Publications

Picture taken @ Gardens by the Bay, Singapore

Research Interest

My research lies at the intersection of mathematical finance, stochastic optimization, and machine learning, with particular emphasis on:

Robust and Model-Free Finance: model uncertainty, distributionally robust optimization, and martingale optimal transport
Stochastic Control and Optimization: stochastic optimal control, dynamic programming, and robust decision-making
Machine Learning for Finance: deep neural networks and reinforcement learning
Financial Applications: market making, credit risk, and concentration risk

Preprints

[25] Y. Chen, H. Nguyen, J. Sester, H. H. Tran, Y.Zhang:Robustness in Sequential Decision Making under Evolving Uncertainty: Evidence from High-Frequency Market Making. (arxiv)
[24] C. I Lu, J. Sester, A Zhang:Distributionally Robust Deep Q-Learning (arxiv, Code)
[23] J. Sester, C. Decker:Q-Learning under Finite Model Uncertainty (arxiv, Code)

Publications

[22] J.Sester, H.Xu:Fast catastrophe bond valuation with neural-network surrogates (arxiv, Code)Finance Research Letters, 109, 110492, 2026
[21] Z. Chen, Y. Qi, S.Que, J. Sester, X. Zhang:Empirical Analysis of the Model-Free Valuation Approach: Hedging Gaps, Conservatism, and Trading Opportunities (arxiv, Code)Quantitative Finance, (Forthcoming)
[20] A. Neufeld, J. Sester:Non-concave stochastic optimal control in finite discrete time under model uncertainty (arxiv, Code)Mathematical Finance, 36(2), pp. 271-308, 2026
[19] C. I Lu, J. Sester:Generative modelling of financial time series with structured noise and MMD-based signature learning (arxiv, Code)Statistics & Risk Modeling, 42, (3-4), pp.91-122, 2025
[18] E. Lütkebohmert, J. Sester: Measuring Name Concentrations through Deep Learning (arxiv, Code) International Review of Financial Analysis, 107, 104598, 2025
[17] E. Lütkebohmert, J. Sester, H. Shen: Name Concentration Risk in Multilateral Development Banks' Portfolios: Measurement and Capital Adequacy Implications   (arxiv, Code) Global Finance Journal, 67, 101154, 2025
[16] A. Neufeld, J. Sester:Bounding the Difference between the Values of Robust and Non-Robust Markov Decision Problems (arxiv, Code)Journal of Applied Probability, 62(2), pp. 558 - 571 , 2025
[15] A. Neufeld, J. Sester:Neural networks can detect model-free static arbitrage strategies (arxiv, Code)Applied Mathematics and Optimization, 90(2), 41, 2024
[14] A. Neufeld, J. Sester:Robust Q-learning algorithm for Markov decision processes under Wasserstein uncertainty (arxiv, Code)Automatica, 168, 111825, 2024
[13] J. Sester:A multi-marginal c-convex duality theorem for martingale optimal transport (arxiv, Code)Statistics and Probability Letters, 210, 110112 , 2024
[12] A. Neufeld, J. Sester, D. Yin:Detecting data-driven robust statistical arbitrage strategies with deep neural networks (arxiv, Code)SIAM Journal on Financial Mathematics, 15(2), pp. 436-472, 2024
[11] J.Ansari, E. Lütkebohmert, A. Neufeld, J. Sester:Improved robust price bounds for multi-asset derivatives under market-implied dependence information (arxiv, Code)Finance and Stochastics, 28, pp. 911–964, 2024
[10] J. Sester:On intermediate marginals in martingale optimal transportation (arxiv)Mathematics and Financial Economics, 17(4), pp. 615 - 654, 2023
[9] A. Neufeld, J. Sester, M. Sikic:Markov decision processes under model uncertainty (arxiv, Code )Mathematical Finance, 33(3), pp. 618-665, 2023
[8] A. Neufeld, J. Sester:A deep learning approach to data-driven model-free pricing and to martingale optimal transport (arxiv, Code, Video of Talk at German Probability Days)IEEE Transactions on Information Theory, 69(5), pp. 3172-3189, 2023
[7] E. Lütkebohmert, T. Schmidt, J. Sester:Robust deep hedging (arxiv, Code )Quantitative Finance, 22(8), pp. 1465-1480, 2022
[6] A. Neufeld, J. Sester:Model-free price bounds under dynamic option trading (arxiv, Code )SIAM Journal on Financial Mathematics, 12(4), pp. 1307–1339, 2021
[5] A. Neufeld, J. Sester:On the stability of the martingale optimal transport problem: A set-valued map approach (arxiv)Statistics and Probability Letters, 176, 109131, 2021
[4] E. Lütkebohmert, J. Sester:Robust statistical arbitrage strategies (SSRN, Code)Quantitative Finance, 21(3), pp. 379-402, 2021
[3] J. Sester:Robust bounds for derivative prices in Markovian models (SSRN)International Journal of Theoretical and Applied Finance, 23(3), 2050015, 2020.
[2] E. Lütkebohmert, J. Sester:Tightening robust price bounds for exotic derivatives (SSRN)Quantitative Finance, 19(11), pp. 1797-1815, 2019.
[1] C. Kurtz, E. Lütkebohmert, J. Sester:Calculating capital charges for sector concentration risk (Code)Journal of Credit Risk, 14(4), IRMC 10th Anniversary Special Issue, pp. 35-67, 2018.

PhD Thesis

[0] J. Sester:On the Improvement of Robust Price BoundsPhD Thesis, Albert-Ludwigs-Universität Freiburg, 2019.

Google Scholar

A list of the publications can also be found here:

https://scholar.google.com/citations?user=s3o7oesAAAAJ&hl=en

Co-Authors

Jonathan Ansari, Zixing Chen, Ying Chen, Cécile Decker, Cornelius Kurtz, Chung I Lu, Eva Lütkebohmert, Ariel Neufeld, Hoa Nguyen, Yihan Qi, Shanlan Que, Thorsten Schmidt, Hongyi Shen, Mario Sikic, Hoang Hai Tran, Huansang Xu, Daiying Yin, Aijia Zhang, Xiao Zhang, Yijiong Zhang

Code

The companion codes for the papers are collected here: https://github.com/juliansester

Code for "Non-concave distributionally robust stochastic control in a discrete time finite horizon setting":

https://github.com/juliansester/Robust-Hedging-Finite-Horizon

Code for "Bounding the Difference between the Values of Robust and non-Robust Markov Decision Problem":

https://github.com/juliansester/MDP_Bound

Code for "Neural networks can detect model-free static arbitrage strategies":

https://github.com/juliansester/Deep-Arbitrage

Code for "A Multi-Marginal C-Convex Duality Theorem for Martingale Optimal Transport":

https://github.com/juliansester/C-Convex

Code for "Robust Q-Learning Algorithm under Wasserstein Uncertainty":

https://github.com/juliansester/Wasserstein-Q-learning

Code for "Markov Decision Processes under Model Uncertainty":

https://github.com/juliansester/Robust-Portfolio-Optimization

Code for "Improved Robust Price Bounds for Multi-Asset Derivatives Under Market-Implied Dependence Information":

https://github.com/juliansester/improved-dependence-pricing

Code for "Robust Deep Hedging":

https://github.com/juliansester/nga

Code for "A deep learning approach to data-driven model-free pricing and to martingale optimal transport " :

https://github.com/juliansester/deep_model_free_pricing

Code for "Model-free price bounds under dynamic option trading":

https://github.com/juliansester/dynamic_option_trading

Code for "Robust statistical arbitrage strategies":

https://github.com/juliansester/statistical-arbitrage

Code for "Calculating Capital Charges for Sector Concentration Risk":

https://github.com/juliansester/calculating_capital_charges

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