Forecast and Analysis of Shanghai Composite Index Based on Extreme Learning Machine
TAN Li-yun
LIU Hai-sheng
TAN Long
Abstract：For the features of stock index such as randomness , time-variant, volatile and non -linear, and for the defects of traditional linear prediction methods like low accuracy , we propose a method for forecasting stock index based on extreme learning machine.Extreme Learning Machine has the merits of high training speed , excellent global optimum and generalization ability , etc., which overcome the shortcomings of the BP neural network such as low training speed , over-fitting , local minima.Using the data of Shanghai Stock Ex-change from 1991 to 2013 on the performance of the algorithm and data of 2014 for testing , 100 test data simu-lation results show that the multiple correlation coefficient is up to 0.9935.Extreme Learning Machine is a stock index prediction algorithm with high precision and small error , which can provide a valuable reference for users.
Keywords：BP neural networkELM extreme learning machineIndex of Shanghai Stock Exchangeprediction
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 57-60 )