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Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar options, such as spread options and/or basket options on subindices. We show that, in most cases, adding further constraints gives rise to bounds that are considerably tighter. Our approach follows the literature on constrained optimal transport and, in particular, builds on the work of Eckstein & Kupper (2018) [Computation of optimal transport and related hedging problems via penalization and neural networks, Appl. Math. Optimiz. 1-29].
|Number of pages||20|
|Journal||International Journal of Theoretical and Applied Finance|
|Publication status||Published - Dec 2020|
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- 1 Finished
FWOODYS11: Quantitative Risk Management under Scenario Constraints: Risk aggregation, Dependence, and Systemic risk
1/10/16 → 30/09/21