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Time series analysis applied to Klabin's quarterly profits

Authors

Keywords:

Outliers, structural break, periodic, frequency

Abstract

Klabin S.A. is a century-old company, a market leader, and also the largest producer and exporter of packaging paper in the country. The difference between revenues and costs/expenses translates into the company’s net profit, the main point of interest for investors, as the stock market share prices are directly influenced by the company’s profit. In this regard, the goal of this study is to analyze the historical series of Klabin’s quarterly profits, examine their temporal patterns, and fit a model to predict future values. The ARMA(1, 1) model, including two indicator variables and a pair of harmonic components, was used to model the effect of an additive outlier, structural break, and periodicity, respectively. The errors generated by the model can be considered normal and exhibit characteristics of white noise. The model’s forecast for the first two quarters of the year 2023 resulted in an approximately 7% Mean Absolute Percentage Error (MAPE).

Author Biographies

Eduardo Campana Barbosa , Federal University of Viçosa (UFV)

Professor at the Statistics Department

Sara Silvério , Federal University of Viçosa (UFV)

Master's student in the Applied Statistics and Biometrics Program

Paulo César Emiliano, Federal University of Viçosa (UFV)

Professor at the Statistics Department

Maurício Silva Lacerda , Federal Institute of Education, Science and Technology of Rondônia (DAPE/IFRO)

Teacher at the Teaching Support Department

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Published

15-03-2024

Versions

How to Cite

Barbosa , E. C., Silvério , S., Emiliano, P. C., & Lacerda , M. S. (2024). Time series analysis applied to Klabin’s quarterly profits. Sigmae, 13(1), 101–109. Retrieved from https://publicacoes.unifal-mg.edu.br/revistas/index.php/sigmae/article/view/2272