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Risk sensitive decision making finds important applications in current day use cases. Existing risk measures consider a single or finite collection of random variables, which do not account for the asymptotic behaviour of underlying…

Risk Management · Quantitative Finance 2024-05-24 Shivam Patel , Vivek Borkar

Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of Neyman-Pearson type binary solution. We…

Portfolio Management · Quantitative Finance 2013-08-19 Jing Li , Mingxin Xu

We account for time-varying parameters in the conditional expectile-based value at risk (EVaR) model. The EVaR downside risk is more sensitive to the magnitude of portfolio losses compared to the quantile-based value at risk (QVaR). Rather…

Statistical Finance · Quantitative Finance 2020-09-29 Xiu Xu , Andrija Mihoci , Wolfgang Karl Härdle

The global financial crisis of 2007-2009 highlighted the crucial role systemic risk plays in ensuring stability of financial markets. Accurate assessment of systemic risk would enable regulators to introduce suitable policies to mitigate…

Statistics Theory · Mathematics 2022-03-03 Natalia Nolde , Chen Zhou , Menglin Zhou

We consider the portfolio optimization with risk measured by conditional value-at-risk, based on the stress event of chosen asset being equal to the opposite of its value-at-risk level, under the normality assumption. Solvability conditions…

Optimization and Control · Mathematics 2017-03-07 Anna Zalewska

Conditional value-at-risk (CoVaR) is one of the most important measures of systemic risk. It is defined as the high quantile conditional on a related variable being extreme, widely used in the field of quantitative risk management. In this…

Methodology · Statistics 2026-02-12 Zhaowen Wang , Yutao Liu , Deyuan Li

The entropic value-at-risk (EVaR) is a new coherent risk measure, which is an upper bound for both the value-at-risk (VaR) and conditional value-at-risk (CVaR). As important properties, the EVaR is strongly monotone over its domain and…

Portfolio Management · Quantitative Finance 2020-04-17 Amir Ahmadi-Javid , Malihe Fallah-Tafti

The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the…

Portfolio Management · Quantitative Finance 2020-07-21 Kei Nakagawa , Shuhei Noma , Masaya Abe

Several well-established benchmark predictors exist for Value-at-Risk (VaR), a major instrument for financial risk management. Hybrid methods combining AR-GARCH filtering with skewed-$t$ residuals and the extreme value theory-based approach…

Risk Management · Quantitative Finance 2021-11-25 Shige Peng , Shuzhen Yang , Jianfeng Yao

Value at Risk (VaR) and stress testing are two of the most widely used approaches in portfolio risk management to estimate potential market value losses under adverse market moves. VaR quantifies potential loss in value over a specified…

Computational Finance · Quantitative Finance 2024-10-01 Krishan Mohan Nagpal

To find a trade-off between profitability and prudence, financial practitioners need to choose appropriate risk measures. Two key points are: Firstly, investors' risk attitudes under uncertainty conditions should be an important reference…

Risk Management · Quantitative Finance 2019-07-30 Wentao Hu

This paper proposes a safety analysis method that facilitates a tunable balance between the worst-case and risk-neutral perspectives. First, we define a risk-sensitive safe set to specify the degree of safety attained by a stochastic…

Systems and Control · Electrical Eng. & Systems 2020-07-28 Margaret P. Chapman , Jonathan P. Lacotte , Kevin M. Smith , Insoon Yang , Yuxi Han , Marco Pavone , Claire J. Tomlin

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

We study risk-sensitive planning under partial observability using the dynamic risk measure Iterated Conditional Value-at-Risk (ICVaR). A policy evaluation algorithm for ICVaR is developed with finite-time performance guarantees that do not…

Artificial Intelligence · Computer Science 2026-01-29 Yaacov Pariente , Vadim Indelman

In economics, insurance and finance, value at risk (VaR) is a widely used measure of the risk of loss on a specific portfolio of financial assets. For a given portfolio, time horizon, and probability $\alpha$, the $100\alpha\%$ VaR is…

Risk Management · Quantitative Finance 2018-03-15 Raúl Torres , Rosa E. Lillo , Henry Laniado

We present the conditional value-at-risk (CVaR) in the context of Markov chains and Markov decision processes with reachability and mean-payoff objectives. CVaR quantifies risk by means of the expectation of the worst p-quantile. As such it…

Logic in Computer Science · Computer Science 2018-05-09 Jan Křetínský , Tobias Meggendorfer

Portfolio selection in the periodic investment of securities modeled by a multivariate Merton model with dependent jumps is considered. The optimization framework is designed to maximize expected terminal wealth when portfolio risk is…

Statistics Theory · Mathematics 2021-04-22 Bahareh Afhami , Mohsen Rezapour , Mohsen Madadi , Vahed Maroufy

The popular systemic risk measure CoVaR (conditional Value-at-Risk) and its variants are widely used in economics and finance. In this article, we propose joint dynamic forecasting models for the Value-at-Risk (VaR) and CoVaR. The CoVaR…

Econometrics · Economics 2025-01-22 Timo Dimitriadis , Yannick Hoga

Risk measures are important key figures to measure the adequacy of the reserves of a company. The most common risk measures in practice are Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). Recently, quantum-based algorithms are…

Quantum Physics · Physics 2025-01-29 Christian Laudagé , Ivica Turkalj

In several real-world applications involving decision making under uncertainty, the traditional expected value objective may not be suitable, as it may be necessary to control losses in the case of a rare but extreme event. Conditional…

Machine Learning · Computer Science 2018-08-07 Ravi Kumar Kolla , Prashanth L. A. , Sanjay P. Bhat , Krishna Jagannathan
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