Stock Index Modeling Using the System of Differential Equations

Abstract

Stock index is an important financial problem, and very difficult to be modeled. In this paper, the system of ordinary differential equation (ODEs) is used to model the behavior of stock markets. The tree-structure based evolutionary algorithm and artificial bee colony algorithm (ABCA) are used to evolve the architecture and parameters of additive tree model for the system of ordinary differential equations. 4-year for NIFTY Index is used to test the performance of our model. The results reveal that the model could represent the stock index behavior very accurately than other intelligent system.