Prof. Dr. Matthias Scherer


Mathematical finance



Academic Career and Research Areas

Prof. Scherer’s (b. 1979) research area is mathematical finance, actuarial science, probability, and statistics. His work aims at the valuation of financial products and the quantification of their risks. He is well known for the modelling of dependency structures, the construction of simulation algorithms for copulas, and the analysis of credit portfolios. Scherer is a member of the board of the “Deutsche Gesellschaft für Versicherungs- und Finanzmathematik”, speaker of the graduate school ISAM, and serves different scientific journals. He supports the exchange between academia and practice in various activities.

Prof. Scherer studied business mathematics at the University of Ulm and obtained his Master of Science in mathematics at Syracuse University (USA). He went on to do his doctorate in structural credit-risk models at the University of Ulm (2007). Since 2010, he has been professor of mathematical finance at TUM.


  • ISAM Supervisory Award, 2nd place, International School of Applied Mathematics at TUM (2018)
  • Teaching Award „Golden Circle“, Mathematics Departmental Student Council at TUM (2010, 2012, 2017)
  • Gauss Award, 2nd place, of the German Association of Actuards and the German Society for Insurance and Financial Mathematics (2011)
  • Südwestmetall award for young researchers (2007)

Mai JF, Scherer M: Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications. 2nd edition. New Jersey et al: World Scientific, 2017.

Mai JF, Scherer M: "Characterization of extendible distributions with exponential minima via processes that are infinitely divisible with respect to time". Extremes. 2014; 17 (1): 77-95.

Bannör KF, Scherer M: "Capturing parameter uncertainty with convex risk measures". European Actuarial Journal. 2013; 3 (1): 97-132.

Mai JF, Scherer M.: "H-extendible copulas". Journal of Multivariate Analysis. 2012; 110: 151-160.

Hofert M, Scherer M: “CDO pricing with nested Archimedean copulas”. Quantitative Finance. 2011;  11(5): 775-787.