MSc

The study entitled “Time series analysis and forecasting of the prices of
Indian Natural Rubber” is primarily intended to forecast the prices for Indian
Natural Rubber (NR). For forecasting the prices, firstly, domestic NR price was
decomposed it into time series components. Evaluation of growth, instability
and relationship between the domestic and international prices in the pre WTO
and post WTO periods were carried out in this study.
For decomposition of domestic NR prices into time series components,
additive decomposition was tried. The data were decomposed into trend,
seasonal and cyclic components. The trend values proved that there was
quadratic trend over the years. Seasonality indices revealed that the highest price
was in June and lowest price in December. Cyclic components showed three
cycles over a period of time under investigation.
For evaluation of growth and instability, volatility and instability
analyses were carried out for pre-WTO, post-WTO and overall periods in terms
of rupees as well as dollars. Two types of volatility i.e., intra-annual volatility
(within year dispersion) and inter annual volatility (between year dispersion)
were calculated. Intra-annual and inter annual volatility were higher in post-
WTO for international and domestic NR price series and the crude oil price
showed higher volatility in pre-WTO period in terms of rupees as also in dollars.
GARCH (1,1) model gave an additional evidence for persistence of volatility. It
proved that the volatility persisted in the overall period in terms of rupees and
dollars for domestic and international NR price. Instability analysis showed that
the price instability in post-WTO period was almost double than that of pre-
WTO period and it tripled in the overall period in terms of rupees. In terms of
dollars, the instability in post-WTO and overall period was almost triple than
pre-WTO period for domestic and international NR prices and crude oil prices
showed almost double instability than pre-WTO period.
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The relationship between domestic and international NR prices were
analysed through cointergration analysis and Vector error correction model
(VECM). The direction of relation was drawn by Granger Causality test.
Cointegration and Granger Causality test proved that there was at least
unidirectional relationship among the variables. VECM analysis proved that
there was long run relationship between domestic NR price, international NR
price and crude oil price. It revealed that, a speed rate of adjustment 14.3 per
cent was required for domestic NR price series to correct its previous period.
There were many general factors affecting the prices of domestic NR like
synthetic rubber production, crude oil prices, international rubber demand and
supply, international transactions, exchange rates, natural factors and
development of automobile industries. Stepwise regression analysis was used to
sort out the factors affected in pre-WTO and post-WTO periods. In pre-WTO,
domestic NR price was affected by international NR prices and in post-WTO by
international NR prices and SR consumption.
Domestic NR prices were forecasted with three different models like
Stepwise regression method, ARIMA and SARIMA models. Stepwise
regression method could be predicted when the variables like international NR
prices and import value of NR were available. Among ARIMA and SARIMA
models, ARIMA (4,1,4) and (4,1,4) (1,0,1) 12 was found to be best judged as per
different statistical criteria for assessing the model fit and model adequacy.