We use information from higher order moments to achieve identification of non-Gaussian structural vector autoregressive moving average (SVARMA) models, possibly nonfundamental or noncausal, through a frequency domain criterion based on spectral densities. This allows us identify the location roots determinantal lag matrix polynomials and rotation model errors leading shocks up sign permutation....