2 citations · 5 across the 15 of their papers we have counts for
16 papers
Fixed Points for the -Bass Martingale: Existence, Stability, and Convergence
Beatrice Acciaio, Antonio Marini
We establish existence, uniqueness, stability, and convergence results for one-dimensional -Bass martingales, characterized as the martingales with prescribed initial and termin…
Existence of -Bass martingales in the semidiscrete setting
Beatrice Acciaio, Antonio Marini
The class of -Bass martingales provides a natural answer to a central question in martingale optimal transport: how to construct martingales with prescribed initial and terminal…
The geometry of the adapted Bures--Wasserstein space
Beatrice Acciaio, Daniel Bartl, Anne Grass +2
The adapted Bures--Wasserstein space consists of Gaussian processes endowed with the adapted Wasserstein distance. It can be viewed as the analogue of the classical Bures--Wasserst…
Dynamic reinsurance via martingale transport
Beatrice Acciaio, Brandon Garcia Flores, Antonio Marini +1
We formulate a dynamic reinsurance problem in which the insurer seeks to satisfy prescribed terminal moment or risk-based constraints while minimizing the -norm of the ceded r…
Strassen's theorem for biased convex order
Beatrice Acciaio, Mathias Beiglböck, Evgeny Kolosov +1
Strassen's theorem asserts that for given marginal probabilities there exists a martingale starting in and terminating in if and only if are in convex order. Fr…
Absolutely Continuous Curves of Stochastic Processes
Beatrice Acciaio, Daniel Kršek, Gudmund Pammer +1
We study absolutely continuous curves in the adapted Wasserstein space of filtered processes. We provide a probabilistic representation of such curves as flows of adapted processes…
Estimating causal distances with non-causal ones
Beatrice Acciaio, Songyan Hou, Gudmund Pammer
The adapted Wasserstein () distance refines the classical Wasserstein () distance by incorporating the temporal structure of stochastic processes. This makes the -distan…
Entropic adapted Wasserstein distance on Gaussians
Beatrice Acciaio, Songyan Hou, Gudmund Pammer
The adapted Wasserstein distance is a metric for quantifying distributional uncertainty and assessing the sensitivity of stochastic optimization problems on time series data. A com…
Time-Causal VAE: Robust Financial Time Series Generator
Beatrice Acciaio, Stephan Eckstein, Songyan Hou
We build a time-causal variational autoencoder (TC-VAE) for robust generation of financial time series data. Our approach imposes a causality constraint on the encoder and decoder…
Multicausal transport: barycenters and dynamic matching
Beatrice Acciaio, Daniel Kršek, Gudmund Pammer
We introduce a multivariate version of causal transport, which we name multicausal transport, involving several filtered processes among which causality constraints are imposed. Su…
Calibration of the Bass Local Volatility model
Beatrice Acciaio, Antonio Marini, Gudmund Pammer
The Bass local volatility model introduced by Backhoff-Veraguas, Beiglböck, Huesmann, and Källblad is a Markov model perfectly calibrated to vanilla options at finitely many maturi…
Convergence of Adapted Empirical Measures on
Beatrice Acciaio, Songyan Hou
We consider empirical measures of -valued stochastic process in finite discrete-time. We show that the adapted empirical measure introduced in the recent work \cite{backhof…
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…
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.
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,…
Weak Transport for Non-Convex Costs and Model-independence in a Fixed-Income Market
Beatrice Acciaio, Mathias Beiglboeck, Gudmund Pammer
We consider a model-independent pricing problem in a fixed-income market and show that it leads to a weak optimal transport problem as introduced by Gozlan et al. We use this to ch…