Publikationen

• Uta Pigorsch and Sebastian Schäfer (2024): Reversal of Monday returns: It is the afternoon that matters, Finance Research Letters, DOI: 10.1016/j.frl.2024.105525

• Uta Pigorsch and Sebastian Schäfer (2023): Anxiety in Returns, Journal of Behavioral Finance, DOI: 10.2139/ssrn.4239765

• Marc Sabek and Uta Pigorsch (2023): Local Assortativity in Weighted and Directed Complex Networks, Physica A: Statistical Mechanics and its Applications, Volume 630, 2023, 129231, DOI: 10.1016/j.physa.2023.129231

• Uta Pigorsch and Marc Sabek (2022): Assortative Mixing in Weighted Directed Networks, Physica A: Statistical Mechanics and its Applications, Volume 604, 2022, 127850, DOI: 10.1016/j.physa.2022.127850

• Uta Pigorsch and Sebastian Schäfer (2022): High-Dimensional Stock Portfolio Trading with Deep Reinforcement Learning, 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), Helsinki, Finland, pp. 1-8, DOI: 10.1109/CIFEr52523.2022.9776121

• Corinna Weberskirch, Uta Pigorsch, Patric Tralls, Sebastian Rachuba (2022): Einsatz neuronaler Netze in der Notaufnahme, Notfall + Rettungsmedizin, DOI: 10.1007/s10049-021-00974-x

• Wolfgang Härdle, Nikolaus Hautsch & Uta Pigorsch (2017): 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, DOI: 10.1007/978-3-662-54486-0_14

• Benjamin Lutz, Uta Pigorsch, Waldemar Rotfuss (2013): Nonlinearity in Cap-and-Trade Systems: The EUA Price and its Fundamentals, Energy Economics, 40, 222 - 232, DOI: 10.1016/j.eneco.2013.05.022

• Jörg Breitung & Uta Pigorsch (2013): A Canonical Correlation Approach for Selecting the Number of Dynamic Factors, Oxford Bulletin of Economics and Statistics, 75 (1), 23-36, DOI: 10.1111/obes.12003

• Christian Pigorsch, Uta Pigorsch & Ivaylo Popov (2012): Volatility Estimation based on High-Frequency Data, in: Handbook of Computational Finance, J. Duan, J.E. Gentle and W. Härdle (eds.), Springer,  335 - 369, DOI: 10.1007/978-3-642-17254-0_13

• Ying Chen, Wolfgang K. Härdle & Uta Pigorsch (2010): Localized Realized Volatility Modelling, Journal of the American Statistical Association, 105 (492), 1376-1393, DOI: 10.1198/jasa.2010.ap09039

•  Tim Bollerslev, Christian Pigorsch, George Tauchen & Uta Pigorsch (2009): A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects, Journal of Econometrics, 150 (2), 151-166, DOI: 10.1016/j.jeconom.2008.12.001

• Fulvio Corsi, Stefan Mittnik, Christian Pigorsch & Uta Pigorsch (2008): The Volatility of Realized Volatility, Econometric Reviews, 27 (1-3), 46 - 78, DOI: 10.1080/07474930701853616

• Arminger, G., Bommert, K., Werner, T. (2001): Innovationen und Beschäftigung in den Multimedia-Dienstleistungen, in Keil-Slawik, R. (Hrsg.), Digitale Medien und gesellschaftliche Entwicklung, Waxmann Verlag (Münster), S. 101-114
   
• Bommert, K. (1999): Das multinomiale Probitmodell (Dissertation), Eul-Verlag (Lohmar/Köln)
   
• Arminger, G., Bommert, K., Werner, T. (1999): Innovation und Beschäftigung in den Multimedia-Dienstleistungen, Bergische Universität Wuppertal, Fach Statistik. In: Herausforderungen des internationalen Wettbewerbs, Hans-Jörg Bullinger (Hrsg.), Gabler-Verlag (Wiesbaden), S. 388-405
   
• Arminger, G., Bommert, K., Bonne, T. (1996): Einfluß der Witterung auf das Unfallgeschehen im Straßenverkehr Allgemeines Statistisches Archiv 80, S. 181-206
   
• Arminger, G., Bommert, K., Bonne, T. (1995): Einfluß der Witterung auf das Unfallgeschehen, Forschungsbericht der Bundesanstalt für Straßenwesen, Bergisch Gladbach, 194 Seiten