Autoregressive models are commonly found in the context of hydrological series, specifically in streamflow and/or ANE series (Affluent Natural Energy). Most of them are models of order 1, which have constant or periodic parameters and need the requirement of normality. According to the literature, annual streamflow series can be approximated for normal distributions, however, in short periods of time, like daily, weekly and monthly, this feature is not observed, especially because of the asymmetry issue. Due to this reason, a new class of model of order 1 was studied for attempting to solve such problem. The new model keeps autoregressive structure and can be additive, multiplicative or hybrid, in which embodies additive and multiplicative properties together, but its marginals will assume gamma distribution. Moreover, this modeling departs from the presupposition that Methods of Moments are efficient to the estimation of its parameters. Recently, this approach, under the hybrid way, has not proved to be successful to the context of Brazilian hydrothermal dispatch. This work focuses on the complete analysis of hybrid model to the series of the Brazilian Electric Sector, bringing, as novelty, Maximum Likelihood Estimation, besides isolated studies of additive and multiplicative models. The results revealed a prosperous line of research, opening a field of possibilities for new orders or asymmetric distributions to be studied starting from this point.