Cheng fuzzy time series model to forecast the price of crude oil in Malaysia / Jasmani Bidin ... [et al.]

• Main Authors: Bidin, Jasmani, Sharif, Noorzila, Syed Abas, Sharifah Fhahriyah, Ku Akil, Ku Azlina, Abdullah, Nurul Aqilah
• Format: Article
• Language: English
• Published: UiTM Cawangan Perlis 2022
• Subjects: Investment, capital formation, speculation; Time-series analysis
• Online Access: https://ir.uitm.edu.my/id/eprint/68915/1/68915.pdf; https://ir.uitm.edu.my/id/eprint/68915/; https://crinn.conferencehunter.com/index.php/jcrinn

Crude oil is one of the important commodities to Malaysia. As a producer and exporter of oil and gas, Malaysia has gained high Gross Revenue from this sector. Crude oil is the global commodity and highly demanded. Therefore, major price changes on the commodity have a significant influence on world economy. Market sentiment, demand, and supply are some elements directly influencing the oil prices. Since crude oil is the backbone of businesses and is extremely important to the economy, it is essential to study the price of crude oil for future planning purposes. For that reason, this study proposes the use of the Cheng Fuzzy Time Series to predict crude oil price in Malaysia. In this study, Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the forecast performance. The finding shows that Cheng Fuzzy Time Series Model using eight intervals representing linguistic prices is able to produce a good result in forecasting since the analyses shows low values of RMSE and MAPE (less than 10 percent). Although this is the fundamental study but the finding may assist many sectors in Malaysia, such as governments, enterprises, investors, and businesses to produce a better economic planning in the future especially after the pandemic covid-19 phase.