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In this article, we address the problem of risk assessment of stealthy attacks on uncertain control systems. Considering data injection attacks that aim at maximizing impact while remaining undetected, we use the recently proposed…

Optimization and Control · Mathematics 2023-09-26 Sribalaji C. Anand , André M. H. Teixeira , Anders Ahlén

This paper addresses allocation methodologies for a risk measure inherited from ruin theory. Specifically, we consider a dynamic value-at-risk (VaR) measure defined as the smallest initial capital needed to ensure that the ultimate ruin…

Mathematical Finance · Quantitative Finance 2021-03-31 Guusje Delsing , Michel Mandjes , Peter Spreij , Erik Winands

We study the risk criterion for investments based on the drawdown from the maximal value of the capital in the past. Depending on investor's risk attitude, thus his risk exposure, we find that the distribution of these drawdowns follows a…

Statistical Mechanics · Physics 2015-06-25 Sergei Maslov , Yi-Cheng Zhang

Credit Suisse First Boston (CSFB) launched in 1997 the model CreditRisk+ which aims at calculating the loss distribution of a credit portfolio on the basis of a methodology from actuarial mathematics. Knowing the loss distribution, it is…

Statistical Mechanics · Physics 2008-12-02 Hermann Haaf , Dirk Tasche

In this paper, within the framework of uncertainty theory, the valuation of equity warrants is investigated. Different from the methods of probability theory, the equity warrants pricing problem is solved by using the method of uncertain…

Pricing of Securities · Quantitative Finance 2017-11-27 Foad Shokrollahi

Determining risk contributions of unit exposures to portfolio-wide economic capital is an important task in financial risk management. Computing risk contributions involves difficulties caused by rare-event simulations. In this study, we…

Risk Management · Quantitative Finance 2019-01-18 Takaaki Koike , Mihoko Minami

Traditional multi-armed bandit (MAB) formulations usually make certain assumptions about the underlying arms' distributions, such as bounds on the support or their tail behaviour. Moreover, such parametric information is usually 'baked'…

Machine Learning · Computer Science 2022-03-29 Anmol Kagrecha , Jayakrishnan Nair , Krishna Jagannathan

Practitioners making decisions based on causal effects typically ignore structural uncertainty. We analyze when this uncertainty is consequential enough to warrant methodological solutions (Bayesian model averaging over competing causal…

Machine Learning · Computer Science 2025-08-01 Maurits Kaptein

Much research in systemic risk is focused on default contagion. While this demands an understanding of valuation, fewer articles specifically deal with the existence, the uniqueness, and the computation of equilibrium prices in structural…

Computational Finance · Quantitative Finance 2015-01-30 Johannes Hain , Tom Fischer

Risk management is particularly concerned with extreme events, but analysing these events is often hindered by the scarcity of data, especially in a multivariate context. This data scarcity complicates risk management efforts. Various tools…

Methodology · Statistics 2026-01-15 Nisrine Madhar , Juliette Legrand , Maud Thomas

We introduce two kinds of risk measures with respect to some reference probability measure, which both allow for a certain order structure and domination property. Analyzing their relation to each other leads to the question when a certain…

Risk Management · Quantitative Finance 2022-04-15 Christa Cuchiero , Guido Gazzani , Irene Klein

The Solvency II Directive and Solvency Assessment and Management (the South African equivalent) give a Solvency Capital Requirement which is based on a 99.5% Value-at-Risk (VaR) calculation. This calculation involves aggregating individual…

Applications · Statistics 2018-04-06 Sean van der Merwe , Darren Steven , Martinette Pretorius

Estimating the parameters of max-stable parametric models poses significant challenges, particularly when some parameters lie on the boundary of the parameter space. This situation arises when a subset of variables exhibits extreme values…

Methodology · Statistics 2026-04-08 Anas Mourahib , Anna Kiriliouk , Johan Segers

We consider the problem of deciding on sampling strategy, in particular sampling design. We propose a risk measure, whose minimizing value guides the choice. The method makes use of a superpopulation model and takes into account uncertainty…

Methodology · Statistics 2020-07-06 Edgar Bueno , Dan Hedlin

Applying a machine learning model for decision-making in the real world requires to distinguish what the model knows from what it does not. A critical factor in assessing the knowledge of a model is to quantify its predictive uncertainty.…

Machine Learning · Computer Science 2023-11-15 Kajetan Schweighofer , Lukas Aichberger , Mykyta Ielanskyi , Sepp Hochreiter

In order to understand underlying processes governing environmental and physical processes, and predict future outcomes, a complex computer model is frequently required to simulate these dynamics. However there is inevitably uncertainty…

Methodology · Statistics 2017-02-14 B. Swallow , M. Rigby , J. C. Rougier , A. J. Manning , M. Lunt , S. O'Doherty

A new risk measure, the lambda value at risk (Lambda VaR), has been recently proposed from a theoretical point of view as a generalization of the value at risk (VaR). The Lambda VaR appears attractive for its potential ability to solve…

Risk Management · Quantitative Finance 2017-06-05 Jacopo Corbetta , Ilaria Peri

This paper firstly addresses the problem of risk assessment under false data injection attacks on uncertain control systems. We consider an adversary with complete system knowledge, injecting stealthy false data into an uncertain control…

Systems and Control · Electrical Eng. & Systems 2022-12-12 Sribalaji C. Anand , André M. H. Teixeira , Anders Ahlén

In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at-risk, of output quantities of complex random differential…

Computation · Statistics 2023-05-23 Quentin Ayoul-Guilmard , Sundar Ganesh , Sebastian Krumscheid , Fabio Nobile

In this paper, a new way to integrate volatility information for estimating value at risk (VaR) and conditional value at risk (CVaR) of a portfolio is suggested. The new method is developed from the perspective of Bayesian statistics and it…

Risk Management · Quantitative Finance 2022-05-04 Taras Bodnar , Vilhelm Niklasson , Erik Thorsén