Dr. Malte Kurz

Research Interests

• Machine Learning
• Causal Inference
• High-Dimensional Statistics
• (Financial) Econometrics
• Dependence Modelling & Copulas

Publications

• Spanhel, F., und Kurz, M. S. (2019). Simplified vine copula models: Approximations based on the simplifying assumption. Electronic Journal of Statistics 13 (1), 1254-1291.
• Kurz, M. S. (2018). A note on low-dimensional Kalman smoothers for systems with lagged states in the measurement equation. Economics Letters 168, 42-45.
• Spanhel, F., und Kurz, M. S. (2016). The partial copula: Properties and associated dependence measures. Statistics & Probability Letters 119, 76-83.

Working Papers

• Kurz, M. S. (2021). Distributed Double Machine Learning with a Serverless Architecture. ArXiv Working Paper: https://arxiv.org/abs/2101.04025.
• Kurz, M. S., und Mittnik, S. (2018). Risk Assessment and Spurious Seasonality. Center for Quantitative Risk Analysis (CEQURA) Working Paper Number 19, https://ssrn.com/abstract=2990772.
• Kurz, M. S., und Spanhel, F. (2018). Testing the simplifying assumption in high-dimensional vine copulas. ArXiv Working Paper https://arxiv.org/abs/1706.02338.

Software

• Python-Paket DoubleML: "Double Machine Learning in Python", verfügbar im Python Package Index (PyPI) https://pypi.org/project/DoubleML, Entwicklung auf GitHub https://github.com/DoubleML/doubleml-for-py, Dokumentation und User Guide https://docs.doubleml.org, mit P. Bach, V. Chernozhukov und M. Spindler.
• R-Paket DoubleML: "Double Machine Learning in R", verfügbar auf CRAN https://cran.r-project.org/package=DoubleML, Entwicklung auf GitHub https://github.com/DoubleML/doubleml-for-r, Dokumentation und User Guide https://docs.doubleml.org, mit P. Bach, V. Chernozhukov und M. Spindler.
• Python package DoubleML-Serverless "Distributed Double Machine Learning with a Serverless Architecture", verfügbar auf GitHub https://github.com/DoubleML/doubleml-serverless.
• R-Paket pacotest: "Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas", verfügbar auf CRAN https://cran.r-project.org/package=pacotest und Entwicklung auf GitHub https://github.com/MalteKurz/pacotest.
• MATLAB Toolbox SSMwLS: State Space Model with Lagged State (SSMwLS) in the measurement equation, verfügbar auf GitHub https://github.com/MalteKurz/SSMwLS.
• MATLAB Toolbox VineCopulaMatlab: "A MATLAB toolbox for vine copulas based on C++", verfügbar auf GitHub https://github.com/MalteKurz/VineCopulaMatlab.
• C++ Bibliothek {VineCopulaCPP}: "A C++ library for vine copulas", verfügbar auf GitHub https://github.com/MalteKurz/VineCopulaCPP. 

Education