Forecasting Real Option Price Model by Means of Evolutionary and Genetic Algorithms

Abstract

Research goals and objective: to predict real option prices using evolutionary and genetic algorithms which affect the accuracy of price forecasting. The object of research: real option price model. The subject of research: forecasting evolutionary and genetic algorithms for real option price model. Research methods are genetic algorithm, evolutionary algorithm, statistical technique. Results of the research: in options trading one of the main tasks is to determine the fair price option, using which we can estimate what options are undervalued, and which ones are overvalued at the moment. The decision on the purchase or sale of a particular option is made according to these algorithms. In this paper we apply genetic and evolutionary algorithms in the areas of financial instruments in order to create software intended for analysis and forecast of real price option.