Robust risk aggregation with neural networks

DOI10.1111/mafi.12280OpenAlexW3034928501WikidataQ100517891 ScholiaQ100517891MaRDI QIDQ5855956

Stephan Eckstein, Michael Kupper, Mathias Pohl

Publication date: 23 March 2021

Published in: Mathematical Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.00304

zbMATH Keywords

penalizationneural networksmodel uncertaintyWasserstein distanceoptimal transportdependence uncertaintyaverage value at riskrisk bounds

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Artificial neural networks and deep learning (68T07)

Related Items (6)

Robust estimation of superhedging prices ⋮ Ordering and inequalities for mixtures on risk aggregation ⋮ Computational methods for adapted optimal transport ⋮ Computation of optimal transport and related hedging problems via penalization and neural networks ⋮ Martingale transport with homogeneous stock movements ⋮ BOUNDS ON MULTI-ASSET DERIVATIVES VIA NEURAL NETWORKS

This page was built for publication: Robust risk aggregation with neural networks