Prediction in Stock-price Index Based on Improved Gene Expression Programming
Qian Xiao-shan · Jisuanji gongcheng · 2009
This paper introduces the basic principle of Gene Expression Programming(GEP).An improved GEP algorithm called IGEP based on dynamic mutation operator which is changed with the gene number of the genome and the number of evolutionary generation is presented.The algorithm complexity of IGEP is given in the paper.Furthermore,IGEP is applied in the solution of prediction in stock-price index.The simulation results show that the model found by IGEP is more accurate than the one of classic GEP and which proves the IGEP can be widely used in many fields.