Robust pricing and hedging of options on multiple assets and its numerics
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Abstract (arXiv)
We consider robust pricing and hedging for options written on multiple assets given market option prices for the individual assets. The resulting problem is called the multi-marginal martingale optimal transport problem. We propose two numerical methods to solve such problems: using discretisation and linear programming applied to the primal side and using penalisation and deep neural networks optimisation applied to the dual side. We prove convergence for our methods and compare their numerical performance. We show how adding further information about call option prices at additional maturities can be incorporated and narrows down the no-arbitrage pricing bounds. Finally, we obtain structural results for the case of the payoff given by a weighted sum of covariances between the assets.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Sep 2019.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1.
6 papers.
- 2022Chaotic Hedging with Iterated Integrals and Neural Networkscited by 10
- 2021A deep learning approach to data-driven model-free pricing and to martingale optimal transportcited by 6
- 2022Detecting data-driven robust statistical arbitrage strategies with deep neural networkscited by 4
- 2023Machine learning for option pricing: an empirical investigation of network architecturescited by 3
- 2023Neural networks can detect model-free static arbitrage strategiescited by 1
- 2024Improved model-free bounds for multi-asset options using option-implied information and deep learningcited by 0
- 2024Improved model-free bounds for multi-asset options using option-implied information and deep learning2 Apr 2024
- 2023Machine learning for option pricing: an empirical investigation of network architectures14 Jul 2023
- 2023Neural networks can detect model-free static arbitrage strategies19 Jun 2023
- 2022Chaotic Hedging with Iterated Integrals and Neural Networks21 Sep 2022
- 2022Detecting data-driven robust statistical arbitrage strategies with deep neural networks7 Mar 2022
- 2021A deep learning approach to data-driven model-free pricing and to martingale optimal transport21 Mar 2021