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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Main Authors: Radzi, N. S. M., Siti Roslindar, Yaziz
Format: Article
Language:English
Published: Penerbit UMP 2021
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/32912/1/Forecasting%20Malaysian%20overnight%20islamic%20interbank%20rate%20using%20the%20box.pdf
http://umpir.ump.edu.my/id/eprint/32912/
https://doi.org/10.15282/daam.v2i1. 6837
https://doi.org/10.15282/daam.v2i1. 6837
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spelling my.ump.umpir.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 https://doi.org/10.15282/daam.v2i1. 6837 https://doi.org/10.15282/daam.v2i1. 6837
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Radzi, N. S. M.
Siti Roslindar, Yaziz
Forecasting Malaysian overnight Islamic interbank rate using the Box-Jenkins model
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.
format Article
author Radzi, N. S. M.
Siti Roslindar, Yaziz
author_facet Radzi, N. S. M.
Siti Roslindar, Yaziz
author_sort Radzi, N. S. M.
title 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_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_sort forecasting malaysian overnight islamic interbank rate using the box-jenkins model
publisher Penerbit UMP
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/32912/1/Forecasting%20Malaysian%20overnight%20islamic%20interbank%20rate%20using%20the%20box.pdf
http://umpir.ump.edu.my/id/eprint/32912/
https://doi.org/10.15282/daam.v2i1. 6837
https://doi.org/10.15282/daam.v2i1. 6837
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score 13.160551