Predicting the agriculture stock prices in Tehran Stock Exchange is greatly helped for investors in making decisions and accepting the agriculture stock price risk. For predicting agriculture price stock three econometric methods are used in this paper; include Auto-Regressive model, Moving Average Process model and Autoregressive Integrated Moving Average Process model. The paper compares these methods in predicting the daily stock price. The selected sample in this research is Magsal Agriculture and Livestock Company stock price which is one of the most active stock companies. Time series data of daily stock price are used from 1389/11/4 to 1390/4/1 period. The results showed that the daily stock price of Maysal company is located at an unstable level and it can become stable by making a difference. Among econometric models ARMIA model is used for predicting because it has a better processing power. Another reason of using ARIMA model is the slight difference between the predicted prices and the actual stock price; it deduces the small percentage of prediction error.
Chizari, A., & Abdollahi, M. (2014). Forecasting Agriculture Stock Price on Tehran Stock Exchange: Magsal Agriculture and Livestock Company. Agricultural Economics, 8(Special Issue), 233-243.
MLA
Amirhossein Chizari; Mehrnoosh Abdollahi. "Forecasting Agriculture Stock Price on Tehran Stock Exchange: Magsal Agriculture and Livestock Company". Agricultural Economics, 8, Special Issue, 2014, 233-243.
HARVARD
Chizari, A., Abdollahi, M. (2014). 'Forecasting Agriculture Stock Price on Tehran Stock Exchange: Magsal Agriculture and Livestock Company', Agricultural Economics, 8(Special Issue), pp. 233-243.
VANCOUVER
Chizari, A., Abdollahi, M. Forecasting Agriculture Stock Price on Tehran Stock Exchange: Magsal Agriculture and Livestock Company. Agricultural Economics, 2014; 8(Special Issue): 233-243.
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