M.Sc. Sven Pappert

• seit Juli 2020: Wissenschaftlicher Mitarbeiter und Promovierender, TU Dortmund
• Juli/August 2025: Forschungsaufenthalt an der University of British Columbia (UBC), Vancouver, Kanada bei Prof. Harry Joe
• 2018-2020: Wissenschaftliche Hilfskraft am Lehrstuhl für Kern- und Teilchenphysik, Ruhr-Universität Bochum
• 2014-2020: B.Sc. und M.Sc. in Physik mit Schwerpunkt theoretische Physik, Ruhr-Universität Bochum
  Masterarbeit: Perturbative Calculation of the Fluctuation Determinant in Burgers Turbulence

Veröffentlichungen:

• Berrisch, J., Pappert , S., Ziel, F. und Arsova, A. (2023). Modeling volatility and dependence of European carbon and energy prices. Finance Research Letters, Volume 52. Link, Preprint.
• Pappert , S. and Arsova, A. (2022). Forecasting Natural Gas Prices with Spatio-Temporal Copula-Based Time Series Models. International Conference on Time Series and Forecasting (pp. 221-236). Cham: Springer Nature Switzerland. Link, Preprint.

Preprints und Working Papers:

• Lebedev, A., Das, A., Pappert, S., & Schlüter, S. (2025). Analyzing Uncertainty Quantification in Statistical and Deep Learning Models for Probabilistic Electricity Price Forecasting. arXiv preprint arXiv:2509.19417. Preprint.
• Pappert, S. (2025). The Field Equations of Penalized non-Parametric Regression. arXiv preprint arXiv:2503.14763.  Preprint.
• Pappert, S. (2024). Moving Aggregate Modified Autoregressive Copula-Based Time Series Models (MAGMAR-Copulas) Without Markov Restriction. arXiv preprint arXiv:2402.01491. Preprint.

• Wahrscheinlichkeitstheorie (WiSe 2024/25)
• Time Series Analysis (SoSe 2024)
• Stochastische Prozesse (WiSe 2023/24)
• Asymptotic Theory (WiSe 2023/24)
• Case Studies (SoSe 2023)
• Asymptotic Theory (WiSe 2022/23)
• Statistical Theory (WiSe 2022/23)
• Time Series Analysis (SoSe 2022)
• Schätzen und Testen I (WiSe 2021/22)
• Wahrscheinlichkeitsrechnung (SoSe 2021)
• Introductory Case Studies (WiSe 2020/21)

• "Copula-based Non-Gaussian Time Series Models" UBC Statistics Seminar (2025), Vancouver, Kanada.
• "Moving Aggregate Modified Autoregressive Copula-Based Time Series Models (MAGMAR-Copulas)" ISF (2024), Dijon, Frankreich.
• "Moving Aggregate Modified Autoregressive Copula-Based Time Series Models (MAGMAR-copulas)" IAAE (2024), Thessaloniki, Griechenland.
• "Neural Network Assisted Probabilistic Forecast Reconciliation" DoDaS-Nachwuchskolloquium (2024), Dortmund.
• "Moving Aggregate modified Autoregressive Copula-Based Time Series without Markov Restriction" Promotionskolloquium (2023), Dortmund.
• " Modeling volatility and dependence of European carbon and energy prices" Statistische Woche (2023), Dortmund.
• "Introducing a Moving Aggregate to Copula-based Time Series Models to Allow for Infinite Autoregressive order" Nachwuchsworkshop der statistischen Woche (2023), Dortmund.
• "Moving Aggregate Modified Autoregressive Copula-Based Time Series Models (MAGMAR-copulas)" 18. Doktorand:innentreffen der Stochastik (2023), Heidelberg.
• "Introducing a Moving Aggregate to Copula-based Time Series Models to allow for Infinite Autoregressive Order" European Meeting of Statisticians (2023), Warschau.
• "Forecasting natural gas prices with spatiotemporal copula-based time series models", International Conference on Computational and Financial Econometrics (2022), London.
• "Modeling Volatility and Dependence of European Carbon and Energy Prices", International Ruhr Energy Conference (2022), Essen.
• "Forecasting Natural Gas Prices with Spatio-Temporal Copulas", International conference on Time Series and Forecasting (2022), Gran Canaria.
• "Modeling Volatility and Dependence of European Carbon and Energy Prices", Workshop on Carbon Finance (2022), Hagen (virtual).
• "Modeling and Forecasting Gas Prices with Copula Models", UA RuhrMetrics Seminar (2022), Essen (virtual).
• "Modellierung und Vorhersage von Gas Preisen mit Copula-Modellen",  Promotionskolloquium (2021), Dortmund.