Let $X_1$ and $X_2$ be two normal random variables. Write $X_1\sim N(\mu_1, \sigma^2_1)$ and $X_2\sim N(\mu_2, \sigma^2_2)$, to fix ideas.
Consider the corresponding log-normal random variables: $Z_1 = \exp(X_1)$, $Z_2 = \exp(X_2)$.
Question: what is the distribution of the product of the two random variables, i.e., the distribution of $Z_1Z_2$?
If the normal random variables $X_1, X_2$ are independent, the answer is simple: we have $Z_1Z_2 = \exp(X_1+X_2)$ with the sum $X_1+X_2$ normal, hence the product $Z_1Z_2$ is still lognormal.
But suppose that $X_1, X_2$ are generally $not$ independent, say with correlation $\rho$. What can we say about the distribution of $Z_1Z_2$?
Best Answer
Even though this is an old post, I want to point out that one needs to be careful by saying "If $X_1$ is normal and $X_2$ is normal, then $X_1+X_2$ is normal, whatever the correlation $\rho$ between $X_1$ and $X_2$"
This statement is definitely wrong! The sum of two normals is normal if the dependency structure is normal (mathematically: if the copula is gaussian). However, if the dependence structure is not gaussian but has heavy tails (e.g. a Student-t copula) between $X_1$ and $X_2$, then $X_1+X_2$ will definitely not be normal distributed.
To come back to the question raised, the product of two lognormals will be lognormal if $(X_1,X_2)$ is a bivariate normal. Otherwise, this will not be the case!