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Thorsten Schmidt

Thorsten Schmidt_klein

Thorsten Schmidt became professor for mathematical stochastics at University of Freiburg in the summer 2015. He is the successor of Ernst Eberlein.

His research combines financial mathematics with the area of stochastic processes and statistics. Currently, he also developed some interest in machine learning. In his career he met interesting problems, both from Statistics and Financial Mathematics which inspire for deeper mathematical understanding by their surprising complexity. In Freiburg he and his young research team are working on tackling these challenges with improved mathematical model and targeting various applied areas where this can be useful. Besides Finance, this includes medicine, roboting and in general all areas where stochastic modelling is used.

 

Some videos (most of them in German, unfortunately)

 

Awards

IDA Award Finance from a practical perspective, together with Eva Lütkebohmert-Holtz (2015)

FRIAS-USIAS Research Fellow: Linking Finance and Insurance, 2017/2018

IDA Award Machine Learning and Artificial Intelligence in Freiburg with Philipp Harms and 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)

Teaching

In the past semesters, Prof. Schmidt taught for example (more see on the German page)

Research areas

  • Financial mathematics in general
  • Credit risk, term-structure models (including multiple yield curves, energy markets etc.)
  • Pricing and hedging of derivatives
  • Affine and polynomial processes
  • Statistics of stochastic processes
  • Nonlinear filtering 
  • Model risk, systemic risk
  • Insurance mathematics
  • Machine Learning

  

Adress: 

Abteilung für Mathematische Stochastik 
Albert-Ludwigs University of Freiburg 
Ernst-Zermelo-Straße 1
Zimmer 247
D - 79104 Freiburg

Tel: +49-761-203-5668
Fax: +49-761-203-5661 
E-Mail: thorsten[dot]schmidt[at]stochastik[dot]uni-freiburg[dot]de

 

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