I was reviewing time series textbooks recently and have been left confused since.
In particular I have looked into the book of Brockwell and Davis (Introduction to Time Series and Forecasting, Second Edition).
In section 2.3 it is said (just after eq 2.3.4) that there is a unique stationary solution to the ARMA(1,1) equation, if the coefficient on the AR part is not 1 in modulus. To quote the text, they look at the equation
$$ X_t − \phi X_{t−1} = Z_t + \theta Z_{t−1}$$ where $\{Z_t\}\sim\text{WN}(0,\sigma^2)$ and $\phi+\theta\neq0$.
And for $\left| \phi \right| > 1$ they get the representation
$$ X_t = -\theta\phi^{-1}Z_t - (\theta+\phi)\sum_{j=1}^\infty\phi^{-j-1}Z_{t+j}.$$
The proof seems OK to me. But I immediately had the question: How does this relate to explosive processes? I read that a coefficient larger than 1 (in modulus) means that a process is explosive.
In particular the accepted answer of Non-Stationary: Larger-than-unit root performed a simulation that shows the explosive behaviour.
I have the suspicion that this conclusion only holds if we look at adapted processes, as the solution from the textbook looks into the future (it is non-causal). Straight-forward simulations will be adapted since they only incorporate one random variable in each step.
Is my explanation correct, and if not, what am I missing?