Fabian Wöbbeking

Fabian Wöbbeking is an Assistant Professor at the Martin Luther University Halle-Wittenberg and leads the Data Science in Financial Economics research group at the Leibniz Institute for Economic Research Halle (IWH). His roles include analyzing unstructured datasets using Data Science methods to generate economic indicators, with a focus on financial intermediation, systemic risk, and machine learning applications in finance. He also contributes to macroprudential policy research and correlation stress testing frameworks.

• Education: Studied at the Frankfurt School of Finance & Management; earned a PhD at Goethe University Frankfurt.

Wöbbeking’s research bridges Data Science and Financial Economics, emphasizing machine learning for financial analytics, risk modeling, and language-based information asymmetry. His work includes measuring non-answers in earnings calls, correlation stress testing, and cryptocurrency volatility dynamics.

His recent publications highlight interdisciplinary approaches to financial markets. Key trends include leveraging NLP for corporate disclosures, Bayesian methods for risk factor modeling, and blockchain analytics for volatility indices. These works demonstrate cross-domain applicability of Data Science techniques.

At IWH, he collaborates with teams like the Financial Markets department, contributing to European Real Estate Index (EREI) development and macroprudential policy analysis. His projects integrate economic theory with computational methods to address systemic risks and market inefficiencies.