EBITDA Index Prediction Using Exponential Smoothing and ARIMA Model

Lihki Rubio, Alejandro J. Gutiérrez-Rodríguez and Manuel G. Forero
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Lihki Rubio: Department of Mathematics and Statistics, Universidad del Norte, Barranquilla 080001, Colombia
Alejandro J. Gutiérrez-Rodríguez: Faculty of Economic Sciences and Management, Universidad de Ibagué, Ibagué 730002, Colombia
Manuel G. Forero: Semillero Lún, Faculty of Engineering, Universidad de Ibagué, Ibagué 730002, Colombia

Mathematics, 2021, vol. 9, issue 20, 1-14

Abstract: Forecasting has become essential in different economic sectors for decision making in local and regional policies. Therefore, the aim of this paper is to use and compare performance of two linear models to predict future values of a measure of real profit for a group of companies in the fashion sector, as a financial strategy to determine the economic behavior of this industry. With forecasting purposes, Exponential Smoothing (ES) and autoregressive integrated moving averages (ARIMA) models were used for yearly data. ES and ARIMA models are widely used in statistical methods for time series forecasting. Accuracy metrics were used to select the model with best performance and ES parameters. For the real profit measure of the financial performance of the fashion sector in Colombia EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) was used and was calculated using multiple SQL queries.

Keywords: time series forecasting; exponential smoothing models; decision-making; ARIMA; EBITDA; fashion industry sector; economic forecasting; financial strategy; financial performance; economic models (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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