I am currently modelling financial time series via ARMA processes, but I have reason to believe that in addition to significant autocorrelation, the time series also exhibit skewness. Is there a way to estimate them jointly?
I am aware of Simulation of Non-normal Autocorrelated Variables, but it only talks about how to combine AR and MA models to achieve a desired skew and kurtosis. There is also this paper Looking for skewness in financial time series analyzing time series to show that they exhibit time-varying conditional skewness instead of unconditional skewness.
There is also this paper Time series models based on the unrestricted skew-normal process, which models skew innovations.
Does a general approach for modelling skewness with ARMA models exist that I am overlooking here? Do heuristics exist?