Stock Market Multi-step Forecasting Based on Fuzzy Neural Networks and R/S Analysis
基于模糊神经网络和R/S分析的股票市场多步预测

Input space of nonlinear model is partitioned into several fuzzy subspaces. Within each subspace, a local linear model is used to model the nonlinear model. The global model output is obtained by interpolating the local model outputs. Adaptive network fuzzy inference system (ANFIS), based on Sugeno fuzzy inference model, is one way of neural network realization of the fuzzy modeling based on the ideal of local linear modeling above. The results of R/S analysis show that Shanghai stock market has long-term memory, thus possible to predict. This study combines ANFIS and FMH to implement multi-step prediction of Shanghai Stock Exchange index.