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General-to-Specific (GETS) modelling has witnessed major advances thanks to the automation of multi-path GETS specification search. However, the estimation complexity associated with financial models constitutes an obstacle to automated multi-path GETS modelling in finance. Making use of a recent result we provide and study simple but general and flexible methods that automate financial multi-path GETS modelling. Starting from a general model where the mean specification can contain autoregressive terms and explanatory variables, and where the exponential volatility specification can include log-ARCH terms, asymmetry terms, volatility proxies and other explanatory variables, the algorithm we propose returns parsimonious mean and volatility specifications.