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Johannes Wiesel

Assistant Professor

Address:
7206 Wean Hall
Department of Mathematical Sciences
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5000 Forbes Avenue
Pittsburgh, PA 15213

412-268-2545

Email

Johannes Wiesel

Education

Ph.D., University of Oxford

Prior Appointment:

  • Assistant Professor in the at Columbia University, 2020-2023

Research

My research focuses on mathematical finance and mathematical statistics with a special emphasis on optimal transport of stochastic processes. I am particularly interested in the robust approach to mathematical finance, which does not start with an a priori model but rather with the information available in the markets. My goal is to establish new connections to the theory of optimal transport on the one hand and robust statistics as well as machine learning on the other, in order to develop a universal toolbox for the implementation of robust and time-consistent trading strategies and risk assessment.

Select Publications

J. Wiesel and E. Zhang. An optimal transport based characterization of convex order, 2023+. Depend. Model. (forthcoming). Available at .

D. Bartl and J. Wiesel. Sensitivity of multi-period optimization problems in adapted Wasserstein distance, 2023+. SIAM J. Financial Math. (forthcoming). Available at .

J. Wiesel. Continuity of the martingale optimal transport problem on the real line, 2023+. Ann. Appl. Probab. (forthcoming). Available at .

M. Nutz and J. Wiesel. Stability of Schrödinger Potentials and Convergence of Sinkhorn's Algorithm, 2022+. Ann. Probab. (forthcoming). Available at .

M. Nutz and J. Wiesel. Entropic Optimal Transport: Convergence of Potentials, 2022. . Available at .

J. Wiesel. Measuring association with Wasserstein distances, 2022. . Available at .

J. Backhoff, D. Bartl, M. Beiglböck, J. Wiesel. Estimating processes in adapted Wasserstein distance, 2022. . Available at .

D. Bartl, S. Drapeau, J. Obloj, J. Wiesel. Sensitivity analysis of Wasserstein distributionally robust optimisation problems, 2021. . Available at .

J. Obloj and J. Wiesel. Robust estimation of superhedging prices, 2021. . Available at .