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Related papers: Knight--Walras Equilibria

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Understanding the uncertainty of a neural network's (NN) predictions is essential for many purposes. The Bayesian framework provides a principled approach to this, however applying it to NNs is challenging due to large numbers of parameters…

Machine Learning · Statistics 2020-02-27 Tim Pearce , Felix Leibfried , Alexandra Brintrup , Mohamed Zaki , Andy Neely

This paper presents a novel framework for characterizing dissipativity of uncertain systems whose dynamics evolve according to differential-algebraic equations. Sufficient conditions for dissipativity (specializing to, e.g., stability or…

Systems and Control · Electrical Eng. & Systems 2024-05-13 Emily Jensen , Neelay Junnarkar , Murat Arcak , Xiaofan Wu , Suat Gumussoy

We revisit the classical topic of quadratic and linear mean-variance equilibria with both financial and real assets. The novelty of our results is that they are the first allowing for equilibrium prices driven by general semimartingales and…

Mathematical Finance · Quantitative Finance 2024-08-07 Christoph Czichowsky , Martin Herdegen , David Martins

An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $\alpha$-maxmin nonlinear…

Mathematical Finance · Quantitative Finance 2021-07-15 Yu-Jui Huang , Xiang Yu

Neural networks predictions are unreliable when the input sample is out of the training distribution or corrupted by noise. Being able to detect such failures automatically is fundamental to integrate deep learning algorithms into robotics.…

Computer Vision and Pattern Recognition · Computer Science 2020-02-18 Antonio Loquercio , Mattia Segù , Davide Scaramuzza

We introduce a solution concept for extensive-form games of incomplete information in which players need not assign likelihoods to what they do not know about the game. This is embedded in a model in which players can hold multiple priors.…

Theoretical Economics · Economics 2021-09-03 Karl Schlag , Andriy Zapechelnyuk

Graph Neural Networks (GNN) provide a powerful framework that elegantly integrates Graph theory with Machine learning for modeling and analysis of networked data. We consider the problem of quantifying the uncertainty in predictions of GNN…

Machine Learning · Computer Science 2022-05-23 Sai Munikoti , Deepesh Agarwal , Laya Das , Balasubramaniam Natarajan

We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled…

Portfolio Management · Quantitative Finance 2020-10-01 Martin Herdegen , Johannes Muhle-Karbe , Dylan Possamaï

The thesis of this essay is that, in heterogeneous agent macroeconomics, the assumption of rational expectations about equilibrium prices is unrealistic and should be replaced. Rational expectations imply that decision makers forecast…

General Economics · Economics 2025-08-29 Benjamin Moll

This paper presents several results on performance analysis for a class of uncertain linear quantum systems subject to either quadratic or non-quadratic perturbations in the system Hamiltonian. Also, coherent guaranteed cost controllers are…

Quantum Physics · Physics 2014-04-16 Chengdi Xiang , Ian R. Petersen , Daoyi Dong

We consider fundamental questions of arbitrage pricing arising when the uncertainty model is given by a set of possible mutually singular probability measures. With a single probability model, essential equivalence between the absence of…

General Finance · Quantitative Finance 2016-11-26 Patrick Beißner

We prove the global existence of an incomplete, continuous-time finite-agent Radner equilibrium in which exponential agents optimize their expected utility over both running consumption and terminal wealth. The market consists of a traded…

Mathematical Finance · Quantitative Finance 2018-09-18 Kim Weston , Gordan Zitkovic

In robust combinatorial optimization, we would like to find a solution that performs well under all realizations of an uncertainty set of possible parameter values. How we model this uncertainty set has a decisive influence on the…

Optimization and Control · Mathematics 2024-04-30 Marc Goerigk , Mohammad Khosravi

We extend the study of learning in games to dynamics that exhibit non-asymptotic stability. We do so through the notion of uniform stability, which is concerned with equilibria of individually utility-seeking dynamics. Perhaps surprisingly,…

Computer Science and Game Theory · Computer Science 2025-10-17 Geelon So , Yi-An Ma

We define a general notion of entropy in elementary, algebraic terms. Based on that, weak forms of a scalar product and a distance measure are derived. We give basic properties of these quantities, generalize the Cauchy-Schwarz inequality,…

Spectral Theory · Mathematics 2024-04-10 Martin Schlather

Today's multiagent systems have grown too complex to rely on centralized controllers, prompting increasing interest in the design of distributed algorithms. In this respect, game theory has emerged as a valuable tool to complement more…

Systems and Control · Computer Science 2020-02-19 Rahul Chandan , Dario Paccagnan , Jason R. Marden

Drawing on set theory, this paper contributes to a deeper understanding of the structural condition of mathematical finance under Knightian uncertainty. We adopt a projective framework in which all components of the model -- prices, priors…

Mathematical Finance · Quantitative Finance 2025-07-01 Alexandre Boistard , Laurence Carassus , Safae Issaoui

We consider object allocation problems with capacities (see, e.g., Abdulkadiroglu and Sonmez, 1998; Basteck, 2025) where objects have to be assigned to agents. We show that if a lottery rule satisfies ex-post non-wastefulness and…

Theoretical Economics · Economics 2025-08-08 Tom Demeulemeester , Bettina Klaus

This paper studies preference aggregation under risk. In our model, each agent has an incomplete preference relation represented by a set of expected utility functions. The classical Pareto principle is silent on agreement involving…

Theoretical Economics · Economics 2026-01-06 Leo Kurata , Kensei Nakamura

In a model with no given probability measure, we consider asset pricing in the presence of frictions and other imperfections and characterize the property of coherent pricing, a notion related to (but much weaker than) the no arbitrage…

Mathematical Finance · Quantitative Finance 2016-09-12 Gianluca Cassese