A Novel Adaptive Multi-step-prediction Method for Chaotic Time Series and Its Applications in Stock Market
混沌序列自适应多步预测及在股票中的应用

Based on the short-term predictability of chaotic time series and the adaptive tracking chaotic trajectory of adaptive algorithm,a novel adaptive multi-step-prediction method is proposed to resolve the problem of adjusting filter's parameters of the adaptive prediction method during multi-step prediction in this paper;and this method is used to predict typical chaotic time series and chaotic stock data.During multi-step prediction this method can adjust filter's parameters and get the multi-step prediction value using the data we know.Simulation results show that: this adaptive multi-step-prediction method can be successfully used to make multi-step predictions of typical chaotic time series and stock data,and this method's multi-step-prediction performance is better than the adaptive prediction method's.