dates price risk management using futures markets tools (bivariate garch model)

agricultural activities are risky activities. in these activities, various natural, social and economic risks have created fragile and vulnerable situation for producers. price risk in agricultural products has caused financial problems for many producers and farmers. to deal with these price risks and price fluctuations, there are varieties of tools. this paper focused on futures markets instruments as risk management tools for date's price risks management. this study used monthly futures prices of dates and used mean-variance framework to determine the optimal hedge ratio with ols method. due to the conditional variances autocorrelated in residuals in regression models, time varying hedge ratios with bivariate garch models were determined. bivariate garch model was used in this study to determine hedge ratios. therefore, first, time varying conditional variance covariance matrix with using multivariate models based on heterogeneous variance bekk (1, 1) was estimated. then, using the results of this matrix, the optimal time varing hedge ratios was calculated. dates future price series were predicted using artificial neural networks pattern and the garch model. the results of hedge performance showed that time varying hedge ratios were eliminated more price risk than the ols method. the results showed that the average hedge ratios of bivariate garch model is 0.7, meaning that about 70% of the date's price risk could be reduced with sales in the futures market.