Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model
Modelling the overnight Islamic interbank rate (IIR) is imperative to define the IIR performance as it would help the Islamic banks to adjust its costs of funding effectively and facilitate the policy makers to regulate a comprehensive monetary policy in Malaysia. The IIR framework which has been re...
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| Format: | Article |
| Language: | English |
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Penerbit UMP
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/32912/ http://umpir.ump.edu.my/id/eprint/32912/1/Forecasting%20Malaysian%20overnight%20islamic%20interbank%20rate%20using%20the%20box.pdf |
| _version_ | 1848824138681024512 |
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| author | Radzi, N. S. M. Siti Roslindar, Yaziz |
| author_facet | Radzi, N. S. M. Siti Roslindar, Yaziz |
| author_sort | Radzi, N. S. M. |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Modelling the overnight Islamic interbank rate (IIR) is imperative to define the IIR performance as it would help the Islamic banks to adjust its costs of funding effectively and facilitate the policy makers to regulate a comprehensive monetary policy in Malaysia. The IIR framework which has been regulated by Bank Negara Malaysia under dual banking and financial system has always been overlooked in most previous studies in modelling the financial instruments rates. Therefore, it is vital to select the appropriate model as it resembles with the features of the IIR. The study assesses the forecasting performance of overnight IIR using the Box-Jenkins model. The suggested Box-Jenkins model has been applied to the Malaysian overnight IIR (in percentage) from 02/01/2001 to 31/12/2020. The empirical results determine that ARIMA (0,1,1) is the most appropriate model in forecasting overnight IIR as the model provides the smallest Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In multistep ahead forecasting, it can be summarised that ARIMA (0,1,1) model is able to trail the actual data trend of daily Malaysian overnight IIR up to 5-day ahead within 95% prediction intervals. |
| first_indexed | 2025-11-15T03:08:16Z |
| format | Article |
| id | ump-32912 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:08:16Z |
| publishDate | 2021 |
| publisher | Penerbit UMP |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-329122021-12-28T02:00:52Z http://umpir.ump.edu.my/id/eprint/32912/ Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model Radzi, N. S. M. Siti Roslindar, Yaziz QA Mathematics Modelling the overnight Islamic interbank rate (IIR) is imperative to define the IIR performance as it would help the Islamic banks to adjust its costs of funding effectively and facilitate the policy makers to regulate a comprehensive monetary policy in Malaysia. The IIR framework which has been regulated by Bank Negara Malaysia under dual banking and financial system has always been overlooked in most previous studies in modelling the financial instruments rates. Therefore, it is vital to select the appropriate model as it resembles with the features of the IIR. The study assesses the forecasting performance of overnight IIR using the Box-Jenkins model. The suggested Box-Jenkins model has been applied to the Malaysian overnight IIR (in percentage) from 02/01/2001 to 31/12/2020. The empirical results determine that ARIMA (0,1,1) is the most appropriate model in forecasting overnight IIR as the model provides the smallest Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In multistep ahead forecasting, it can be summarised that ARIMA (0,1,1) model is able to trail the actual data trend of daily Malaysian overnight IIR up to 5-day ahead within 95% prediction intervals. Penerbit UMP 2021-06-29 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/32912/1/Forecasting%20Malaysian%20overnight%20islamic%20interbank%20rate%20using%20the%20box.pdf Radzi, N. S. M. and Siti Roslindar, Yaziz (2021) Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model. Data Analytics and Applied Mathematics (DAAM), 2 (1). pp. 38-51. ISSN 2773-4854. (Published) https://doi.org/10.15282/daam.v2i1. 6837 https://doi.org/10.15282/daam.v2i1. 6837 |
| spellingShingle | QA Mathematics Radzi, N. S. M. Siti Roslindar, Yaziz Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title | Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title_full | Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title_fullStr | Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title_full_unstemmed | Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title_short | Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model |
| title_sort | forecasting malaysian overnight islamic interbank rate using the box-jenkins model |
| topic | QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/32912/ http://umpir.ump.edu.my/id/eprint/32912/ http://umpir.ump.edu.my/id/eprint/32912/ http://umpir.ump.edu.my/id/eprint/32912/1/Forecasting%20Malaysian%20overnight%20islamic%20interbank%20rate%20using%20the%20box.pdf |