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Random G-expectations

We construct a time-consistent sublinear expectation in the setting of volatility uncertainty. This mapping extends Peng's G-expectation by allowing the range of the volatility uncertainty to be stochastic. Our construction is purely probabilistic and based on an optimal control formulation with path-dependent control sets.

5 nodes6 linksoverview mapRandom G-expectations
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Random G-expectations5 visible / 5 total nodes / 6 links
Related contextRelated contextAuthorshipTopic signalTopic signalTopic signalWRandom G-expectationspreprint / 2013AMarcel NutzResearcherTmath.OC9232 worksTmath.PR7239 worksTq-fin.RM381 works
PaperSignal 104 links

Random G-expectations

preprint / 2013

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