Phone: +49 (0)202 / 439 - 2487

Office: M.14.27

E-mail: pigorsch[at]uni-wuppertal.de

Office hours: By appointment via e-mail.

Short CV:

Uta Pigorsch began her studies of Business Administration at the Julius-Maximilians-Universität Würzburg. In 1998, she received her Master’s degree in Economics from the University at Albany, State University of New York. Thereafter, she switched to the University of Kiel, where she completed her diploma studies in Quantitative Economics and worked as a research assistant at the Institute for Regional Research. In the period from 2003 until 2007 she was research assistant at the Institute for Econometrics and Operations Research at the University of Bonn. During this time she was also a visiting scholar at Duke University, NC. In 2007 she received her doctoral degree from the University of Bonn under the supervision of Prof. Dr. Jörg Breitung, and became assistant professor for Applied Econometrics at the University of Mannheim. Since 2015, she holds the chair of Economic Statistics and Econometrics at the University of Wuppertal.

Research Focus:

• Financial Econometrics
• Time Series and Network Analysis
• Dynamic Factor Models

Current Working Papers:

• Short- to Long-Term Realized Volatility Forecasting using Extreme Gradient Boosting (with Andreas Teller and Christian Pigorsch), 
• https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4267541

Publications:

• Reversal of Monday returns: It is the afternoon that matters, Finance Research Letters, 2024, (with Sebastian Schäfer)

• Anxiety in Returns, Journal of Behavioral Finance, 2023, (with Sebastian Schäfer)

• Local Assortativity in Weighted and Directed Complex Networks, Physica A: Statistical Mechanics and its Applications, Volume 630, 2023, 129231 (with Marc Sabek)

• Assortative Mixing in Weighted Directed Networks, Physica A: Statistical Mechanics and its Applications, Volume 604, 2022, 127850 (with Marc Sabek)

• High-Dimensional Stock Portfolio Trading with Deep Reinforcement Learning, 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), 2022, pp. 1-8 (with Sebastian Schäfer)

• Einsatz neuronaler Netze in der Notaufnahme, Notfall + Rettungsmedizin 2022, (with Corinna Weberskirch, Patric Tralls, and Sebastian Rachuba)

• Measuring and Modeling Risk Using High-Frequency Data, in: Applied Quantitative Finance, 3rd edition, W. Härdle, C. Y.-H. Chen and L. Overbeck (eds.), Springer, Berlin, 2017, (with Wolfgang Härdle and Nikolaus Hautsch).

• Nonlinearity in Cap-and-Trade Systems: The EUA Price and its Fundamentals, Energy Economics, 2013, 40, 222 - 232 (with Benjamin Lutz and Waldemar Rotfuss).
   
• A Canonical Correlation Approach for Selecting the Number of Dynamic Factors, Oxford Bulletin of Economics and Statistics, 2013, 75 (1), 23-36 (with Jörg Breitung).
   
• Volatility Estimation based on High-Frequency Data, in: Handbook of Computational Finance, J. Duan, J.E. Gentle and W. Härdle (eds.), Springer, 2012, 335 - 369 (with Christian Pigorsch and Ivaylo Popov)
   
• Localized Realized Volatility Modelling, Journal of the American Statistical Association, 2010, 105 (492), 1376-1393 (with Ying Chen and Wolfgang K. Härdle).
   
• A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects, Journal of Econometrics, 2009, 150 (2), 151-166 (with Tim Bollerslev, Christian Pigorsch, and George Tauchen).
   
• The Volatility of Realized Volatility, Econometric Reviews, 2008, 27 (1-3), 46 - 78 (with Fulvio Corsi, Stefan Mittnik, and Christian Pigorsch).