3 citations · 15 across the 36 of their papers we have counts for
8 papers · 1 filter
Denseness of biadapted Monge mappings
Mathias Beiglböck, Gudmund Pammer, Stefan Schrott
Adapted or causal transport theory aims to extend classical optimal transport from probability measures to stochastic processes. On a technical level, the novelty is to restrict to…
A regularized Kellerer theorem in arbitrary dimension
Gudmund Pammer, Benjamin A. Robinson, Walter Schachermayer
We present a multidimensional extension of Kellerer's theorem on the existence of mimicking Markov martingales for peacocks, a term derived from the French for stochastic processes…
Quantitative Fundamental Theorem of Asset Pricing
Beatrice Acciaio, Julio Backhoff, Gudmund Pammer
In this paper we provide a quantitative analysis to the concept of arbitrage, that allows to deal with model uncertainty without imposing the no-arbitrage condition. In markets tha…
Lipschitz continuity of the Wasserstein projections in the convex order on the line
Benjamin Jourdain, William Margheriti, Gudmund Pammer
Wasserstein projections in the convex order were first considered in the framework of weak optimal transport, and found application in various problems such as concentration inequa…
A short proof of the characterisation of convex order using the 2-Wasserstein distance
Beatrice Acciaio, Gudmund Pammer
We provide a short proof of the intriguing characterisation of the convex order given by Wiesel and Zhang.
A note on the adapted weak topology in discrete time
Gudmund Pammer
The adapted weak topology is an extension of the weak topology for stochastic processes designed to adequately capture properties of underlying filtrations. With the recent work of…
Computational methods for adapted optimal transport
Stephan Eckstein, Gudmund Pammer
Adapted optimal transport (AOT) problems are optimal transport problems for distributions of a time series where couplings are constrained to have a temporal causal structure. In t…
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer
Beatrice Acciaio, Anastasis Kratsios, Gudmund Pammer
Several problems in stochastic analysis are defined through their geometry, and preserving that geometric structure is essential to generating meaningful predictions. Nevertheless,…