Seal element of the university of freiburg in the shape of a circle

Prof. Dr. Thorsten Schmidt

Mathematical Stochastics

Thorsten Schmidt

Thorsten Schmidt was appointed to the Chair of Mathematical Stochastics at the University of Freiburg for the summer semester 2015, succeeding Prof. Ernst Eberlein. From October 2017 to September 2019, Prof. Schmidt was a Research Fellow at the Freiburg Institute for Advanced Studies in a joint research group with the University of Strasbourg and USIAS on the topic Linking Finance and Insurance.

His research primarily focuses on three areas and their applications: financial and insurance mathematics, stochastic processes, and statistics. More recently, he has been working on methods of machine learning, in particular their applications in mathematical finance and with regard to the regulation of AI. 

Throughout his career, both in statistics and in mathematical finance, he has repeatedly encountered interesting questions whose surprisingly high complexity inspired researchers and spurred the development of new mathematical techniques. In Freiburg, his goal with his young team is to tackle these challenges with improved mathematical models and to apply the developed methods to a wide range of fields. Since 2024, he has been Editor-in-Chief of the journal Statistics and Risk Modeling.

CRC “Small Data”

Small Data Logo

In the Collaborative Research Center Small Data, Thorsten Schmidt is working together with Harald Binder on a medical research question that involves estimating the temporal progression of a disease, even though only a few data points are available for each patient. Methods from stochastics are combined with machine learning techniques to enable sound, nonparametric statements and error assessments.

News

Siegel der Universität Freiburg

Research fields

  • Financial Mathematics: interest rate markets, credit risk, pricing and hedging of derivative financial products, valuation under uncertainty, insurance linked to financial markets (such as pensions, unit-linked life insurance with guarantees, etc.)
  • Uncertainty: Knightian uncertainty, generalisations and applications (in particular to the scaling of forests)
  • Risk management: in particular risk measures and their estimation
  • Regulation, in particular regulation of machine learning and related fairness questions
  • Machine Learning: development of dynamic (Bayesian) methods, in particular under uncertainty and under small data.

Consultation:

Any time. Please send an email to arrange a time point for the consultation.

Prices and awards

IAS Research Fellow: Linking Finance and Insurance, 2017/2018

IDA Award Maschinelles Lernen und künstliche Intelligenz in Freiburg mit Philipp Harms und Frank Hutter (2020)

MAPFRE Research Grant Ignacio H. de Larramendi: affine processes for insurances linked to financial markets mit Raquel Gaspar (2020) 

Luis Bachelier Fellow (2021)

Plenary Speaker: QMF Sydney, 2024; Stochastics in Mathematical Finance and Physics Conference Hammamet, 2024

CV

Thorsten Schmidt is Professor for Mathematical Stochastics at University Freiburg (successor of Ernst Eberlein) and Senior Financial Engineer at MathFinance. From 2017-2019 he was fellow of the Freiburg institute of Advanced Studies (FRIAS). Prior to this he was professor for Mathematical Finance at Chemnitz University of Technology since 2008, held a replacement Professorship from Technical University Munich in 2008 and was Associate Professor at University of Leipzig from 2004 on. Besides many stays at leading universities, he was guest professor at ETH Zurich and at Université d’Evry.

His Ph.D. he obtained from University in Giessen in 2003 on credit risk. He is Associate Editor for Mathematical Finance, International Journal of Theoretical and Applied Finance and was Associate Editor for Journal of Banking and Finance and Statistical and Probability Letters. He is an elected member of the International Statistical Institute and was member of the Board of Fachgruppe Stochastik of the German Mathematical Society. 

With numerous articles in the areas of Mathematical Finance and Probability in internationally leading journals and frequent presentations on conferences around the world, he is a well-known scientist in the area of affine models, interest rates, credit risk, incomplete information, risk management, filtering, and insurance mathematics. He has a strong background in statistics and information technology and teaches probability, mathematical finance and machine learning at the university of Freiburg. 

Further Details you may found in his CV (hier als pdf).

Editorial Activities
  • Editor-in-Chief of Statistics & Risk Modeling
  • Associate Editor of Mathematical Finance
  • Associate Editor of International Journal of Theoretical and Applied Finance
  • Former Associate Editor of Journal of Banking and Finance
  • Former Associate Editor of Statistics and Probability Letters
Related Institutions

Publications

Mehrere gedruckte Artikel im Regal

See my publications and citations at google scholar 

Editor of  a special volume in Risks on “Machine Learning in Finance, Insurance and Risk Management

Some recent Preprints
  1. R. Gaspar, T. Schmidt (2025) “Insurance products with guarantees in an affine setting”, arXiv.
  2. C. Fontana, S. Pavarana, T. Schmidt (2025) “An extended CIR process with stochastic discontinuities”, arXiv.
  3. Z. Grbac, S. Pavarana, T. Schmidt, P. Tankov (2025) “Propagation of carbon price shocks through the value chain: the mean-field game of defaults”. arXiv.
Some recent Publications
  1. Niemann, L. and Schmidt, T. (2024), “A conditional version of the second fundamental theorem of asset pricing in discrete time”, Frontiers of Mathematical Finance (Open access)
  2. Fontana, C., Grbac, Z. and Schmidt, T. (2023), „Term structure modeling with overnight rates beyond stochastic continuity“, Mathematical Finance
  3. Artzner, P. , Eisele, K.-T., and Schmidt, T. (2023) „Insurance-Finance Arbitrage“, Mathematical Finance 

Teaching

Professor Schmidt schreibt eine Formel an die Tafel

In the winter semester I teach Stochastic I and Basics in Applied Mathematics.

I often teach specialise lectures in financial mathematics, machine learning and insurance mathematics. Please look at Lehre. If you are interested in a special area, you could also contact me individually. Earlier lectures include (many of them can also be taught in English):

Professor SChmidt mit den Doktoranden

Arbeitsgruppe

In der Arbeitsgruppe von Prof. Thorsten Schmidt forschen:

JProf. Dr. David Criens, Dr. Moritz Ritter, Dr. Stefan Tappe, Felix Ndonfack und Simone Padavara

zu den Themen Finanzmathematik, Stochastische Prozesse, Versicherungsmathematik, Regulierung von AI, Small Data, modernen Bayesianischen Methoden, Filtering with Neural Networks u.v.m.

Workshops

Workshops are an essential resource of exchange of ideas and therefore constitute an important part of a mathematicians life. I (co-)origanize(d) the following workshops / conferences

Third-party funds

  • ReScale Responsable and Scalable Learning for Robots Assisting Humans (Carl-Zeiss-Stiftung)
  • Insurance linked to Financial Markets: Theory & Applications (DFG)
  • Dynamische Modellierung von Unsicherheiten in der Finanzmathematik (DFG), together with Christa Cuchiero, Irene Klein and Josef Teichmann.
  • New Approaches to Defaultable Term Structure Models (DFG)
  • Impulse Control Problems and Adaptive Numerical Solution of Quasi-Variational Inequalities in Markovian Factor Models (DFG, with Prof. Dr. Roland Herzog)
  • Filtering techniques in the modeling, pricing and hedging of interest rate and credit risk (finished, DFG – with Prof. Rüdiger Frey)
     
  • Support for international scientific events: 13. Stochastik Tage Freiburg, 2018.

Participating Scientist in the GRK 597:  Analysis, Geometry and their Connection with the Natural Sciences, DFG (2000-2009)

Vorträge

  • Vortrag über Finanzmathematik und künstliche Intelligenz, April 2023 im Freiburg Seminar. Slides
  • MathFinance Flow Event (Nov. 2018): Deep Hedging – Vortrag über aktuelle Forschungsergebnisse in der Finanzmathematik mit Deep Neural Networks.
  • Ein Vortrag von R. Wardenga über unsere gemeinsame Arbeit über affine processes with stochastic discontinuities, Lisbon 
  • Unbiased Estimation of Risk: Mitgliederversammlung der Schweizer Aktuarsvereinigung, Lugano 2017. Slides 
  • 16th Winter school on Mathematical Finance, Jan 2017, Lunteren, A new perspective on multiple yield curve models.
  • Bachelier Colloquium Jan 2017, Metabief. On a general approach to dynamical term structures. Slides.  
  • Paris Bachelier Seminar, Nov 2016, Institut Henri Poincaré, A new perspective on multiple yield curve models.
  • 7th General AMaMeF and Swissquote Conference, Sep 2015, EPFL Lausanne.Term Structure Modeling beyond the intensity paradigm.

Videos

Künstliche Intelligenz und Machine Learning (YouTube, von Thorsten Schmidt)

Deep Learning ist in aller Mund und in der Tat eine erstaunliche Technik mit der man unglaubliche Sachen machen kann. Und das auch noch mit wenigen Zeilen Code !

  • Was sind die Grundlagen und Hintergründe von maschinellem Lernen ? 
  • Wie kann man einem Computer beibringen handgeschrieben Ziffern besser zu erkennen als jeder Mensch und was hat das auch noch mit Mathematik zu tun ?

Dieses Video gibt einen kurzen Einblick in künstliche Intelligenz und versucht ein bisschen unter die Haube dieser spannenden Technologie zu schauen. 

Der Code ist auf Google Colab verfügbar. 

Formel Withboard
UB Universität Freiburg

Workshop Advances in Mathematical Finance

From May 21-23, 2025 this workshop will take place in Freiburg in honor of Ernst Eberleins’ birthday.