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Department of Engineering Science University of Oxford, Machine Learning Research Group, Department of Engineering Science, University of Oxford
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Forget generic deep learning models—for financial time series prediction, architectures explicitly designed to capture temporal dynamics, like VSN with LSTM, deliver superior risk-adjusted returns and robustness.
Fine-grained task decomposition in LLM-powered trading agents unlocks significantly better risk-adjusted returns, outperforming traditional coarse-grained approaches.
