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This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are…

Pricing of Securities · Quantitative Finance 2013-01-22 Larry G. Epstein , Shaolin Ji

I introduce novel preference formulations which capture aversion to ambiguity about unknown and potentially time-varying volatility. I compare these preferences with Gilboa and Schmeidler's maxmin expected utility as well as variational…

Theoretical Economics · Economics 2021-09-21 Peter G. Hansen

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

Ambiguity is inherently present in many machine learning tasks, but especially for sequential models seldom accounted for, as most only output a single prediction. In this work we propose an extension of the Multiple Hypothesis Prediction…

Machine Learning · Statistics 2020-03-24 Alessandro Berlati , Oliver Scheel , Luigi Di Stefano , Federico Tombari

Recent advances in time series, where deterministic and stochastic modelings as well as the storage and analysis of big data are useless, permit a new approach to short-term traffic flow forecasting and to its reliability, i.e., to the…

Applications · Statistics 2016-02-29 Hassane Abouaïssa , Michel Fliess , Cédric Join

Monotonicity and recursivity are central assumptions in intertemporal consumption problems under ambiguity. We show that monotone recursive preferences admit both a recursive and an ex-ante representation, and that the certainty equivalent…

Theoretical Economics · Economics 2026-01-23 Massimo Marinacci , Giulio Principi , Lorenzo Stanca

This paper considers dynamic moral hazard settings, in which the consequences of the agent's actions are not precisely understood. In a new continuous-time moral hazard model with drift ambiguity, the agent's unobservable action translates…

General Economics · Economics 2021-10-29 Martin Dumav

We give a general formulation of the utility maximization problem under nondominated model uncertainty in discrete time and show that an optimal portfolio exists for any utility function that is bounded from above. In the unbounded case,…

Portfolio Management · Quantitative Finance 2013-07-16 Marcel Nutz

Ambiguity is shown in the context of the differential calculus of several variables and with the help of the language of category theory, a way to solve it in its most general form is offered. It is also shown that this new definition is…

Classical Analysis and ODEs · Mathematics 2007-05-23 Andrew E. Chubykalo , Rolando A. Flores , Juan A. Pérez

Completeness and transitivity are standard rationality conditions in economics. However, under ambiguity, decision makers sometimes violate these requirements because of the difficulty of forming accurate predictions about ambiguous events.…

Theoretical Economics · Economics 2025-09-16 Kensei Nakamura , Shohei Yanagita

It is well known that the minimal superhedging price of a contingent claim is too high for practical use. In a continuous-time model uncertainty framework, we consider a relaxed hedging criterion based on acceptable shortfall risks.…

Mathematical Finance · Quantitative Finance 2019-03-07 Ludovic Tangpi

In the present article we use the quantum formalism to describe the effects of risk and ambiguity in decision theory. The main idea is that the probabilities in the classic theory of expected utility are estimated probabilities, and thus do…

General Physics · Physics 2011-09-21 Riccardo Franco

The continuous time model of dynamic asset trading is the central model of modern finance. Because trading cannot in fact take place at every moment of time, it would seem desirable to show that the continuous time model can be viewed as…

Theoretical Economics · Economics 2022-07-08 William R. Zame

People often deviate from expected utility theory when making risky and intertemporal choices. While the effects of probabilistic risk and time delay have been extensively studied in isolation, their interplay and underlying theoretical…

Theoretical Economics · Economics 2025-04-10 Ho Ka Chan , Taro Toyoizumi

Standard models of multi-agent modal logic do not capture the fact that information is often \emph{ambiguous}, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different…

Artificial Intelligence · Computer Science 2014-01-10 Joseph Y. Halpern , Willemien Kets

We give explicit solutions for utility maximization of terminal wealth problem $u(X_T)$ in the presence of Knightian uncertainty in continuous time $[0,T]$ in a complete market. We assume there is uncertainty on both drift and volatility of…

Mathematical Finance · Quantitative Finance 2019-09-13 Kerem Ugurlu

The process of identifying a time variable in time reparameterization invariant theories results in great ambiguities about the actual laws of physics described by a given theory. A theory set up to describe one set of physical laws can…

High Energy Physics - Theory · Physics 2010-04-08 Andreas Albrecht , Alberto Iglesias

We propose a game-theoretic framework that incorporates both incomplete information and general ambiguity attitudes on factors external to all players. Our starting point is players' preferences on payoff-distribution vectors, essentially…

Economics · Quantitative Finance 2017-04-04 Jian Yang

In this paper we study a robust utility maximization problem in continuous time under model uncertainty. The model uncertainty is governed by a continuous semimartingale with uncertain local characteristics. Here, the differential…

Mathematical Finance · Quantitative Finance 2023-08-04 David Criens , Lars Niemann

In real-world time series forecasting, uncertainty and lack of reliable evaluation pose significant challenges. Notably, forecasting errors often arise from underfitting in-distribution data and failing to handle out-of-distribution inputs.…

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