Persönlicher Status und Werkzeuge

Prof. Dr. Claudia Klüppelberg



Contact Details

Business card at TUMonline

Academic Career and Research Areas

The research interests of Professor Klüppelberg combine various disciplines of applied probability theory and statistics with applications in the area of biological, economic and technical risks. Her fundamental research concentrates on advancing the modeling and extension of the spectrum of methods for risk analysis and risk measurement, but she is also interested in real-world problems and cooperation with industry.  
After studying mathematics and receiving her doctorate (1987) at the University of Mannheim, Prof. Klüppelberg completed her lecturer qualification at the Swiss Federal Institute of Technology Zurich (1993). Before becoming full professor of mathematical statistics at TUM, she was a professor of applied statistics in Mainz until 1997. She headed up the IAS focus group Risk Analysis and Stochastic Modeling at TUM from 2008 to 2011. Along with more than 100 publications in scientific journals and books, she is the editor of the Springer Finance series of books and the Springer Lecture Notes in Mathematics subseries Lévy Matters. She is an Elected Fellow of the Institute of Mathematical Statistics.


  • Olga Taussky-Pauli Fellow am Wolfgang Pauli Institut (2009/10)
  • IMS Medaillon Lecture  (2009)
  • PRMIA New Frontiers in Risk Management Award (2007)
  • Bundesverdienstkreuz  (2001)

Key Publications (all publications)

Delong L, Klüppelberg C: “Optimal investment and consumption in a Black-Scholes market with Lévy-driven stochastic coefficients.” Ann. Appl. Prob. 2008; 18(3): 879-908.


Klüppelberg C, Lindner A, Maller R: “A continuous time GARCH process driven by a Lévy process: stationarity and second order behavior.” J. Appl. Probab. 2004; 41: 601-622.


Embrechts P, Klüppelberg C, Mikosch T: Modelling Extremal Events for Insurance and Finance. Berlin: Springer, 1997.


Mikosch T, Gadrich T, Klüppelberg C, Adler RJ: “Parameter estimation for ARMA models with infinite variance innovations.” Ann. Statist. 1995; 23, 305-326.