Research on Applying Wavelet Transform to Stock Market Forecast
Zheng Pi-e · Nanjing Linye Daxue xuebao · 2005
In this paper,the modeling and forecast of Shenzhen stock market are studied through(wavelet) transform theory.First,share index time series are decomposed into several parts.Then,the chaotic forecasting models are established to forecast each part respectively.Finally,the forecast(result) of chaotic model is reconstructed by wavelet theory and the final forecast results of the original time series are achieved.Furthermore,the reason of improved forecasting precision is analyzed further from the angle of the construction of attractors.The time series obtained by wavelet decomposition are simpler than the original time series.Thus,they are forecasted more easily than the original time series.It proves that wavelet transform is of wide potential applications in the respect of stock market forecast.