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This paper develops a safety analysis method for stochastic systems that is sensitive to the possibility and severity of rare harmful outcomes. We define risk-sensitive safe sets as sub-level sets of the solution to a non-standard optimal…

Systems and Control · Electrical Eng. & Systems 2022-06-28 Margaret P. Chapman , Riccardo Bonalli , Kevin M. Smith , Insoon Yang , Marco Pavone , Claire J. Tomlin

We consider an online stochastic game with risk-averse agents whose goal is to learn optimal decisions that minimize the risk of incurring significantly high costs. Specifically, we use the Conditional Value at Risk (CVaR) as a risk measure…

Machine Learning · Computer Science 2022-06-17 Zifan Wang , Yi Shen , Michael M. Zavlanos

The popularity of Conditional Value-at-Risk (CVaR), a risk functional from finance, has been growing in the control systems community due to its intuitive interpretation and axiomatic foundation. We consider a nonstandard optimal control…

Systems and Control · Electrical Eng. & Systems 2022-06-22 Margaret P. Chapman , Michael Fauss , Kevin M. Smith

The conditional value-at-risk (CVaR) is a useful risk measure in fields such as machine learning, finance, insurance, energy, etc. When measuring very extreme risk, the commonly used CVaR estimation method of sample averaging does not work…

Methodology · Statistics 2021-03-10 Dylan Troop , Frédéric Godin , Jia Yuan Yu

We propose nonparametric estimators for conditional value-at-risk (CVaR) and conditional expected shortfall (CES) associated with conditional distributions of a series of returns on a financial asset. The return series and the conditioning…

Methodology · Statistics 2016-12-28 Carlos Martins-Filho , Feng Yao , Maximo Torero

The stability of a complex financial system may be assessed by measuring risk contagion between various financial institutions with relatively high exposure. We consider a financial network model using a bipartite graph of financial…

Risk Management · Quantitative Finance 2025-05-23 Bikramjit Das , Vicky Fasen-Hartmann

Distributional reinforcement learning (RL) -- in which agents learn about all the possible long-term consequences of their actions, and not just the expected value -- is of great recent interest. One of the most important affordances of a…

Artificial Intelligence · Computer Science 2021-11-15 Chris Gagne , Peter Dayan

Risk measure forecast and model have been developed in order to not only provide better forecast but also preserve its (empirical) property especially coherent property. Whilst the widely used risk measure of Value-at-Risk (VaR) has shown…

Risk Management · Quantitative Finance 2020-09-08 Bony Josaphat , Khreshna Syuhada

Value-at-Risk (VaR) is an institutional measure of risk favored by financial regulators. VaR may be interpreted as a quantile of future portfolio values conditional on the information available, where the most common quantile used is 95%.…

Risk Management · Quantitative Finance 2016-05-18 Khizar Qureshi

This paper develops a semi-parametric procedure for estimation of unconditional quantile partial effects using quantile regression coefficients. The estimator is based on an identification result showing that, for continuous covariates,…

Econometrics · Economics 2024-01-02 Javier Alejo , Antonio F. Galvao , Julian Martinez-Iriarte , Gabriel Montes-Rojas

This paper is devoted to the quantification and analysis of marginal risk contribution of a given single financial institution i to the risk of a financial system s. Our work expands on the CoVaR concept proposed by Adrian and Brunnermeier…

Risk Management · Quantitative Finance 2012-11-27 Brice Hakwa , Manfred Jäger-Ambrożewicz , Barbara Rüdiger

For many real-world decision-making problems subject to uncertainty, it may be essential to deal with multiple and often conflicting objectives while taking the decision-makers' risk preferences into account. Conditional value-at-risk…

Optimization and Control · Mathematics 2023-02-14 Najmesadat Nazemi , Sophie N. Parragh , Walter J. Gutjahr

In many sequential decision-making problems we may want to manage risk by minimizing some measure of variability in costs in addition to minimizing a standard criterion. Conditional value-at-risk (CVaR) is a relatively new risk measure that…

Artificial Intelligence · Computer Science 2014-07-14 Yinlam Chow , Mohammad Ghavamzadeh

Conditional value at risk (CVaR) is a popular measure for quantifying portfolio risk. Sensitivity analysis of CVaR is very useful in risk management and gradient-based optimization algorithms. In this paper, we study the infinitesimal…

Numerical Analysis · Mathematics 2020-09-22 Zhijian He

This paper concerns sequential computation of risk measures for financial data and asks how, given a risk measurement procedure, we can tell whether the answers it produces are `correct'. We draw the distinction between `external' and…

Risk Management · Quantitative Finance 2015-11-20 Mark H. A. Davis

Value-at-Risk and its conditional allegory, which takes into account the available information about the economic environment, form the centrepiece of the Basel framework for the evaluation of market risk in the banking sector. In this…

Methodology · Statistics 2019-10-03 Gery Geenens , Richard Dunn

In safety-critical decision-making, the environment may evolve over time, and the learner adjusts its risk level accordingly. This work investigates risk-averse online optimization in dynamic environments with varying risk levels, employing…

Optimization and Control · Mathematics 2025-12-30 Siyi Wang , Zifan Wang , Karl H. Johansson

This paper is dedicated to the consistency of systemic risk measures with respect to stochastic dependence. It compares two alternative notions of Conditional Value-at-Risk (CoVaR) available in the current literature. These notions are both…

Risk Management · Quantitative Finance 2012-08-30 Georg Mainik , Eric Schaanning

Conditional Value-at-Risk (CVaR) is a central tail-risk measure in stochastic structural mechanics, yet its accurate evaluation under high-dimensional, spatially correlated material uncertainty remains computationally prohibitive for…

Machine Learning · Statistics 2026-02-11 Alireza Tabarraei

Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we…

Machine Learning · Statistics 2014-11-25 Aviv Tamar , Yonatan Glassner , Shie Mannor