JProf. Dr. Antonia Arsova

• since October 2019: Junior Professor in Econometrics, TU Dortmund University
• 2012-2019: PhD in Econometrics (Dr. rer. pol), Leuphana University Lüneburg
• 2012-2018: Research Assistant for the DFG-funded project "Likelihood-Based Panel Cointegration Methodology and Its Applications in Macroeconomics and Financial Market Analysis", Leuphana University Lüneburg
• 2009-2012: Credit Risk Analyst, Experian Decision Analytics
• 2008-2011: M.Sc. in Probability Theory and Statistics, Sofia University "St. Kliment Ohridski"
• 2004-2008: B.Sc. in Applied Mathematics, Sofia University "St. Kliment Ohridski"

Project manager of subproject C02: "Renewable energy forecasts and their impact on electricity prices"  in the course of DFG TRR 391 "Spatio-temporal Statistics for the Transition of Energy and Transport"

ORCiD

• Berrisch, J., Pappert, S., Ziel, F. and Arsova, A. (2022). Modeling volatility and dependence of European carbon and energy prices. Finance Research Letters 52, 103503. DOI.
• Pappert, S., and Arsova, A. (2022). Forecasting Natural Gas Prices with Spatio-Temporal Copula-Based Time Series Models. In International Conference on Time Series and Forecasting (pp. 221-236). Cham: Springer Nature Switzerland. DOI
• Arsova, A. (2021). Exchange rate pass-through to import prices in Europe: a panel cointegration approach. Empirical Economics 61, 61-100. DOI.
• Arsova, A. and Karaman Örsal, D. D. (2020). A panel cointegrating rank test with structural breaks and cross-sectional dependence. Econometrics and Statistics 17, 107-129. DOI.
• Arsova, A. and Karaman Örsal, D. D. (2020). Intersection tests for the cointegrating rank in dependent panel data. Communications in Statistics - Simulation and Computation 49, 918-941. DOI.
• Arsova, A. and Karaman Örsal, D. D. (2018). Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence. Econometric Reviews 37, 1033-1050. DOI.
• Karaman Örsal, D. D. and Arsova, A. (2017). Meta-analytic cointegrating rank tests for dependent panels. Econometrics and Statistics 2, 61-72. DOI.

• Arsova, A. (2019). Exchange rate pass-through to import prices in Europe: A panel cointegration approach. Working Paper 384, Working Paper Series in Economics, Leuphana Universität Lüneburg. Link.
• Arsova, A. and Karaman Örsal, D. D. (2016). A panel cointegration rank test with structural breaks and cross-sectional dependence. In Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel: Session: Time Series Econometrics, No. D01-V3, Deutsche Zentralbibliothek für Wirtschaftswissenschaften (ZBW). Link.
• Arsova A. and Karaman Örsal D. D. (2016). An intersection test for the cointegrating rank in dependent panel data. Working Paper 357, Working Paper Series in Economics, Leuphana Universität Lüneburg. Link.
• Karaman Örsal, D. D. and Arsova A. (2015). Meta-analytic cointegrating rank tests for dependent panels. Working Paper 349, Working Paper Series in Economics, Leuphana Universität Lüneburg. Link.
• Arsova, A. and Karaman Örsal, D. D. (2013). Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence. Working Paper 280, Working Paper Series in Economics, Leuphana Universität Lüneburg. Link.

• Econometric Forecasting (with Matei Demetrescu) (WiSe 2025/26)
• Econometrics (SuSe 2025)
• Unit Root and Cointegration Analysis (WiSe 2024/25)
• Time Series Analysis (SuSe 2024)
• Unit Root and Cointegration Analysis (SuSe 2023)
• Time Series Analysis (SuSe 2022)
• Introductory Case Studies (WiSe 2020/21)
• Econometrics (SuSe 2020)
• Time Series Analysis (in German) (A. Arsova, R. Schüssler) (WiSe 2019/20)

• Predicting Wind Power: A Probabilistic Forecasting Approach with Generalised Additive Models for Location, Scale and Shape (MSc Econometrics, 2025)
• Implementing Continuous Distributions in the Rolch Package in Python (MSc Data Science, 2025)
• Unsupervised temperature sensor anomaly detection for fault diagnosis in heating appliances (MSc Data Science, 2024)
• Reject Inference mit Semi-Supervised Clustering – Eine empirische Fallstudie mit einer deutschen Bank (MSc Statistik, 2024)
• Comparison of short-term probabilistic and pointwise electric vehicle load forecasting at electric charging stations in Denmark using a deep learning approach (MSc Data Science, 2024)
• Volatilitätsmodellierung und Prognose des kurzfristigen Zinses: Eine statistische Analyse (BSc Statistik, 2023)
• The Gaussian copula assumption of the inverse normal method for dependent cointegration test statistics (BSc Statistik, 2021)