Portfolio risk bounds without covariance matrices, using language-model representations
uct · hf · 2026-09-03
A quant finance paper on Hugging Face proposes using distribution-valued firm characteristics and language-model-embedding-based representations to build portfolios. The framework provides computable upper bounds on portfolio variance without estimating cross-asset return covariances, yielding low-variance allocations — a new approach to risk control in high-dimensional asset pools.
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