Information geometry in mathematical finance: Model risk, worst and almost worst scenarios

Thomas Breuer, Imre Csiszar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The mathematical problem addressed is minimising the expectation of a random variable over a set of feasible distributions P Γ, given as a level set of a convex integral functional. As special cases, Γ may be an f-divergence or f-divergence ball or a Bregman ball around a default distribution. Our approach is motivated by geometric intuition and relies upon the theory of minimising convex integral functionals subject to moment constraints. One main result is that all 'almost minimisers' P Γ belong to a small Bregman ball around a specified distribution or defective distribution P, equal to the strict minimiser if that exists but well defined also otherwise.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages404-408
Number of pages5
DOIs
Publication statusPublished - Dec 19 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: Jul 7 2013Jul 12 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2013 IEEE International Symposium on Information Theory, ISIT 2013
CountryTurkey
CityIstanbul
Period7/7/137/12/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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  • Cite this

    Breuer, T., & Csiszar, I. (2013). Information geometry in mathematical finance: Model risk, worst and almost worst scenarios. In 2013 IEEE International Symposium on Information Theory, ISIT 2013 (pp. 404-408). [6620257] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2013.6620257