English

Root to Kellerer

Probability 2017-07-27 v1

Abstract

We revisit Kellerer's Theorem, that is, we show that for a family of real probability distributions (μt)t[0,1](\mu_t)_{t\in [0,1]} which increases in convex order there exists a Markov martingale (St)t[0,1](S_t)_{t\in[0,1]} s.t.\ StμtS_t\sim \mu_t. To establish the result, we observe that the set of martingale measures with given marginals carries a natural compact Polish topology. Based on a particular property of the martingale coupling associated to Root's embedding this allows for a relatively concise proof of Kellerer's theorem. We emphasize that many of our arguments are borrowed from Kellerer \cite{Ke72}, Lowther \cite{Lo07}, and Hirsch-Roynette-Profeta-Yor \cite{HiPr11,HiRo12}.

Cite

@article{arxiv.1507.07690,
  title  = {Root to Kellerer},
  author = {Mathias Beiglböck and Martin Huesmann and Florian Stebegg},
  journal= {arXiv preprint arXiv:1507.07690},
  year   = {2017}
}

Comments

8 pages, 1 figure

R2 v1 2026-06-22T10:20:15.675Z