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The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices.