Journal
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
Volume 130, Issue 5, Pages 2918-2953Publisher
ELSEVIER
DOI: 10.1016/j.spa.2019.08.009
Keywords
Causal transport plan; Semimartingale decomposition; Filtration enlargement; Stochastic optimization; Robust bounds; Value of information
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Funding
- Doktoratskolleg of the Austrian Science Fund (FWF) [W1245]
- Department of Statistics, LSE, UK
- Austrian Science Fund (FWF) [W1245] Funding Source: Austrian Science Fund (FWF)
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The martingale part in the semimartingale decomposition of a Brownian motion with respect to an enlargement of its filtration, is an anticipative mapping of the given Brownian motion. In analogy to optimal transport theory, we define causal transport plans in the context of enlargement of filtrations, as the Kantorovich counterparts of the aforementioned non-adapted mappings. We provide a necessary and sufficient condition for a Brownian motion to remain a semimartingale in an enlarged filtration, in terms of certain minimization problems over sets of causal transport plans. The latter are also used in order to give robust transport-based estimates for the value of having additional information, as well as model sensitivity with respect to the reference measure, for the classical stochastic optimization problems of utility maximization and optimal stopping. (C) 2019 Elsevier B.V. All rights reserved.
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