Technical indicators and the cross-section of corporate bond returns in a machine learning era
研究了用技术指标和机器学习模型预测公司债券收益，发现技术指标优于债券特征，且机器学习相比线性模型提升不大。
We explore the use of technical indicators to forecast corporate bond returns with various machine learning models. We show that technical indicators yield statistically significant and economically meaningful results, consistently outperforming bond characteristics. Although bond characteristics possess predictive power for bond returns, they do not provide incremental value beyond technical indicators across all bonds. Additionally, machine learning models do not offer substantial improvements over the benchmark linear model. These results underscore the significance of technical indicators in the corporate bond market.