Reimagining Credit Investing: Leveraging Data & Machine Learning

Join Bloomberg’s Head of BQuant Research to explore how to integrate data-driven, factor-based insights into credit research using BQuant Enterprise, Bloomberg’s Python-based data science and research platform. Designed for both fundamental and quantitative analysts, you will learn how quantitative methods — such as bond bucketing, curve fitting, and machine learning techniques — can complement traditional credit analysis to estimate bond fair value, based on issuer fundamentals and market dynamics, to achieve true value investing. We will also explore how to backtest these strategies, enabling credit investors to evaluate the robustness of quantamental approaches before applying them in live investment workflows.