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This article introduces a framework for evaluating statistical decisions under both prior ambiguity and likelihood misspecification. We begin with an ambiguity set - a frequentist model that pairs a possibly misspecified likelihood with…

Econometrics · Economics 2026-05-14 Karun Adusumilli

In decision-making problems under uncertainty, probabilistic constraints are a valuable tool to express safety of decisions. They result from taking the probability measure of a given set of random inequalities depending on the decision…

Optimization and Control · Mathematics 2021-02-09 Yassine Laguel , Wim van Ackooij , Jérôme Malick , Guilherme Ramalho

We combine forward investment performance processes and ambiguity averse portfolio selection. We introduce the notion of robust forward criteria which addresses the issues of ambiguity in model specification and in preferences and…

Portfolio Management · Quantitative Finance 2014-11-17 Sigrid Kallblad , Jan Obloj , Thaleia Zariphopoulou

We derive a closed form portfolio optimization rule for an investor who is diffident about mean return and volatility estimates, and has a CRRA utility. The novelty is that confidence is here represented using ellipsoidal uncertainty sets…

Portfolio Management · Quantitative Finance 2015-02-11 Sara Biagini , Mustafa Pinar

I study robust comparative statics for risk-averse subjective expected utility (SEU) maximizers. Starting with a finite menu of actions totally ordered by sensitivity to risk, I identify the transformations of her menu that lead a…

Theoretical Economics · Economics 2025-05-27 Mark Whitmeyer

This paper studies the advance-purchase game when a consumer has belief-based loss-averse preferences, introducing a novel perspective by incorporating reference updating. It demonstrates that loss aversion increases the consumer's…

Theoretical Economics · Economics 2024-05-14 Senran Lin

This paper investigates a purely qualitative version of Savage's theory for decision making under uncertainty. Until now, most representation theorems for preference over acts rely on a numerical representation of utility and uncertainty…

Artificial Intelligence · Computer Science 2013-01-30 Helene Fargier , Patrice Perny

Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task. In this work, we show that explicitly quantifying the uncertainty in…

Machine Learning · Computer Science 2019-10-08 Asma Ghandeharioun , Brian Eoff , Brendan Jou , Rosalind W. Picard

Can stated preferences help in counterfactual analyses of actual choice? This research proposes a novel approach to researchers who have access to both stated choices in hypothetical scenarios and actual choices. The key idea is to use…

Econometrics · Economics 2023-07-27 Romuald Meango

Experiments on decision making under uncertainty are known to display a classical pattern of risk aversion and risk seeking referred to as "fourfold pattern" (or "reflection effect") , but recent experiments varying the speed and order of…

Neurons and Cognition · Quantitative Biology 2024-01-17 Francesco Fumarola , Lukasz Kusmierz , Ronald B. Dekker

DeMarzo et al. (2005) consider auctions in which bids are selected from a completely ordered family of securities whose values are tied to the resource being auctioned. The paper defines a notion of relative steepness of families of…

Computer Science and Game Theory · Computer Science 2015-01-14 Vineet Abhishek , Bruce Hajek , Steven R. Williams

This study examines the relationship between ambiguity and the ideological positioning of political parties across the political spectrum. We identify a strong non-monotonic (inverted U-shaped) relationship between party ideology and…

General Economics · Economics 2024-03-21 Hector Galindo-Silva

There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous…

General Finance · Quantitative Finance 2015-11-06 Liang Wu , Jingyi Luo , Yingkai Tang , Gregory Bardes

Supervised learning has gone beyond the expected risk minimization framework. Central to most of these developments is the introduction of more general aggregation functions for losses incurred by the learner. In this paper, we turn towards…

Machine Learning · Computer Science 2024-06-05 Armando J. Cabrera Pacheco , Rabanus Derr , Robert C. Williamson

Humans display a tendency to pay more attention to bad outcomes, often in a disproportionate way relative to their statistical occurrence. They also display euphorism, as well as a preference for the current state of affairs (status quo…

Artificial Intelligence · Computer Science 2022-03-24 Michel de Lara

We explore whether ambiguous communication can be beneficial to the sender in a persuasion problem, when the receiver (and possibly the sender) is ambiguity averse. Our analysis highlights the necessity of using a collection of experiments…

Theoretical Economics · Economics 2026-02-19 Xiaoyu Cheng , Peter Klibanoff , Sujoy Mukerji , Ludovic Renou

In this work we show that the ordering ambiguity on quantization depends on the representation choice. This property is then used to solve unambiguously some particular systems. Finally, we speculate on the consequences for more involved…

Quantum Physics · Physics 2007-05-24 Alvaro de Souza Dutra

I revisit the standard moral-hazard model, in which an agent's preference over contracts is rooted in costly effort choice. I characterise the behavioural content of the model in terms of empirically testable axioms, and show that the…

Theoretical Economics · Economics 2025-11-26 Ludvig Sinander

The widespread use of machine learning and data-driven algorithms for decision making has been steadily increasing over many years. \emph{Bias} in the data can adversely affect this decision-making. We present a new mitigation strategy to…

Machine Learning · Computer Science 2025-07-25 Bruno Scarone , Alfredo Viola , Renée J. Miller , Ricardo Baeza-Yates

The aims of this study are twofold. First, we consider an optimal risk allocation problem with non-convex preferences. By establishing an infimal representation for distortion risk measures, we give some necessary and sufficient conditions…

Risk Management · Quantitative Finance 2015-03-17 Hirbod Assa
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