Zhou, Z., Blanchet, J., & Glynn, P. W. (2021). Distributionally Robust Martingale Optimal Transport. ArXiv. /abs/2106.07191

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Abstract

We study the problem of bounding path-dependent expectations (within any finite time horizon ) over the class of discrete-time martingales whose marginal distributions lie within a prescribed tolerance of a given collection of benchmark marginal distributions. This problem is a relaxation of the martingale optimal transport (MOT) problem and is motivated by applications to super-hedging in financial markets. We show that the empirical version of our relaxed MOT problem can be approximated within error where is the number of samples of each of the individual marginal distributions (generated independently) and using a suitably constructed finite-dimensional linear programming problem.

Authors
Zhengqing Zhou, Jose Blanchet, Peter W Glynn
Publication date
2021/6/14
Journal
arXiv preprint arXiv:2106.07191