# BondBERT: What we learn when assigning sentiment in the bond market

arXiv: https://arxiv.org/abs/2511.01869 · HTML: https://mlsanity.com/paper/2511.01869/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 42 references that are in the map.
- First posted on arXiv 21 Oct 2025.

## Builds on (most cited first, 12 of 12)

- [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://mlsanity.com/paper/1908.10063/) (2019)
- [Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts](https://mlsanity.com/paper/1307.5336/) (2013)
- [FinGPT: Open-Source Financial Large Language Models](https://mlsanity.com/paper/2306.06031/) (2023)
- [Large Language Models in Finance: A Survey](https://mlsanity.com/paper/2311.10723/) (2023)
- [FinBERT: A Pretrained Language Model for Financial Communications](https://mlsanity.com/paper/2006.08097/) (2020)
- [FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets](https://mlsanity.com/paper/2310.04793/) (2023)
- [FinGPT: Democratizing Internet-scale Data for Financial Large Language Models](https://mlsanity.com/paper/2307.10485/) (2023)
- [Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models](https://mlsanity.com/paper/2306.12659/) (2023)
- [Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis](https://mlsanity.com/paper/2407.16150/) (2024)
- [Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy](https://mlsanity.com/paper/2411.06211/) (2024)
- [FinGPT: Enhancing Sentiment-Based Stock Movement Prediction with Dissemination-Aware and Context-Enriched LLMs](https://mlsanity.com/paper/2412.10823/) (2024)
- [Dynamic Asset Pricing: Integrating FinBERT-Based Sentiment Quantification with the Fama--French Five-Factor Model](https://mlsanity.com/paper/2505.01432/) (2025)

## Built on by (most cited first, 1 of 1)

- [CSTrader: A Testbed for Language-Grounded Trading in a Community-Driven Virtual Asset Market](https://mlsanity.com/paper/2606.31461/) (2026)

## Abstract (arXiv)

Bond markets respond differently to macroeconomic news compared to equity markets, yet most sentiment models are trained primarily on general financial or equity news data. However, bond prices often move in the opposite direction to economic optimism, making general or equity-based sentiment tools potentially misleading. We introduce BondBERT, a transformer-based language model fine-tuned on bond-specific news. BondBERT can act as the perception and reasoning component of a financial decision-support agent, providing sentiment signals that integrate with forecasting models. We propose a generalisable framework for adapting transformers to low-volatility, domain-inverse sentiment tasks by compiling and cleaning 30,000 UK bond market articles (2018-2025). BondBERT's sentiment predictions are compared against FinBERT, FinGPT, and Instruct-FinGPT using event-based correlation, up/down accuracy analyses, and LSTM forecasting across ten UK sovereign bonds. We find that BondBERT consistently produces positive correlations with bond returns, and achieves higher alignment and forecasting accuracy than the three baseline models. These results demonstrate that domain-specific sentiment adaptation better captures fixed income dynamics, bridging a gap between NLP advances and bond market analytics.