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Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model

Department of Mathematics and Statistics, Universidad del Norte, Barranquilla 080001, Colombia
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Academic Editor: Tatiana Filatova
Mathematics 2022, 10(13), 2181; https://doi.org/10.3390/math10132181
Received: 13 April 2022 / Revised: 23 May 2022 / Accepted: 7 June 2022 / Published: 23 June 2022
Forecasting future values of Colombian companies traded on the New York Stock Exchange is a daily challenge for investors, due to these stocks’ high volatility. There are several forecasting models for forecasting time series data, such as the autoregressive integrated moving average (ARIMA) model, which has been considered the most-used regression model in time series prediction for the last four decades, although the ARIMA model cannot estimate non-linear regression behavior caused by high volatility in the time series. In addition, the support vector regression (SVR) model is a pioneering machine learning approach for solving nonlinear regression estimation procedures. For this reason, this paper proposes using a hybrid model benefiting from ARIMA and support vector regression (SVR) models to forecast daily and cumulative returns of selected Colombian companies. For testing purposes, close prices of Bancolombia, Ecopetrol, Tecnoglass, and Grupo Aval were used; these are relevant Colombian organizations quoted on the New York Stock Exchange (NYSE). View Full-Text
Keywords: hybrid model; ARIMA; support vector regression (SVR); forecasting; time series analysis; daily returns; cumulative returns hybrid model; ARIMA; support vector regression (SVR); forecasting; time series analysis; daily returns; cumulative returns
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MDPI and ACS Style

Rubio, L.; Alba, K. Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model. Mathematics 2022, 10, 2181. https://doi.org/10.3390/math10132181

AMA Style

Rubio L, Alba K. Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model. Mathematics. 2022; 10(13):2181. https://doi.org/10.3390/math10132181

Chicago/Turabian Style

Rubio, Lihki, and Keyla Alba. 2022. "Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model" Mathematics 10, no. 13: 2181. https://doi.org/10.3390/math10132181

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