People & Competencies

Dr. Thomas Krabichler

Contact

Dr. Thomas Krabichler
Institut IFU-FHS
Kompetenzzentrum Banking & Finance

+41 71 226 12 18
thomas.krabichler@fhsg.ch

Education

  • 2012 - 2017 Doctor of Sciences, Stochastic Finance Group, ETH Zürich
  • 2010 - 2013 Advanced Studies in Acturial Science (Actuary SAA), ETH Zürich
  • 2004 - 2009 Master of Science in Mathematics, ETH Zürich

Professional Experience

  • 2020 - present Lecturer & Quant Researcher, FHS St. Gallen
  • 2018 - 2020 Lecturer & Quant Researcher in Mathematical Finance, Lucerne University of Applied Sciences and Arts (HSLU - IFZ)
  • 2010 - 2018 Quantitative Finance & Risk Consultant, PricewaterhouseCoopers AG (PwC)
  • 2009 - 2010 Trading Desk Quant (Internship), Credit Suisse AG
  • ALM
  • Credit Risk
  • Derivatives
  • Financial Modelling
  • Hedging
  • Programming
  • Reinforcement Learning
  • Risk Quantification
  • Validation
  • Analysis
  • Analytics
  • Credit Risk Management
  • Machine Learning
  • Mathematical Finance
  • Probability Theory
  • Quantitative Modelling
  • Statistics
  • 2019 - present Deep ALM
  • 2019 - 2020 Predictive Credit Analytics with Neural Networks
  • 2018 - 2020 Reinforcement Learning for Pricing & Hedging of Derivatives

Publications and Essays

  • Krabichler, T. and Teichmann, J. (2020). A constraint-based notion of illiquidity. Preprint, arXiv:2004.12394.
  • Krabichler, T. and Teichmann, J. (2020). The Jarrow & Turnbull setting revisited. Preprint, arXiv:2004.12392.
  • Krabichler, T. (2019). Reinforcement Learning for Pricing & Hedging of Derivatives - A Simplified Showcase. IFZ Working Paper Series.
  • Krabichler, T. (2019). If only there were no liquidity constraints. IFZ Working Paper Series.
  • Krabichler, T. (2019). If only we knew the drift. IFZ Working Paper Series.
  • Krabichler, T. (2019). Künstliche Intelligenz in der Finanzbranche - eine Utopie? IFZ Retail Banking Blog.
  • Krabichler, T. (2018). Term Structure Modelling Beyond Classical Paradigms - An FX-like Approach. Dissertation.

Contributions

  • Cuchiero, C., Larsson, M. and Svalutto-Ferro, S. (2018). Polynomial jump-diffusions on the unit simplex. Annals of Applied Probability. Vol. 28, No. 4, pp. 2451-2500.
  • Golnaraghi, M. (2018). Climate Change and the Insurance Industry: Taking Action as Risk Managers and Investors. The Geneva Association.
  • Deep Replication of a Runoff Portfolio. (2020). ETH Stochastic Finance Group, Webinar.
  • New Frontiers in Quantitative Risk Management. (2019). IFZ Fintech Colloquium, Rotkreuz (CH).
  • Dynamic Financial Analyses with Reinforcement Learning. (2019). Expert meeting of an international insurance company, Switzerland (CH).
  • Machine Learning in Finance. (2019). Data Science Fundamentals, University of St. Gallen (CH).
  • Deep ALM. (2019). Minisymposium on Mathematical Finance in the age of Machine Learning, ÖMG Conference, Dornbirn (A).
  • Deep ALM. (2019). FPWZ Seminar, University of Padova (I).
  • Credit Risk Management. (2019). Board meeting of a Swiss retail bank, Switzerland (CH).
  • The Transformation of Treasury/ALM to Deliver Optimised Performance Management. (2019). Finastra Universe, Frankfurt (D).
  • Reinforcement Learning in Quant Finance: An Introduction for Non-Financial Experts. (2018). Swiss Data Alliance Expert Group Meeting, Schweizerische Mobiliar, Berne (CH).
  • A Joint Modelling Framework for Credit and Liquidity Risk. (2018). Workshop of the Freiburg-Strasbourg Research Group on Financial and Actuarial Mathematics, Freiburg Institute for Advanced Studies (D).
  • Term Structure Modelling Beyond Classical Paradigms. (2017). Doctoral Defence, ETH Zürich (CH).
  • The Jarrow & Turnbull Setting Revisited. (2017). 5th Imperial - ETH Workshop on Mathematical Finance, Imperial College London (UK).
  • Term Structure Modelling in the Presence of Multiple Yield Curves. (2016). Challenges in Mathematical Finance, University of Cape Town (ZA).
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