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Juniorprofessor Dr. Fabian Woebbeking

Juniorprofessor Dr. Fabian Woebbeking
Aktuelle Position

seit 1/23

Leiter der Forschungsgruppe Data Science in der Finanzökonomik

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 9/22

Wissenschaftlicher Mitarbeiter der Abteilung Finanzmärkte

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 12/22

Juniorprofessor

Martin-Luther-Universität Halle-Wittenberg

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Forschungsschwerpunkte
  • Data Science
  • Finanzintermediation
  • Analyse systemischen Risikos

Fabian Woebbeking ist seit September 2022 wissenschaftlicher Mitarbeiter in der Abteilung Finanzmärkte und seit Dezember 2022 Juniorprofessor an der Martin-Luther-Universität Halle-Wittenberg. Er beschäftigt sich mit Data Science Methoden zur Generierung ökonomischer Indikatoren aus unstrukturierten Datensätzen und forscht zu den Themen Finanzintermediation, Risikomanagement, Systemische Risiken, Machine Learning und Bayesianische Methodik in der Finanzökonomie.

Fabian Woebbeking hat an der Frankfurt School of Finance & Management studiert und an der Goethe-Universität Frankfurt promoviert.

Ihr Kontakt

Juniorprofessor Dr. Fabian Woebbeking
Juniorprofessor Dr. Fabian Woebbeking
- Abteilung Finanzmärkte
Nachricht senden +49 345 7753-851 LinkedIn Profil

Publikationen

Zitationen
135

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"Let Me Get Back to You" — A Machine Learning Approach to Measuring NonAnswers

Andreas Barth Sasan Mansouri Fabian Woebbeking

in: Management Science, Vol. 69 (10), 2023

Abstract

Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal nonanswers in earnings call questions and answers (Q&A). We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls.

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Correlation Scenarios and Correlation Stress Testing

Natalie Packham Fabian Woebbeking

in: Journal of Economic Behavior and Organization, Vol. 205 (January), 2023

Abstract

We develop a general approach for stress testing correlations of financial asset portfolios. The correlation matrix of asset returns is specified in a parametric form, where correlations are represented as a function of risk factors, such as country and industry factors. A sparse factor structure linking assets and risk factors is built using Bayesian variable selection methods. Regular calibration yields a joint distribution of economically meaningful stress scenarios of the factors. As such, the method also lends itself as a reverse stress testing framework: using the Mahalanobis distance or Highest Density Regions (HDR) on the joint risk factor distribution allows to infer worst-case correlation scenarios. We give examples of stress tests on a large portfolio of European and North American stocks.

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Cryptocurrency Volatility Markets

Fabian Woebbeking

in: Digital Finance, Vol. 3 (3), 2021

Abstract

By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.

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Arbeitspapiere

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The Price of Beauty: Biodiversity Effects on Residential Housing Markets

Michael Koetter Birte Winter Fabian Woebbeking

in: IWH Discussion Papers, Nr. 21, 2025

Abstract

We study how and why local biodiversity affects residential property values. Leveraging remotely sensed greenness indicators and a novel dataset of granular property listings, we examine how changes in vegetation load on real estate prices. Hikes in greenness are associated with higher listing prices, fewer properties listed, and reduced liquidity in housing markets. These results suggest that price hikes in housing markets are driven by supply-side constraints instead of a “greenium” that buyers might be willing to pay due to innate preferences. Exogenous zoning shocks to foster biodiversity corroborate the presence of supply side constraints as price drivers in residential housing markets. Our findings emphasize the need to calibrate biodiversity and (social) housing policy objectives more explicitly.

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The Limits of Local Laws in Global Supply Chains: Extending Governance or Cutting Ties?

Michael Koetter Melina Ludolph Hendrik Keilbach Fabian Woebbeking

in: IWH Discussion Papers, Nr. 14, 2025

Abstract

We exploit an information shock related to the German Supply Chain Due Diligence Act and use detailed customs data to analyze how smaller, non-listed firms respond when expecting accountability for externalities beyond their organizational boundaries. Product-level regressions reveal a substantial reduction in imports from high ESG-risk production sectors. Adjustments occur mainly at the extensive margin, indicating that firms cut ties with high-risk suppliers. The product-level results translate into meaningful changes in overall international procurement for firms with Big Four auditors. Our findings suggest potential limits to mandates requiring firms to integrate broad sustainability considerations into operational decisions.

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Information Flow and Market Efficiency - The Economic Impact of Precise Language

Andreas Barth Sasan Mansouri Fabian Woebbeking

in: IWH Discussion Papers, Nr. 13, 2025

Abstract

This paper examines the impact of complex yet precise language, particularly financial jargon, on information dissemination and ultimately market efficiency. As a natural laboratory, we analyze the information exchanged during earnings conference calls, where we instrument jargon with the Plain Writing Act of 2010. Our findings suggest that the Act‘s promotion of plain language usage results in a reduction in complex financial jargon for US firms. However, in contrast to the presumed benefits of accessible language, this reduction in jargon is associated with a decrease in market efficiency, implying that the Act may inadvertently hinder information flow. This finding is particularly important at the juncture where human-generated information is received by machines, which are known to be vunerable to ambiguous inputs.

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