Previsão de Faturamento de Shopping: um estudo de caso no setor de varejo

Abstract

In this research, the central objective is to develop a revenue forecasting model for a shopping center located in Juiz de Fora. To achieve this goal, time series analysis techniques are applied to provide projections that will serve as the basis for the company's financial planning. The study is based on a comprehensive investigation of financial planning, the company in question, and the context of shopping centers in Brazil. The analysis period spans five years, from January 2017 to December 2022, and the Holt-Winters model, selected after a thorough evaluation of methods, is used to generate highly explanatory forecasts. The results emphasize the value of using mathematical and statistical methods in creating revenue forecasting scenarios, highlighting the relevance of revenue projections in shaping the shopping center's financial planning. This research aims to contribute to knowledge by identifying how advanced techniques, such as data analysis with time series models, can enhance the accuracy of forecasts. Furthermore, by analyzing seasonality and specific events in the retail sector, it seeks to provide practical insights for shopping center managers, enabling them to make informed decisions and improve financial performance. Ultimately, this research has the potential to make a significant contribution to academic literature and the retail sector, promoting more informed and effective approaches to enhance financial results, benefiting not only shopping centers but also the overall economy.