Publikationen

Prof. Dr. Uta Pigorsch:

• Assortative Mixing in Weighted Directed Networks, Physica A: Statistical Mechanics and its Applications, Volume 604, 2022, 127850 (mit 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 (mit Sebastian Schäfer)

• Einsatz neuronaler Netze in der Notaufnahme, Notfall + Rettungsmedizin 2022, (mit Corinna Weberskirch, Patric Tralls und 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, (mit Wolfgang Härdle und Nikolaus Hautsch).

• Nonlinearity in Cap-and-Trade Systems: The EUA Price and its Fundamentals, Energy Economics, 2013, 40, 222 - 232 (mit Benjamin Lutz und Waldemar Rotfuss).
   
• A Canonical Correlation Approach for Selecting the Number of Dynamic Factors, Oxford Bulletin of Economics and Statistics, 2013, 75 (1), 23-36 (mit 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 (mit Christian Pigorsch und Ivaylo Popov)
   
• Localized Realized Volatility Modelling, Journal of the American Statistical Association, 2010, 105 (492), 1376-1393 (mit Ying Chen und 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 (mit Tim Bollerslev, Christian Pigorsch und George Tauchen).
   
• The Volatility of Realized Volatility, Econometric Reviews, 2008, 27 (1-3), 46 - 78 (mit Fulvio Corsi, Stefan Mittnik und Christian Pigorsch).