Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi
Time series modelling is an effective study that has engaged consideration of researcher society in excess of the past few periods. The purpose of the time series modelling is to wisely compile and precisely study the previous information of a time series to create an applicable model that defines t...
| Main Authors: | , , |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2019
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/32352/1/32352-Comparative%20Perfomance%20of%20arima.pdf |
| _version_ | 1796903425650196480 |
|---|---|
| author | Bakar, Hasma Basyirah Nik Rusdi, Nik Sofiah Rushdi, Nurul Athirah |
| author_facet | Bakar, Hasma Basyirah Nik Rusdi, Nik Sofiah Rushdi, Nurul Athirah |
| author_sort | Bakar, Hasma Basyirah |
| collection | UITM |
| description | Time series modelling is an effective study that has engaged consideration of researcher society in excess of the past few periods. The purpose of the time series modelling is to wisely compile and precisely study the previous information of a time series to create an applicable model that defines the necessary arrangement of the series and to generate forecast values for the series. It is well acknowledged that a time series are regularly affected with outliers. Outliers may impact the forecasting where the tendency in parameter estimates created by extreme observation will reduce its effectiveness because the optimum predictor for an Autoregressive Integrated Moving Average (ARIMA) model is determined by its parameters. This study used ARIMA and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) to compare the best model for forecasting Kuala Lumpur Composite Index (KLCI) when the outlier exists. The best models of ARIMA and GARCH were evaluated using Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). It can be concluded that GARCH model performed better compared to Box-Jenkins ARIMA in forecasting KLCI |
| first_indexed | 2024-03-06T02:19:54Z |
| format | Thesis |
| id | oai:ir.uitm.edu.my:32352 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:19:54Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | oai:ir.uitm.edu.my:323522020-07-16T07:33:08Z https://ir.uitm.edu.my/id/eprint/32352/ Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi Bakar, Hasma Basyirah Nik Rusdi, Nik Sofiah Rushdi, Nurul Athirah Study and teaching. Research Time series modelling is an effective study that has engaged consideration of researcher society in excess of the past few periods. The purpose of the time series modelling is to wisely compile and precisely study the previous information of a time series to create an applicable model that defines the necessary arrangement of the series and to generate forecast values for the series. It is well acknowledged that a time series are regularly affected with outliers. Outliers may impact the forecasting where the tendency in parameter estimates created by extreme observation will reduce its effectiveness because the optimum predictor for an Autoregressive Integrated Moving Average (ARIMA) model is determined by its parameters. This study used ARIMA and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) to compare the best model for forecasting Kuala Lumpur Composite Index (KLCI) when the outlier exists. The best models of ARIMA and GARCH were evaluated using Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). It can be concluded that GARCH model performed better compared to Box-Jenkins ARIMA in forecasting KLCI 2019-12 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/32352/1/32352-Comparative%20Perfomance%20of%20arima.pdf Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi. (2019) Degree thesis, thesis, Universiti Teknologi MARA Cawangan Kelantan. |
| spellingShingle | Study and teaching. Research Bakar, Hasma Basyirah Nik Rusdi, Nik Sofiah Rushdi, Nurul Athirah Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title | Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title_full | Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title_fullStr | Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title_full_unstemmed | Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title_short | Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi |
| title_sort | comparative performance of arima and garch models in modelling and forecasting volatility of kuala lumpur composite index hasma basyirah bakar nik sofiah nik rusdi and nurul athirah rushdi |
| topic | Study and teaching. Research |
| url | https://ir.uitm.edu.my/id/eprint/32352/1/32352-Comparative%20Perfomance%20of%20arima.pdf |
| work_keys_str_mv | AT bakarhasmabasyirah comparativeperformanceofarimaandgarchmodelsinmodellingandforecastingvolatilityofkualalumpurcompositeindexhasmabasyirahbakarniksofiahnikrusdiandnurulathirahrushdi AT nikrusdiniksofiah comparativeperformanceofarimaandgarchmodelsinmodellingandforecastingvolatilityofkualalumpurcompositeindexhasmabasyirahbakarniksofiahnikrusdiandnurulathirahrushdi AT rushdinurulathirah comparativeperformanceofarimaandgarchmodelsinmodellingandforecastingvolatilityofkualalumpurcompositeindexhasmabasyirahbakarniksofiahnikrusdiandnurulathirahrushdi |