Improved model-free bounds for multi-asset options using option-implied information and deep learning

arXiv:2404.02343v1 Announce Type: cross
Abstract: We consider the computation of model-free bounds for multi-asset options in a setting that combines dependence uncertainty with additional information on the dependence structure. More specifically, we consider the setting where the marginal distributions are known and partial information, in the form of known prices for multi-asset options, is also available in the market. We provide a fundamental theorem of asset pricing in this setting, as well as a superhedging duality that allows to transform …

abstract arxiv computation cs.lg deep learning form free information math.oc q-fin.pr stat.ml type uncertainty