Modeling and the impact of economic shocks on food industry stock returns

The purpose of this study is modeling and the effect of economic shocks on stock returns of food industry during the period 2009 to 2020. In this research, the optimal macroeconomic variables on the stock returns of food companies are modeled using the genetic algorithm approximation function method and then the impulses and shocks of macroeconomic variables affecting the stock returns of food industries are analyzed by Auto regression method has been analyzed. Initially, using the genetic function approximation algorithm, four variables of OPEC oil price, liquidity volume, land price and stock price index were identified among the eight macroeconomic variables as influential variables in the optimal regression model. OPEC oil prices and land prices have a negative and significant effect on the stock returns of food companies, while the volume of liquidity and stock price index have a positive and significant effect on the stock returns of food companies. Given the response impulse functions, the stock return reaction to OPEC oil prices and liquidity was initially positive. In the analysis of variance method, the largest share is due to the shock of the food industry stock returns to itself, followed by the volume of liquidity. Given the positive impact of liquidity on the stock returns of food industry companies, it is suggested that policy makers and planners to implement policies to increase the volume of liquidity to food industry companies in order to develop food industry investment.