---
title: Machine Learning and the Cross-Section of Emerging Market Corporate Bond Returns
url: https://www.ml-quant.com/papers/ssrn/4632924/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4632924
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4632924
featured: 2023-11-15
citations: 1
topic: Asset Pricing & Factors
---


# Machine Learning and the Cross-Section of Emerging Market Corporate Bond Returns

Machine learning models considering nonlinearities and interactions offer better predictions of corporate bond behavior in emerging markets with high transaction costs, with key predictors tied to low-risk macro and momentum factors.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4632924
- Identifier: SSRN 4632924
- Released: 2023-10-30
- First featured: Quant Letter No. 26 (2023-11-15): https://www.ml-quant.com/issues/2023-11-15/
- Citations (Semantic Scholar): 1
- Published in: not yet
- Topic: Asset Pricing & Factors

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