Malte Kurz

Malte Kurz is a researcher affiliated with the University of Hamburg Business School, specifically within the Department of Statistics. His primary role was as a Researcher under the Professorship of Statistics with Applications in Business Administration. He holds a PhD in Statistics from Ludwig-Maximilians-Universität München (2018), an M.Sc. in Statistics from LMU Munich (2013), and a B.Sc. in Mathematical Finance from Universität Konstanz (2011).

His research interests focus on Machine Learning, Causal Inference, High-Dimensional Statistics, Financial Econometrics, and Dependence Modelling & Copulas. He has contributed to advancements in vine copula theory, distributed machine learning frameworks, and state space models.

Key publications include works on vine copula simplifications (2019), low-dimensional Kalman smoothers (2018), and distributed double machine learning architectures (2021). He has developed influential software tools like the pacotest R package for copula hypothesis testing and the DoubleML framework for Python/R.

Kurz has also contributed to open-source projects such as the VineCopulaMatlab toolbox and the SSMwLS MATLAB package for state space modeling. His work bridges statistical theory and computational implementation, with applications in finance and econometrics.