Hybrid LSTM-QCBM model outperforms classical LSTM on SSE Composite and CSI 300 volatility forecasting and supports quantum-assisted training followed by fully classical inference.
Deep learning with long short-term memory networks for financial market predictions.European Journal of Operational Research, 270(2):654–669
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A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines
Hybrid LSTM-QCBM model outperforms classical LSTM on SSE Composite and CSI 300 volatility forecasting and supports quantum-assisted training followed by fully classical inference.