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About this paper
Yixiong Chen
The authors test quantum-assisted volatility forecasting on five-minute SSE Composite and CSI 300 data. A quantum circuit supplies a learned prior to an LSTM trained to operate with or without that signal. On CSI 300, after Drop-Prior training, classical-only inference has lower mean RMSE and QLIKE than inference retaining the prior across three seeds; this does not establish quantum advantage or generalization beyond these datasets.
Summary by alphaXiv.
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