Machine Learning-Based Prediction of Stock Market Returns

Focusing on the prediction of CSI 300 Index returns, this empirical study employs a hybrid CNN-LSTM-Attention model. The model integrates the strengths of CNN for local feature extraction, LSTM for temporal dependency modelling, and the Attention mechanism for key information focus, effectively capturing the multi-scale characteristics of financial data. Comparative experimental results demonstrate that multivariate models achieve superior fitting performance compared to univariate models, with