Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model
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,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/13/2181 |
| _version_ | 1797434077621518336 |
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| author | Lihki Rubio Keyla Alba |
| author_facet | Lihki Rubio Keyla Alba |
| author_sort | Lihki Rubio |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-03-09T10:27:07Z |
| format | Article |
| id | doaj.art-528419adcd354014a3d0b6889410ed76 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T10:27:07Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-528419adcd354014a3d0b6889410ed762023-12-01T21:34:59ZengMDPI AGMathematics2227-73902022-06-011013218110.3390/math10132181Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR ModelLihki Rubio0Keyla Alba1Department of Mathematics and Statistics, Universidad del Norte, Barranquilla 080001, ColombiaDepartment of Mathematics and Statistics, Universidad del Norte, Barranquilla 080001, ColombiaForecasting 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).https://www.mdpi.com/2227-7390/10/13/2181hybrid modelARIMAsupport vector regression (SVR)forecastingtime series analysisdaily returns |
| spellingShingle | Lihki Rubio Keyla Alba Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model Mathematics hybrid model ARIMA support vector regression (SVR) forecasting time series analysis daily returns |
| title | Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model |
| title_full | Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model |
| title_fullStr | Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model |
| title_full_unstemmed | Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model |
| title_short | Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model |
| title_sort | forecasting selected colombian shares using a hybrid arima svr model |
| topic | hybrid model ARIMA support vector regression (SVR) forecasting time series analysis daily returns |
| url | https://www.mdpi.com/2227-7390/10/13/2181 |
| work_keys_str_mv | AT lihkirubio forecastingselectedcolombiansharesusingahybridarimasvrmodel AT keylaalba forecastingselectedcolombiansharesusingahybridarimasvrmodel |