  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 and discuss the maximizing/minimizing
copulas achieving such bounds. Our approach follows the literature on
constrained optimal transport and, in particular, builds on a recent paper by
Eckstein and Kupper (2019, Appl. Math. Optim.).
