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raph -Based Uncertainty-Aware Financial Forecasting via Cross-Asset Conformal Prediction

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TL;DR

Cross-Asset Graph Conformal Prediction (CA-GCP), a framework that pools volatility-normalized nonconformity scores across the correlation-graph neighborhood of each target asset using a proximity-and recency-weighted quantile, grounded in the theory of weighted conformal prediction, is proposed.

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