A systematic TDA-ML benchmark on four stock indices finds Takens embedding point clouds and Betti curve features most effective; the best CSI300 configuration reaches about 160% cumulative return in backtest.
Forecasting the volatility of stock price index
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Exploring applications of topological data analysis in stock index movement prediction
A systematic TDA-ML benchmark on four stock indices finds Takens embedding point clouds and Betti curve features most effective; the best CSI300 configuration reaches about 160% cumulative return in backtest.