Year: 2025
Type: article
Abstract: This paper, a model for predicting the sales of Walmart is demonstrated with the VARMAX technique (Vector Autoregression with Exogenous Factors). By incorporating sales data along with variables like holidays as well as economic indicators such as temperature fluctuations, fuel costs, CPI (Consumer Price Index) and unemployment rates, the Walmart’s weekly sales figures can be precisely forecasted by this model. Impressively, the performance metrics of thi model achieved an RMSE of 18, 961 and a MAPE of 4%, outperforming forecasting models such as ARIMA. Considering these influences, the model successfully recognized seasonal sales growth and considered economic changes that may affect consumer habit.
Authors: Owen Chau, Junfeng Liu
Institutions: Northeastern University, Sun Yat-sen University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4409618953