Resumen

AJA KINDELAN, Alfonso; MATA MATA, Leovardo  y  BELTRAN GODOY, Jaime Humberto. Análisis y proyección de los rendimientos accionarios de Pfizer, en el período 2018-2020, mediante redes neuronales diferenciales. The Anáhuac j. [online]. 2019, vol.19, n.1, pp.13-34.  Epub 17-Ene-2022. ISSN 2683-2690.  https://doi.org/10.36105/theanahuacjour.2019v19n1.01.

In this paper, a differential neural network (DNN) is used to project Pfizer’s stock returns in the 2018-2020 period. The model uses quarterly data, at the end of the period, the price of the company’s stock (P), net sales (NS), total assets (TA) and accounts receivable (AR). The results are compared with the classic regression models and there is evidence of the superior goodness of fit of the DNN, compared to conventional methods, since the error in out sample forecast is less than 5 %.

Palabras llave : neural networks; forecast; stock returns; C45; C51.

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