The Forecasts Performance of Gray Theory, BP Network, SVM for Stock Index

In order to evaluate the performance of several forecasts, the paper firstly uses three forecasting methods, namely grey model (GM (1,1)), BP neural networks and support vector machines (SVM), to forecast the Shanghai Industrial Index, the Shanghai Commercial Index, the Shanghai Real Estate Index, t...

Full description

Saved in:
Bibliographic Details
Main Authors: Fengqin Niu, Shuangshuang Nie, Weihong Wang
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Artificial neural networks
BP neural networks
Economic forecasting
grey model
Knowledge acquisition
Knowledge management
Mathematical model
Neural networks
Performance Evaluation
Predictive models
Stock Index
Stock markets
Support vector machines
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to evaluate the performance of several forecasts, the paper firstly uses three forecasting methods, namely grey model (GM (1,1)), BP neural networks and support vector machines (SVM), to forecast the Shanghai Industrial Index, the Shanghai Commercial Index, the Shanghai Real Estate Index, the Shanghai Public Utilities Index. Through evaluating the results of these forecasting methods, it is argued that, for forecasting concussing stock market, the forecast effects of BP network method is obviously better than the forecast effects of GM (1, 1) method and SVM method; GM (1, 1) method and SVM method are more suitable for forecasting stable stock market.
DOI:10.1109/KAM.2008.161