Prof. Dr. Martin Hillebrand

Fachgebiete: Digital Transformation, Data Science, Fintech, Quantiative Methods

AUSBILDUNG

2000-2003: Dr. rer. nat. in Mathematik an der Universität Oldenburg

1997-2000: Diplom in Mathematik an der Universität Göttingen

BERUFSERFAHRUNG

Seit SoSe22: Professor Quantitative Methoden an der XU Exponential University

Seit 2013: Quantitativer Analyst, Europäischer Stabilitätsmechanismus (ESM), Luxemburg. Refinanzierung und Derivate, Kapitalmarktanalyse, Geschäftsinnovation

2009-2013: Risikobeauftragter, Deutsche Finanzagentur, Frankfurt. Entwicklung einer Kreditrisikostrategie für das Geldmarktportfolio (25 Mrd. Euro) der Deutschen Finanzagentur

2007-2009: Quantitativer Analyst, Sal. Oppenheim/Equity Derivatives Trading, Frankfurt. Entwicklung von Pricing Tools (7 Mrd. e Portfolio) und technischen Handelsstrategien

2007: Quantitativer Analyst, Deutsche Bank/Risk Analytics, Frankfurt. Entwicklung von Scorecards für das Privatkundengeschäft

2004-2007: Wissenschaftliche Mitarbeiterin, Technische Universität München, München. Forschung über die Preisgestaltung von Kreditderivaten und Risikoanalyse


FORSCHUNGSINTERESSE

Sustainable Finance, Fintech, Capital Market Dynamics

PUBLIKATIONEN

Schwendner, Peter; Schüle, Martin; Hillebrand, Martin: Sentiment analysis of European bonds 2016 – 2018, Frontiers in Artificial Intelligence 2 (20), 2019

Schwendner, Peter; Schüle, Martin; Ott, Thomas: European Government Bond Dynamics and Stability Policies: Taming Contagion Risks, Journal of Network Theory in Finance 1 (4), 2015

Kadam, Ashay; Hillebrand, Martin: Dynamic credit risk modeling, working paper, 2009

Böcker, Klaus; Hillebrand, Martin: Interaction of Market And Credit Risk: An Analysis of Inter-Risk Correlation and Risk Aggregation, Journal of Risk Vol 11 No 4, 2009 

Hillebrand, Martin: On Robust Corner-Preserving Smoothing in Image Processing, monograph, Verlag Dr. Müller, 2008

Müller, Christine: Outlier robust corner-preserving methods for reconstructing noisy images, Annals of Statistics 2007, Vol.35 No. 1, 132-165

Hillebrand, Martin: Modelling and estimating dependent loss given default, RISK, September 2006

Müller, Christine; Hillebrand, Martin: On consistency of redescending M-kernel smoothers, Metrika 2006, Vol. 63 No. 1, 71-90

Hillebrand, Martin: On Robust Corner-Preserving Smoothing in Image Processing (Dissertation, 2003)

AUSGEWÄHLTE PRÄSENTATIONEN

2020: How to Run a Primary Market Bond Desk- Developing a Secondary Market, Zurich, University of Applied Sciences.

2019: Predicting Investor Behaviour in European Bond Markets. A Machine Learning Approach, Zurich, European Conference on AI in Finance and Industry and Summit of the Swiss Financial Analysts Association.

2018: Does the Euro Rescue Mechanism Work? Visualizing Market Sentiment, University of Dortmund and University of Luxembourg.

2017: The ESM- a Crisis Mechanism and its Strategic Presence in Volatile Markets: A Quantitative Approach, London, Global Borrowers and Bond Investors Forum

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