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We introduce a framework for quantifying propagation of uncertainty arising in a dynamic setting. Specifically, we define dynamic uncertainty sets designed explicitly for discrete stochastic processes over a finite time horizon. These…

Risk Management · Quantitative Finance 2024-02-05 Marlon Moresco , Mélina Mailhot , Silvana M. Pesenti

We review the nature of some well-known phenomena such as volatility smiles, convexity adjustments and parallel derivative markets. We propose that the market is incomplete and postulate the existence of intrinsic risks in every contingent…

Pricing of Securities · Quantitative Finance 2014-08-19 Truc Le

We prove that a general class of measures, which includes $\log$-concave measures, is $\frac{1}{n}$-concave according to the terminology of Borell, with additional assumptions on the measures or on the sets, such as symmetries. This…

Functional Analysis · Mathematics 2014-12-16 Arnaud Marsiglietti

Convex risk measures play a foundational role in the area of stochastic optimization. However, in contrast to risk neutral models, their applications are still limited due to the lack of efficient solution methods. In particular, the mean…

Optimization and Control · Mathematics 2024-12-30 Zhichao Jia , Guanghui Lan , Zhe Zhang

This paper applies risk analysis to medical problems, through the properties of nonlinear responses (convex or concave). It shows 1) necessary relations between the nonlinearity of dose-response and the statistical properties of the…

Quantitative Methods · Quantitative Biology 2018-08-02 Nassim Nicholas Taleb

This paper compares two different frameworks recently introduced in the literature for measuring risk in a multi-period setting. The first corresponds to applying a single coherent risk measure to the cumulative future costs, while the…

Risk Management · Quantitative Finance 2015-03-19 Dan A. Iancu , Marek Petrik , Dharmashankar Subramanian

We provide a new computationally-efficient class of estimators for risk minimization. We show that these estimators are robust for general statistical models: in the classical Huber epsilon-contamination model and in heavy-tailed settings.…

Machine Learning · Statistics 2018-04-23 Adarsh Prasad , Arun Sai Suggala , Sivaraman Balakrishnan , Pradeep Ravikumar

We study policy evaluation of offline contextual bandits subject to unobserved confounders. Sensitivity analysis methods are commonly used to estimate the policy value under the worst-case confounding over a given uncertainty set. However,…

Machine Learning · Statistics 2026-01-13 Kei Ishikawa , Niao He , Takafumi Kanamori

We expose a theoretical hedging optimization framework with variational preferences under convex risk measures. We explore a general dual representation for the composition between risk measures and utilities. We study the properties of the…

Mathematical Finance · Quantitative Finance 2024-10-11 Marcelo Righi

Systemic risk measures were introduced to capture the global risk and the corresponding contagion effects that is generated by an interconnected system of financial institutions. To this purpose, two approaches were suggested. In the first…

Optimization and Control · Mathematics 2024-02-23 Sarah Kaakai , Anis Matoussi , Achraf Tamtalini

Conditional forecasts of risk measures play an important role in internal risk management of financial institutions as well as in regulatory capital calculations. In order to assess forecasting performance of a risk measurement procedure,…

Risk Management · Quantitative Finance 2017-02-22 Natalia Nolde , Johanna F. Ziegel

In this paper, we develop the lower and upper bounds of worst-case distortion riskmetrics and weighted entropy for unimodal, and symmetric unimodal distributions when mean and variance information are available. We also consider the sharp…

Risk Management · Quantitative Finance 2025-11-24 Baishuai Zuo , Chuancun Yin

We develop a new approach to solving classification problems, which is bases on the theory of coherent measures of risk and risk sharing ideas. The proposed approach aims at designing a risk-averse classifier. The new approach allows for…

Machine Learning · Statistics 2018-07-24 Constantine Vitt , Darinka Dentcheva , Hui Xiong

We develop a framework for regularly varying measures on complete separable metric spaces $\mathbb{S}$ with a closed cone $\mathbb{C}$ removed, extending material in Hult & Lindskog (2006), Das, Mitra & Resnick (2013). Our framework…

Probability · Mathematics 2013-07-23 Filip Lindskog , Sidney I. Resnick , Joyjit Roy

This paper is concerned with the properties of the sets of strategic measures induced by admissible team policies in decentralized stochastic control and the convexity properties in dynamic team problems. To facilitate a convex analytical…

Optimization and Control · Mathematics 2016-11-01 Serdar Yüksel , Naci Saldi

We study strategic interaction in data-driven games where players face uncertainty about payoff distributions inferred from finite samples. To model calibrated attitudes toward such uncertainty, we formulate distributionally robust games…

Computer Science and Game Theory · Computer Science 2026-05-28 Bharat Gangwani , Arunesh Sinha

Measuring and managing risk has become crucial in modern decision making under stochastic uncertainty. In two-stage stochastic programming, mean risk models are essentially defined by a parametric recourse problem and a quantification of…

Optimization and Control · Mathematics 2016-11-28 Matthias Claus , Volker Krätschmer , Rüdiger Schultz

In this paper, we consider the problem of equal risk pricing and hedging in which the fair price of an option is the price that exposes both sides of the contract to the same level of risk. Focusing for the first time on the context where…

Optimization and Control · Mathematics 2020-09-17 Saeed Marzban , Erick Delage , Jonathan Yumeng Li

We propose forecast encompassing tests for the Expected Shortfall (ES) jointly with the Value at Risk (VaR) based on flexible link (or combination) functions. Our setup allows testing encompassing for convex forecast combinations and for…

Econometrics · Economics 2020-09-17 Timo Dimitriadis , Xiaochun Liu , Julie Schnaitmann

Despite decades of research in risk management, most of the literature has focused on scalar risk measures (like e.g. Value-at-Risk and Expected Shortfall). While such scalar measures provide compact and tractable summaries, they provide a…

Risk Management · Quantitative Finance 2025-11-28 Michele Bonollo , Martino Grasselli , Gianmarco Mori , Havva Nilsu Oz
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