Financial Bond Similarity Search Using Representation Learning
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 20 references that are in the map. First posted on arXiv 2 Feb 2026.
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10 of 20 references.
References · 10
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- 2025Generative AI Enhanced Financial Risk Management Information Retrievalcited by 3
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