Enlarged Filtrations and Indistinguishable Processes

Stochastic Analysis and Applications, 2020, Vol. 38, No. 1, 179-189

12 Pages Posted: 29 May 2018 Last revised: 4 Dec 2019

See all articles by Markus Hess

Markus Hess

RPTU University Kaiserslautern-Landau

Date Written: August 22, 2019

Abstract

We study modification properties of stochastic processes under different probability measures in an initially enlarged filtration setup. For this purpose, we consider several pure-jump Lévy processes under two equivalent probability measures and derive the associated martingale compensators with respect to different enlarged filtrations. As our main result, we prove that the obtained martingale processes under different probability measures in our enlarged filtration approach are indistinguishable. In addition, we provide a condition under which the pure-jump result can be carried over to the Brownian motion case. In this context, we show how indistinguishable Brownian motions under different probability measures can be constructed in an enlarged filtration framework. We finally apply our theoretical results to precipitation derivatives pricing under weather forecasts and optimal portfolio selection under future information.

Keywords: Enlarged Filtration, Indistinguishable Processes, Lévy Process, Poisson Random Measure, Martingale Compensator, Radon-Nikodym Density, Doléans-Dade Exponential, Girsanov Theorem, Stochastic Differential Equation, Weather Derivative, Precipitation Swap, Optimal Portfolio Selection

JEL Classification: C02, C53, D52, D80, G11, G13, G14

Suggested Citation

Hess, Markus, Enlarged Filtrations and Indistinguishable Processes (August 22, 2019). Stochastic Analysis and Applications, 2020, Vol. 38, No. 1, 179-189, Available at SSRN: https://ssrn.com/abstract=3176969 or http://dx.doi.org/10.2139/ssrn.3176969

Markus Hess (Contact Author)

RPTU University Kaiserslautern-Landau ( email )

Kaiserslautern, 67663
Germany

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