 Multivariate Circulant Singular Spectrum Analysis (M-CiSSA) is a non-parametric automated technique that allows to extract signals of time series at any frequency specified beforehand . It is useful to uncover co-movements at different frequencies and understand their commonalities and specificities  . We apply M-CiSSA to understand the main drivers and co-movements of energy commodity prices at trend and cyclical frequencies that are key to assess energy policy at different time horizons. We clearly distinguish the detached behaviour of US natural gas from the rest of energy commodities at both frequencies while coals and Japan natural gas only decouple at the cyclical frequency.
We introduce Multivariate Circulant Singular Spectrum Analysis (M-CiSSA) , a non-parametric automated technique to extract signals at different frequencies . It is useful to uncover co-movements per frequency, understand their commonalities and specificities , and also the relative cyclical position of the signals . We apply M-CiSSA to understand the main drivers and co-movements of energy commodity prices at trend and cyclical frequencies that are key to assess energy policy at different time horizons. We distinguish the detached behaviour of US natural gas from other energy commodities at both frequencies , while coal and Japan's natural gas only decouple at the cyclical frequency.
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