Dr. Thomas Krabichler

Curriculum Vitae

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

Competence profile

• ALM
• Credit Risk
• Derivatives
• Financial Modelling
• Hedging
• Programming
• Reinforcement Learning
• Risk Quantification
• Validation

Teaching activity

• Analysis
• Analytics
• Credit Risk Management
• Machine Learning
• Mathematical Finance
• Probability Theory
• Quantitative Modelling
• Statistics

Projects

• 2019 - present Deep ALM
• 2019 - 2020 Predictive Credit Analytics with Neural Networks
• 2018 - 2020 Reinforcement Learning for Pricing & Hedging of Derivatives

Presentation

• Predictive Technologies for Better Business Lending. (2020). Professional Risk Managers' International Association (PRMIA), Webinar.
• 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).

Publications and Essays

• Krabichler, T. and Teichmann, J. (2020). Deep Replication of a Runoff Portfolio. Preprint, arXiv:2009.05034.
• 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.