Predicción de precios de acciones de empresas que cotizan en la Bolsa de Valores de Guayaquil usando series de tiempo Multivariantes

Abstract

In this article the company’s stock prices are listed in the Guayaquil Stock Exchange using Multivariate Time Series. The models were compared with eight companies’ data which had movements all the months in the period from January 2008 to December 2018. The multivariate time series models were compared with univariate time series models. The fitting and forecasting of the data were done with package functions of the statistical software R. The evaluation of the forecast performance was made with the mean square error (MSE), the mean absolute percentage error (MAPE) and the root mean square error (RMSE). The results of the experiments showed that in 62.5% of the cases the multivariate time series had better forecasting capacity than the univariate time series.