“…Econometric models have been widely applied for this task; however, they have also been heavily criticized as the majority are linear and work under assumptions that restrict them. Thus, the use of artificial intelligence techniques has spread, such as Artificial Neural Networks (ANN), which are able to model the non‐linear behavior of time series through their learning, adaptability, and training properties, without needing to know the data structure in advance, favoring models focused on forecasting ((Chen & Leung, ); (Davis, Episcopos, & Wettimuny, ); (Kodogiannis & Lolis, ); (Yao & Tan, )).Despite the discrepancies between different studies on exchange rate linearity, the literature shows a greater interest in non‐linear models to analyze the behavior of this time series ((Clements & Lan, ); (Yu, Wang, & Lai, ); (Leung, Chen, & Daouk, )). The goal of this study is to verify that there is an improvement in the forecasts of exchange rate returns when using embedded models as opposed to using only econometric or artificial intelligence models, all in a rolling windows frame.…”