Natalie Packham

Natalie Packham is Professor of Mathematics and Statistics at Berlin School of Economics and Law and Principal Researcher within the International Research Training Group High Dimensional Nonstationary Time Series (IRTG 1792) at Humboldt University Berlin. Natalie has several years of industry experience as a front office software engineer at an investment bank, and is frequently involved in industry-related research and consulting projects. Her research expertise includes Mathematical Finance, Financial Risk Management and Computational Finance, and her academic work has been published in Mathematical Finance, Finance & Stochastics, Quantitative Finance, Journal of Applied Probability and many other academic journals. She is associate editor of Methodology and Computing in Applied Probability and Digital Finance and co-chair of the GARP Research Fellowship Advisory Board. Natalie holds an M.Sc. in Computer Science from the University of Bonn, a Master's degree in Banking & Finance from Frankfurt School, and a Ph.D. in Quantitative Finance from Frankfurt School.

EDUCATION

• Ph.D. (Dr. rer. pol.) Finance, Frankfurt School of Finance & Management, 2009
• M.A. Banking & Finance, Frankfurt School of Finance & Management, 2005
• M.Sc. (Diplom) Computer Science, University of Bonn, 2000
• B.Sc. (Vordiplom) Computer Science, University of Bonn, 1997

EMPLOYMENT AND AFFILIATIONS

• Professor of Mathematics and Statistics, Berlin School of Economics and Law, since 2016
• Principal Investigator and Associated Researcher within the International Research Training Group 1792 “High Dimensional Non-Stationary Time Series”, Humboldt University Berlin, 2018-2023
• Assistant Professor, Frankfurt School of Finance & Management, 2009–2016
• (one year parental leave)
• Research Assistant, Frankfurt School of Finance & Management, 2005–2009
• Senior Software Engineer, Dresdner Kleinwort Wasserstein, Frankfurt and London, 2001–2005
• Positions at Robert Bosch GmbH, Artifical Life Deutschland AG and IBM Deutschland GmbH, 1997–2001

RESEARCH INTERESTS

• Mathematical Finance, Financial Risk Management, Computational Finance, Extreme Value Theory, Cryptocurrencies, Bayesian Statistics

TEACHING

• Game Theory and Strategic Decision-Making (Bachelor), since 2021
• Statistics of Finance (Bachelor), since 2021
• Computational Finance and FinTech (Master), since 2019
• Corporate Finance / Advanced Coroprate Finance (Master), 2018-2019
• Derivatives Pricing in Theory and Practice (Master), 2018
• Quantitative Empirical Methods (Master), since 2017
• Mathematics for Business and Economics (Bachelor), since 2016
• Statistik / Statistics (Bachelor), since 2016
• Statistik 2 (Bachelor), since 2017
• Management of International Asset Portfolios (Master), 2016, 2021
• Financial Engineering (Bachelor), 2016-2018
• Mathematical Problem Solving (Short lecture, PhD), 2015
• Quantitative Finance Research Colloquium (PhD-seminar), 2014
• Principles of Finance (Master), 2009, 2011, 2012
• Risk Management (Master), 2009, 2010, 2012, 2013, 2014, 2015
• Foundations of Risk Management and Market Risk (Executive Master), 2010, 2011, 2012, 2013, 2015
• Risk Modelling (Master and Excec. Master), 2010, 2011, 2012, 2013, 2014, 2015, 2016
• Arbitrage Theory (Master), 2014, 2015, 2017
• Effective C++ (Master Quant. Finance), 2009
• Numerical computation with Octave (Master Quant. Finance), 2006, 2007, 2008, 2009
• Foundations of Finance (Bachelor), 2009, 2010
• Introduction to Credit Derivatives (Master/Bachelor), ERASMUS teaching programme, IUP Nancy 2, France, 2008