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This work proposes a way to align statistical modeling with decision making. We provide a method that propagates the uncertainty in predictive modeling to the uncertainty in operational cost, where operational cost is the amount spent by…

Machine Learning · Statistics 2015-03-19 Theja Tulabandhula , Cynthia Rudin

The paper provides a framework for the assessment and optimization of the total risk of complex distributed systems. The framework takes into account the risk of each agent, which may arise from heterogeneous sources, as well as the risk…

Optimization and Control · Mathematics 2025-09-09 Aray Almen , Darinka Dentcheva

Systemic risk is the risk that a company- or industry-level risk could trigger a huge collapse of another or even the whole institution. Various systemic risk measures have been proposed in the literature to quantify the domino and…

Risk Management · Quantitative Finance 2024-05-14 Tong Pu , Yifei Zhang , Yiying Zhang

Recently, Basel Committee for Banking Supervision proposed to replace all approaches, including Advanced Measurement Approach (AMA), for operational risk capital with a simple formula referred to as the Standardised Measurement Approach…

Risk Management · Quantitative Finance 2016-09-15 Gareth W. Peters , Pavel V. Shevchenko , Bertrand Hassani , Ariane Chapelle

This article provides an overview of model predictive control (MPC) frameworks for dynamic operation of nonlinear constrained systems. Dynamic operation is often an integral part of the control objective, ranging from tracking of reference…

Systems and Control · Electrical Eng. & Systems 2024-01-10 Johannes Köhler , Matthas A. Müller , Frank Allgöwer

By treating the financial market as a thermodynamic system, we establish a one-to-one correspondence between thermodynamic variables and economic quantities. Measured by the expected loss under the worst-case scenario, financial risk caused…

Risk Management · Quantitative Finance 2019-04-02 Yu Feng

Given two random variables $X$ and $Y$, an operational approach is undertaken to quantify the ``leakage'' of information from $X$ to $Y$. The resulting measure $\mathcal{L}(X \!\! \to \!\! Y)$ is called \emph{maximal leakage}, and is…

Information Theory · Computer Science 2018-07-23 Ibrahim Issa , Aaron B. Wagner , Sudeep Kamath

In this paper, we introduce a probabilistic approach to risk assessment of robot systems by focusing on the impact of uncertainties. While various approaches to identifying systematic hazards (e.g., bugs, design flaws, etc.) can be found in…

Robotics · Computer Science 2024-10-28 Woo-Jeong Baek , Tom P. Huck , Joschka Haas , Jonas Lewandrowski , Tamim Asfour , Torsten Kröger

We present a probabilistic model of an intrusion in a renewal process. Given a process and a sequence of events, an intrusion is a subsequence of events that is not produced by the process. Applications of the model are, for example, online…

Artificial Intelligence · Computer Science 2018-05-29 David Tolpin

Business process simulation is an approach to evaluate business process changes prior to implementation. Existing methods in this field primarily support tactical decision-making, where simulations start from an empty state and aim to…

Software Engineering · Computer Science 2025-09-10 Maksym Avramenko , David Chapela-Campa , Marlon Dumas , Fredrik Milani

Organizations that develop software have recognized that software process models are particularly useful for maintaining a high standard of quality. In the last decade, simulations of software processes were used in several settings and…

Software Engineering · Computer Science 2014-02-24 Holger Neu , Thomas Hanne , Jürgen Münch , Stefan Nickel , Andreas Wirsen

We present a new, tractable method for solving and analyzing risk-aware control problems over finite and infinite, discounted time-horizons where the dynamics of the controlled process are described as a martingale problem. Supposing…

Optimization and Control · Mathematics 2020-06-23 Jukka Isohätälä , William B. Haskell

Financial market risk forecasting involves applying mathematical models, historical data analysis and statistical methods to estimate the impact of future market movements on investments. This process is crucial for investors to develop…

Statistical Finance · Quantitative Finance 2024-05-24 Jinxin Xu , Kaixian Xu , Yue Wang , Qinyan Shen , Ruisi Li

In this paper, we discuss aspects of model risk management in financial institutions which could be adopted by academic institutions to improve the process of conducting academic research, identify and mitigate existing limitations,…

Risk Management · Quantitative Finance 2024-06-24 Mahmood Alaghmandan , Olga Streltchenko

The ongoing concern about systemic risk since the outburst of the global financial crisis has highlighted the need for risk measures at the level of sets of interconnected financial components, such as portfolios, institutions or members of…

Risk Management · Quantitative Finance 2017-03-24 Yannick Armenti , Stephane Crepey , Samuel Drapeau , Antonis Papapantoleon

We study the difference between the level of systemic risk that is empirically measured on an interbank network and the risk that can be deduced from the balance sheets composition of the participating banks. Using generalised DebtRank…

Risk Management · Quantitative Finance 2022-09-07 Alessandro Ferracci , Giulio Cimini

While attack graphs are useful for identifying major cybersecurity threats affecting a system, they do not provide operational support for determining the likelihood of having a known vulnerability exploited, or that critical system nodes…

Cryptography and Security · Computer Science 2026-04-21 Francesco Vitale , Simone Guarino , Stefano Perone , Massimiliano Rak , Nicola Mazzocca

This paper provides a unified framework, which allows, in particular, to study the structure of dynamic monetary risk measures and dynamic acceptability indices. The main mathematical tool, which we use here, and which allows us to…

Probability · Mathematics 2014-08-22 Tomasz R. Bielecki , Igor Cialenco , Samuel Drapeau , Martin Karliczek

By adopting a distributional viewpoint on law-invariant convex risk measures, we construct dynamics risk measures (DRMs) at the distributional level. We then apply these DRMs to investigate Markov decision processes, incorporating latent…

Optimization and Control · Mathematics 2024-04-24 Ziteng Cheng , Sebastian Jaimungal

Clinical trials are characterized by high costs, extended timelines, and substantial operational risk, yet reliable prospective methods for predicting trial success before initiation remain limited. Existing artificial intelligence…