Financial Bond Similarity Search Using Representation Learning

Amin Haeri, Mahdi Ghelichi, Nishant Agrawal, David Li and Catalina Gomez Sanchez

Papers from arXiv.org

Abstract: Finding similar bonds remains challenging in fixed-income analytics, as numerical financial attributes often overshadow categorical non-financial ones such as issuer sector and domicile. This paper shows that these categorical attributes dominate the predictability of spread curves and proposes embedding models to capture their semantic similarities, outperforming one-hot and many other baselines. Evaluated via sparse-issuer augmentation, the approach improves risk modeling and curve construction.

Date: 2026-02
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