characteristic function is given by: \begin{equation}\label{I}\tag{I} \varphi_Y(z) = \exp\left\{ \int_\mathbb R [e^{izx} - 1] d\nu(x) \right\} \end{equation} Note that if $\nu(\mathbb R)< \infty$, we can set $\lambda:= \nu(\mathbb R)$ and writte: $$ \varphi_Y(z) = \exp\left\{\lambda \int_\mathbb R [e^{izx} - 1] d\eta(x) \right\}, \quad d\eta(x):= d\nu(x)/\lambda$$ In this case, we have that $Y$ is a Compound Poisson random variable $Y \sim CP(\lambda, \eta)$( See page 18, Equation (4.1) from the Sato's book (reference above)). However, in general, we don't have $\nu(\mathbb R)< \infty$. For example, see [ this question][1] and this [other question][2], where we have infinite mass around zero. By the other hand, we know thar every random variable $Y$ is infinitely divisible if and only if there is a sequence $(X_n)_{n \in \mathbb N}$ of Compound Poisson random variables such that, in weak limits: \begin{equation}X_n \Longrightarrow Y, \quad (n\to \infty) \end{equation} C.f. Theorem 16.5, page 333, from <cite authors="Klenke, Achim">_Klenke, Achim_, [**Probability theory. A comprehensive course**](http://dx.doi.org/10.1007/978-1-4471-5361-0). [ZBL1295.60001](https://zbmath.org/?q=an:1295.60001).</cite> *So my question is*: suppose I have a sequence $(X_n)_{n \in \mathbb N}$ of Compound Poisson random variables with $X_n \sim CP(1, \eta_n)$ such that \begin{equation}\label{II}\tag{II} X_n \Longrightarrow Y, \quad (n\to \infty) \end{equation} where $Y$ has characterization given by (\ref{I}). **in what situations ( assumptions about $\eta_n$ ) the convergence given in (\ref{II}) implies that $Y$, with characterization given by (\ref{I}), is in fact a Compoun Poisson random variable?** Or in other suficient way, when we have $\nu(\mathbb R)< \infty$?. One trivial case is when $(X_n)$ has the same distribution. I.e. $\eta_n = \eta$ for all $n$. So we exclude this case. My intuition tells me that it is not possible, given (\ref{II}), to have $\nu(\mathbb R)< \infty$. Help [1]: https://math.stackexchange.com/questions/4561024/example-of-a-levy-measure-with-infinite-mass-around-zero [2]: https://math.stackexchange.com/questions/4561609/example-of-a-levy-measure-with-infinite-mass-around-zero-but-with-finite-second