So suppose you have two sequences $\{Y_t\}$ and $\{Z_t\}$ and they are both iid and independent from each other. Now suppose I have a time series $\{X_t\}$ such that...
$$\{X_t\} = Y_t(1-Y_{t-1})Z_t$$
What would be the variance of this time series?
If my understanding of this is correct the process would go.
\begin{align} \newcommand{\Var}{{\rm Var}} \Var(Y_t(1-Y_{t-1})Z_t) &= \Var(Z_tY_t-Z_tY_tY_{t-1}) \\ &= \Var(Z_tY_t) + \Var(Z_tY_tY_{t-1}) \end{align}
...
My question mainly focusing around how to deal with the expanded version $\Var(Z_tY_t-Z_tY_tY_{t-1})$ as well as what to do afterwards. I know that $\Var(X-Y) = \Var(X) + \Var(Y)$ when $X$ and $Y$ are independent however I don't know if that carries when $X$ and/or $Y$ are products of iid random variables. As well how to decompose the variance of three sequences.