The table above draws comparisons between field theory and other techniques used for time series. ‘A

FMI vs Other Techniques

The table above draws comparisons between field theory and other techniques used for time series. ‘ARMA ‘ denotes classical methods including GARCH, ARIM, SARIMA and generalisations. ‘ML’ denotes all techniques involving neural networks, clustering, PCA, etc. FMI stands for ‘Field Machine Intelligence ‘, an acronym describing all field theory based algorithms. While it can break linearity, ML has various inbuilt assumptions such as stationarity, IID, regime dependence. It is a black box and overfits. While classical methods can break stationarity and IID, they are by definition linear. FMI has none of these problems or assumptions. Indeed it can be shown that FMI reduces to autoregressive methods and neural networks and chaos theoretic methods in different limits. 

Why FMI does not overfit

ai vs FMI

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