The Performance of Several Combining Forecasts for Stock Index

In order to evaluate the performance of several combining forecasts, the paper firstly uses three single 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. Then it uses optimal weight linear combining forecasts model, BP neural based combining forecasts model and SVM-based combining forecasts model to forecast the above indexes. Through evaluating the results of these forecasting methods, it is argued that choosing the method which has the best forecasting result as the combining forecasts model can greatly enhance the forecast effectiveness.