Stock Market Nonlinear Analysis and Prediction Toolbox

Stock Market Nonlinear Analysis and Prediction Toolbox integrates the original nonlinear time series analysis toolbox programs, featuring multiple complexity analysis methods (such as Higuchi's method, box-counting method), phase space reconstruction techniques (Cao's method, GP algorithm, mutual information method), maximum Lyapunov exponent determination (Wolf's method, small data sets method) and prediction procedures (Lyapunov exponent method, one-step multi-step prediction, etc.). The toolbox demonstrates high execution efficiency and practical usability, with optimized algorithms for real-world financial data processing.