collaborators

9 papers

cs.DC2026

Triangle-Free Coloring in LOCAL via Resilient Lovász Local Lemma

Peter Davies-Peck, Xusheng Zhang

The Lovász Local Lemma (LLL) is a probabilistic tool that has been shown to be of central importance in the study of distributed algorithms. For example, the constructive LLL is kn…

math.PR2026

A Small-Noise Analysis of Controlled Functional Differential Equations with Gaussian Noise

David Criens, Max Nendel

We study small-noise asymptotics for controlled functional differential equations driven by additive Gaussian noise. The Gaussian noise is modeled on an abstract Wiener space, cove…

q-fin.TR2026

Optimal Market Making in Prediction Markets

Dominik Feil, Max Nendel

Prediction markets are attracting growing attention as trading volumes rise and their practical relevance increases. To ensure efficient price discovery, liquidity provision become…

math.OC2026

Scaling limits of multi-period distributionally robust optimization problems

Max Nendel, Ariel Neufeld, Kyunghyun Park +1

We examine the scaling limit of multi-period distributionally robust optimization (DRO) problems via a semigroup approach. Each period involves a worst-case maximization over distr…

q-fin.MF2026

An optimal transport foundation for a class of dynamically consistent risk measures

Sven Fuhrmann, Michael Kupper, Max Nendel

We study a class of dynamically consistent risk measures that robustify a time-homogeneous Markovian reference model by allowing for distributional uncertainty in its transition la…

q-fin.RM2026

Asymptotic Behaviour of Unexpected Losses and Risk Ratios for Co-Monotonic Alternatives

Max Nendel

The aggregation of individual risks in large credit and insurance portfolios is guided by diversification and the law of large numbers, which formalizes the convergence of sample a…