Forecasting with univariate time series models : a case of export demand for Peninsular Malaysia’s moulding and chipboard.
This study determines a suitable method from the univariate time series models to forecast the export demand of moulding and chipboard volume (m³) from Peninsular Malaysia using the quarterly data from March 1982 to June 2009. Export demand for moulding and chipboard were estimated using univariate...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Canadian Center of Science and Education
2010
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| Online Access: | http://psasir.upm.edu.my/id/eprint/14800/1/Forecasting%20with%20univariate%20time%20series%20models.pdf http://psasir.upm.edu.my/id/eprint/14800/ |
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| Summary: | This study determines a suitable method from the univariate time series models to forecast the export demand of moulding and chipboard volume (m³) from Peninsular Malaysia using the quarterly data from March 1982 to June 2009. Export demand for moulding and chipboard were estimated using univariate time series models including the Holt-Winters Seasonal, ARAR algorithms and the seasonal ARIMA models. The seasonal ARIMA (1, 0, 4) X (0, 0, 1, 0)4 model produced the best forecast at the lowest forecast errors of MAPE, MAE and RMSE at 18.83%, 32730.8 and 35282.13, respectively. It forecasts the volume (m³) of moulding and chipboard for export to reach more than 150000 m3, and it is expected to be within range of 100000 to 250000 m3 at 95% confidence level. The forecasts assist in decision making process and facilitate a short-term marketing plan to meet the export demand from international market. |
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