Robust risk aggregation with neural networks
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DOI: 10.1111/mafi.12280
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- Aude Geneway & Gabriel Peyré & Marco Cuturi, 2017. "Learning Generative Models with Sinkhorn Divergences," Working Papers 2017-83, Center for Research in Economics and Statistics.
- NESTEROV, Yurii, 2012. "Efficiency of coordinate descent methods on huge-scale optimization problems," LIDAM Reprints CORE 2511, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019.
"Choosing expected shortfall over VaR in Basel III using stochastic dominance,"
International Review of Economics & Finance, Elsevier, vol. 60(C), pages 95-113.
- Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michel McAleer & Teodosio Pérez-Amaral, 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Tinbergen Institute Discussion Papers 15-133/III, Tinbergen Institute.
- Chang, C-L. & Jiménez-Martín, J.A. & Maasoumi, E. & McAleer, M.J., 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Econometric Institute Research Papers EI2015-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Paul Embrechts & Bin Wang & Ruodu Wang, 2015. "Aggregation-robustness and model uncertainty of regulatory risk measures," Finance and Stochastics, Springer, vol. 19(4), pages 763-790, October.
- Carole Bernard & Ludger Rüschendorf & Steven Vanduffel & Ruodu Wang, 2017. "Risk bounds for factor models," Finance and Stochastics, Springer, vol. 21(3), pages 631-659, July.
- Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
- Daniel Bartl & Samuel Drapeau & Ludovic Tangpi, 2017. "Computational aspects of robust optimized certainty equivalents and option pricing," Papers 1706.10186, arXiv.org, revised Mar 2019.
- Paul Embrechts & Giovanni Puccetti, 2006. "Bounds for Functions of Dependent Risks," Finance and Stochastics, Springer, vol. 10(3), pages 341-352, September.
- Georg Pflug & David Wozabal, 2007. "Ambiguity in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 435-442.
- Jose Blanchet & Karthyek Murthy, 2019. "Quantifying Distributional Model Risk via Optimal Transport," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 565-600, May.
- Stephan Eckstein & Michael Kupper, 2018. "Computation of optimal transport and related hedging problems via penalization and neural networks," Papers 1802.08539, arXiv.org, revised Jan 2019.
Citations
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Cited by:
- Michael Kupper & Max Nendel & Alessandro Sgarabottolo, 2023. "Risk measures based on weak optimal transport," Papers 2312.05973, arXiv.org.
- Max Nendel & Alessandro Sgarabottolo, 2022. "A parametric approach to the estimation of convex risk functionals based on Wasserstein distance," Papers 2210.14340, arXiv.org, revised Aug 2024.
- Ariel Neufeld & Matthew Ng Cheng En & Ying Zhang, 2024. "Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems," Papers 2403.09532, arXiv.org.
- Xia Han & Peng Liu, 2024. "Robust Lambda-quantiles and extreme probabilities," Papers 2406.13539, arXiv.org.
- Yuyu Chen & Peng Liu & Yang Liu & Ruodu Wang, 2022. "Ordering and inequalities for mixtures on risk aggregation," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 421-451, January.
- Ariel Neufeld & Antonis Papapantoleon & Qikun Xiang, 2023. "Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Their Exact Computation," Management Science, INFORMS, vol. 69(4), pages 2051-2068, April.
- Yuyu Chen & Peng Liu & Yang Liu & Ruodu Wang, 2020. "Ordering and Inequalities for Mixtures on Risk Aggregation," Papers 2007.12338, arXiv.org, revised Jun 2021.
- Bingyan Han, 2022. "Distributionally robust risk evaluation with a causality constraint and structural information," Papers 2203.10571, arXiv.org, revised Aug 2024.
- Laurens Van Mieghem & Antonis Papapantoleon & Jonas Papazoglou-Hennig, 2023. "Machine learning for option pricing: an empirical investigation of network architectures," Papers 2307.07657, arXiv.org.
- Ariel Neufeld & Julian Sester & Daiying Yin, 2022. "Detecting data-driven robust statistical arbitrage strategies with deep neural networks," Papers 2203.03179, arXiv.org, revised Feb 2024.
- Ariel Neufeld & Philipp Schmocker, 2022. "Chaotic Hedging with Iterated Integrals and Neural Networks," Papers 2209.10166, arXiv.org, revised Jul 2024.
- Ariel Neufeld & Julian Sester, 2021. "A deep learning approach to data-driven model-free pricing and to martingale optimal transport," Papers 2103.11435, arXiv.org, revised Dec 2022.
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