|
Forecasting MSCI World Energy Sector Index with the SARIMA Model |
|---|---|
| รหัสดีโอไอ | |
| Creator | Wissanudeth Nunchaikaew |
| Title | Forecasting MSCI World Energy Sector Index with the SARIMA Model |
| Publisher | Business Administration Kasetsart University |
| Publication Year | 2566 |
| Journal Title | Kasetsart Applied Business Journal |
| Journal Vol. | 17 |
| Journal No. | 26 |
| Page no. | 37-53 |
| Keyword | Energy, Forecasting, Index, Model, Seasonal |
| URL Website | https://so04.tci-thaijo.org/index.php/KAB/about |
| Website title | http://journal.bus.ku.ac.th/ |
| ISSN | 25396250 ONLINE |
| Abstract | Energy plays a crucial role in economic systems in terms of consumption and production.At the present, there is a high fluctuation of energy prices due to the business cycle movementand the differences in business energy consumption demanding in each cycle; therefore,the energy index prediction could help investor plans appropriately. The model used in thisstudy is Seasonal Autoregressive Integrated Moving Average model (SARIMA). This is a modelincreasing seasonal effects which was developed from ARIMA (p, d, q) of Box and Jenkins.The purposes of this study are 1) to construct a suitable model for MSCI World Energy Indexby using SARIMA (Seasonal Autoregressive Integrated Moving Average), and 2) to compareForecast Accuracy of MSCI World Energy Sector Index via SARIMA Model. The data in thisstudy is a monthly information from the MSCI World Energy Index from 2005 to 2019 (15 years).In the research methodology, there is a data stationary tested by using the unit root test, andsimulating SARIMA model. After selecting the most appropriate model, the data predictiontest was operated. In conclusion, the result of this study revealed that the most appropriatemodel for prediction was SARIMA (2,1,1)ื(2,1,3)12. The prediction model outcome was very closeto the real indices, when the deviation of RMSE was 16.68 and MAE was 12.39 respectively |
