Abstract:This study presents a novel approach to incorporating news topics and their associated sentiment into predictions of breakeven inflation rate (BEIR) movements for eight countries with mature bond markets. We calibrate five classes of machine learning models including narrative-based features for each country, and find that they generally outperform corresponding benchmarks that do not include such features. We find Logistic Regression and XGBoost classifiers to deliver the best performance across countries. We… Show more
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