*E-mail address: senthilkumargtanuvas@gmail.com
The present study was aimed to model and forecast the feed prices of small ruminants in Tamil Nadu using the time series data on market prices of concentrate feed from January 2012 to December 2022. After applying tests for the presence of trend, seasonality and stationary data, various time series models viz., mean, naive, random drift, seasonal naive, simple exponential smoothing, Holt's linear, Holt-Winters, autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) were fitted. Based on accuracy and error measures of sample forecasts, the best fit model for forecasting of prices were ARIMA (1,1,0) for sheep feed, SARIMA (1,1,0)(1,0,0) for goat feed and random drift model and ARIMA (2,1,0) model for creep feed. Short-term forecast of feed prices of small ruminants may be utilized by the farmers in order to plan and make decision of feed purchase thereby reduce feed cost.
Autoregressive integrated moving average, Feed prices, Forecasting, Small ruminants, Time series models