Stochastic integration and differential equations for typical paths

Daniel Bartl, Michael Kupper, Ariel Neufeld

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The goal of this paper is to define stochastic integrals and to solve stochastic differential equations for typical paths taking values in a possibly infinite dimensional separable Hilbert space without imposing any probabilistic structure. In the spirit of [33, 37] and motivated by the pricing duality result obtained in [4] we introduce an outer measure as a variant of the pathwise minimal superhedging price where agents are allowed to trade not only in ω but also in ω dω:= ω2 − ‹ω› and where they are allowed to include beliefs in future paths of the price process expressed by a prediction set. We then call a property to hold true on typical paths if the set of paths where the property fails is null with respect to our outer measure. It turns out that adding the second term ω2 − ‹ω› in the definition of the outer measure enables to directly construct stochastic integrals which are continuous, even for typical paths taking values in an infinite dimensional separable Hilbert space. Moreover, when restricting to continuous paths whose quadratic variation is absolutely continuous with uniformly bounded derivative, a second construction of model-free stochastic integrals for typical paths is presented, which then allows to solve in a model-free way stochastic differential equations for typical paths.

Original languageEnglish
Article number97
JournalElectronic Journal of Probability
Volume24
DOIs
Publication statusPublished - 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Institute of Mathematical Statistics. All rights reserved.

ASJC Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Föllmer integration
  • Infinite dimensional stochastic calculus
  • Pathwise SDE
  • Pathwise stochastic integral
  • Vovk’s outer measure

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