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Josef Teichmann is Professor of Mathematics at ETH Zurich. Professor Teichmann is a regular speaker at international conferences on finance and mathematics and has published extensively in his areas of research expertise.

Expertise

Professor Teichmann taps into his functional analysis, geometry, and mathematical finance background to develop machine learning technology further for the financial industry. In one project conducted jointly with investment bankers, he solves generic hedging tasks by relying on deep learning techniques in an entirely realistic market environment—in the presence of market frictions and trading constraints. Other projects include solutions for calibration, simulation, or prediction tasks using deep learning technology or reservoir computing. Future projects will continue his work on the fascinating interplay between mathematical finance, stochastic dynamics, and machine learning. Professor Teichmann actively participates in SFI Knowledge Exchange activities on machine learning and artificial intelligence applied to banking and finance.

Expertise Fields

  • Financial Markets
    • Financial Forecasting
    • Information and Market Efficiency
  • Portfolio Management and Asset Classes
    • Commodities
    • Equities
    • Fixed Income
    • Foreign Exchange
    • Options and Other Derivatives
    • Portfolio Management
  • Corporate Finance and Governance
    • Financial Risk and Risk Management
  • Frontier Topics
    • Big Data and Fintech
    • Operations Research and Decision Theory

Current Publications:

N°24-79: Randomized Signature Methods in Optimal Portfolio Selection

Nº 21-88: Deep Hedging under Rough Volatility

Nº 19-80: Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning

Consistent Yield Curve Prediction

A Convergence Result for the Emery Topology and a Variant of the Proof of the Fundamental Theorem of Asset Pricing

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