Wasserstein-barycentric embedding fields beat traditional weighting in spatial factor models
uct · hf · 2026-09-03
A quant research paper on Hugging Face reconstructs a language-model embedding field via Wasserstein barycenters to build spatial factor models. Empirically, the approach predicts peer-misalignment penalties more accurately than conventional weighting schemes, demonstrating the potential of language-model representations in asset-pricing factor research.
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