Indian natural rubber price forecast–An Autoregressive Integrated Moving Average (ARIMA) approach

SHYJU MATHEW; RAMASAMY MURUGESAN

doi:10.56093/ijas.v90i2.103067

Authors

SHYJU MATHEW PhD Scholar, National Institute of Technology, Tiruchirappalli, Tamil Nadu 620 015, India
RAMASAMY MURUGESAN Professor, Department of Humanities and Social Sciences, National Institute of Technology, Tiruchirappalli

https://doi.org/10.56093/ijas.v90i2.103067

Keywords:

ARIMA, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Natural rubber, Rubber price forecast

Abstract

The objective of this study was to forecast the price of natural rubber in India during April 2019 to March 2020 by employing autoregressive integrated moving average (ARIMA). The monthly pricing data for the period from April 2008 to March 2018 was used for the study. The analysis was carried out during the year 2018–19. RSS4 (Ribbed Smoked Sheets), latex (60% DRC (Dry Rubber Content)) and ISNR 20 (Indian Standard Natural Rubber) are the different types of Indian natural rubber that are competitive in international rubber market. The prices of these types of natural rubber were taken for modelling. AIC was used as a selection criterion for the best-fitted model. ARIMA(3,1,2) for RSS 4, ARIMA (3,1,2) for Latex 60% DRC, and ARIMA (4,1,3) for ISNR20were the most suited modelsto forecast the price.The evaluation metrics were R², Adjusted R², Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). These were employed for validating the forecasting model. The price forecasting of natural rubber in India can be a better-suited tool for the policymakers to decide on their investment in natural rubber cultivation.

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