Commodity predictability analysis with a permutation information theory approach

► Commodity predictability is quantified by using permutation information theory tools. ► Linear and nonlinear correlations are taken into account by this novel approach. ► More general applicability than other widely used approaches like the Hurst exponent. ► Very useful information about the underlying dynamics can be obtained. ► The methodology is very fast, flexible and robust in a noisy environment.