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Regime-Aware Portfolio Management via Retrieval-Augmented LLM-Guided Expert Switching
Financial markets are inherently non-stationary, making the effectiveness of individual portfolio-management strategies highly dependent on changing market conditions. This work proposes a retrieval-augmented expert-switching framework that dynamically selects portfolio management experts based on t
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