Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques

Forecasting the foreign currency exchange is a challenging task since it is influenced by political, economic and psychological factors. This paper focuses on the forecasting Malaysian Ringgit (MYR) exchange rate against the United States Dollar (USD) using Exponential Smoothing Techniques which ar...

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Publicado: Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis 2021
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spelling oai:doaj.org-article:063067fe343147b0b5cd6cc8c5aaba6f2021-11-06T02:21:32ZForecasting Malaysian Ringgit Using Exponential Smoothing Techniques2600-8793https://doaj.org/article/063067fe343147b0b5cd6cc8c5aaba6f2021-09-01T00:00:00Zhttp://repeater.my/index.php/jcrinn/article/view/183https://doaj.org/toc/2600-8793 Forecasting the foreign currency exchange is a challenging task since it is influenced by political, economic and psychological factors. This paper focuses on the forecasting Malaysian Ringgit (MYR) exchange rate against the United States Dollar (USD) using Exponential Smoothing Techniques which are Single Exponential Smoothing, Double Exponential Smoothing, and Holt’s method. The objectives of this paper are to identify the best Exponential Smoothing Technique that describes MYR for 5 years period and to forecast MYR 12 months ahead by using the best Exponential Smoothing Technique. The comparison between these techniques is also made and the best one will be selected to forecast the MYR exchange rate against USD. The result showed that Holt’s method has the smallest value of error measure which depending on the Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) for the evaluation part. The MSE is 1.43915x10-14 and MAPE is 2.5413 x 10-6. Meanwhile, the forecast value of MYR in August 2019 is RM 4.30226. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA PerlisarticleProbabilities. Mathematical statisticsQA273-280TechnologyTTechnology (General)T1-995ENJournal of Computing Research and Innovation, Vol 6, Iss 2 (2021)
institution DOAJ
collection DOAJ
language EN
topic Probabilities. Mathematical statistics
QA273-280
Technology
T
Technology (General)
T1-995
spellingShingle Probabilities. Mathematical statistics
QA273-280
Technology
T
Technology (General)
T1-995
Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
description Forecasting the foreign currency exchange is a challenging task since it is influenced by political, economic and psychological factors. This paper focuses on the forecasting Malaysian Ringgit (MYR) exchange rate against the United States Dollar (USD) using Exponential Smoothing Techniques which are Single Exponential Smoothing, Double Exponential Smoothing, and Holt’s method. The objectives of this paper are to identify the best Exponential Smoothing Technique that describes MYR for 5 years period and to forecast MYR 12 months ahead by using the best Exponential Smoothing Technique. The comparison between these techniques is also made and the best one will be selected to forecast the MYR exchange rate against USD. The result showed that Holt’s method has the smallest value of error measure which depending on the Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) for the evaluation part. The MSE is 1.43915x10-14 and MAPE is 2.5413 x 10-6. Meanwhile, the forecast value of MYR in August 2019 is RM 4.30226.
format article
title Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
title_short Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
title_full Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
title_fullStr Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
title_full_unstemmed Forecasting Malaysian Ringgit Using Exponential Smoothing Techniques
title_sort forecasting malaysian ringgit using exponential smoothing techniques
publisher Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
publishDate 2021
url https://doaj.org/article/063067fe343147b0b5cd6cc8c5aaba6f
_version_ 1718443959262380032