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The study on “Price forecast models for coconut and coconut oil” was conducted to estimate seasonal variations in prices of coconut oil, copra and coconut, to evaluate different time series forecast models for prices of coconut oil, copra and coconut and to suggest suitable forecast models for Alappuzha, Kochi
and Kozhikode markets.
Time series data on monthly average prices of coconut oil and copra for
Alappuzha, Kochi and Kozhikode markets from January 1990 to December 2015
and for coconut price at Alappuzha market from January 1998 to December 2015
were collected from Coconut Development Board (CDB), Kochi formed the
database.Analysis of price pattern revealed that wide fluctuation exists in the prices of coconut oil and copra at Alappuzha, Kochi and Kozhikode markets and price of coconut at Alappuzha market. For coconut oil and copra price, the coefficient of
variation was around 50 per cent indicating the instability in prices and a coefficient
of variation of 37 per cent for coconut price showed that variability in price is lower than that of coconut oil and copra.
Seasonal indices for the 12 months from January to December showed that
December is the peak price month for coconut oil at Alappuzha and Kozhikode
markets, whereas it is in January at Kochi. Lowest price is observed in May at Alappuzha and Kozhikode market, whereas, at Kochi it is in July. In all the three markets, September – February is the buoyant phase and price depression is during
March - August. For copra, peak price is in December at Alappuzha and Kochi
markets, whereas, it is in November at Kozhikode. Trough price for copra is in
May in all the three markets. October to February is favourable for copra price in
all the three markets, whereas, depressed phase is from March to September. For coconut, peak price at Alappuzha market is in December and the buoyant phase is from November to February. April is the low price month with depressed phase from March to October. During the summer months from March
to May, harvest the coconuts as tender and increase the production of neera. Also,
during March- September, where the price of coconut oil and copra is low, steps are to be taken to convert coconut into other value added products like desiccated coconut powder, virgin coconut oil, activated carbon etc. and to identify regular
markets in major cities of India as also outside India.
Different forecast models were fitted viz., Auto regressive Integrated
Moving Average (ARIMA), Artificial Neural Network (ANN) and exponential smoothing models (single, double, Holt-Winters’ additive and multiplicative) were fitted and compared for prices of coconut, coconut oil and copra in different market.
Holt-Winters’ Multiplicative Seasonal (HWMS) model is the appropriate
forecast model for price of coconut oil at Alappuzha and Kochi markets. At Kozhikode market, SARIMA(1,1,1)(1,0,1)12 and HWMS can be used. HWMS model is selected as the suitable forecast model for copra at all markets. ARIMA
(0,1,1) model is suitable for forecasting price of coconut at Alappuzha market.