---
title: ML for Trade Direction in Corporate Bonds
url: https://www.ml-quant.com/papers/repec/kap-rqfnac-v-63-y-2024-i-1-d-10-1007-s11156-024-01252-w/
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: RePEc:kap:rqfnac:v:63:y:2024:i:1:d:10.1007_s11156-024-01252-w
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11156-024-01252-w%3Bh%3Drepec%3Akap%3Arqfnac%3Av%3A63%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1007_s11156-024-01252-w
featured: 2024-05-28
citations: unknown
topic: Macro-Finance & Rates
---


# ML for Trade Direction in Corporate Bonds

Machine learning can enhance trade direction classification in corporate bond markets, with trade timing and information environment impacting the accuracy of existing rules.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11156-024-01252-w%3Bh%3Drepec%3Akap%3Arqfnac%3Av%3A63%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1007_s11156-024-01252-w
- Identifier: RePEc:kap:rqfnac:v:63:y:2024:i:1:d:10.1007_s11156-024-01252-w
- Released: 2024-05-28
- First featured: Quant Letter No. 51 (2024-05-28): https://www.ml-quant.com/issues/2024-05-28/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Macro-Finance & Rates

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