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This paper introduces and studies factor risk measures. While risk measures only rely on the distribution of a loss random variable, in many cases risk needs to be measured relative to some major factors. In this paper, we introduce a…

Mathematical Finance · Quantitative Finance 2024-04-15 Hirbod Assa , Peng Liu

In recent years, it has become apparent that an isolated microprudential approach to capital adequacy requirements of individual institutions is insufficient. It can increase the homogeneity of the financial system and ultimately the cost…

Risk Management · Quantitative Finance 2023-11-27 Jana Hlavinova , Birgit Rudloff , Alexander Smirnow

We present a general framework for measuring the liquidity risk. The theoretical framework defines a class of risk measures that incorporate the liquidity risk into the standard risk measures. We consider a one-period risk measurement…

Mathematical Finance · Quantitative Finance 2016-10-31 Erindi Allaj

We introduce a general framework for measuring risk in the context of Markov control processes with risk maps on general Borel spaces that generalize known concepts of risk measures in mathematical finance, operations research and…

Optimization and Control · Mathematics 2014-01-27 Yun Shen , Wilhelm Stannat , Klaus Obermayer

The inf-convolution of risk measures is directly related to risk sharing and general equilibrium, and it has attracted considerable attention in mathematical finance and insurance problems. However, the theory is restricted to finite sets…

Risk Management · Quantitative Finance 2022-03-22 Marcelo Brutti Righi , Marlon Ruoso Moresco

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

Monetary risk measures are usually interpreted as the smallest amount of external capital that must be added to a financial position to make it acceptable. We propose a new concept: intrinsic risk measures and argue that this approach…

Risk Management · Quantitative Finance 2016-10-28 W. Farkas , A. Smirnow

This paper approaches the definition and properties of dynamic convex risk measures through the notion of a family of concave valuation operators satisfying certain simple and credible axioms. Exploring these in the simplest context of a…

Risk Management · Quantitative Finance 2008-12-02 A. Jobert , L. C. G. Rogers

The concept of boundary plays an important role in several branches of general relativity, e.g., the variational principle for the Einstein equations, the event horizon and the apparent horizon of black holes, the formation of trapped…

General Relativity and Quantum Cosmology · Physics 2021-03-30 Emmanuele Battista , Giampiero Esposito

We discuss equivalent axiomatic characterizations of distortion risk measures, and give a novel and concise proof of the characterization of elicitable distortion risk measures. Elicitability has recently been discussed as a desirable…

Risk Management · Quantitative Finance 2014-05-27 Ruodu Wang , Johanna F. Ziegel

In this paper, we present a unified framework for decision making under uncertainty. Our framework is based on the composite of two risk measures, where the inner risk measure accounts for the risk of decision given the exact distribution…

Optimization and Control · Mathematics 2015-01-07 Pengyu Qian , Zizhuo Wang , Zaiwen Wen

In this paper, we introduce the rich classes of conditional distortion (CoD) risk measures and distortion risk contribution ($\Delta$CoD) measures as measures of systemic risk and analyze their properties and representations. The classes…

Risk Management · Quantitative Finance 2019-01-29 Jan Dhaene , Roger J. A. Laeven , Yiying Zhang

Since the quasiconvex risk measures is a bigger class than the well known convex risk measures, the study of quasiconvex risk measures makes sense especially in the financial markets with volatility. In this paper, we will study the…

Risk Management · Quantitative Finance 2019-06-26 Fei Sun , Yijun Hu

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

Uncertainty is prevalent in engineering design, data-driven problems, and decision making broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to address uncertainty by formulating and solving conservative…

Optimization and Control · Mathematics 2024-04-05 Johannes O. Royset

In this paper, we propose the multivariate range Value-at-Risk (MRVaR) and the multivariate range covariance (MRCov) as two risk measures and explore their desirable properties in risk management. In particular, we explain that such…

Statistics Theory · Mathematics 2023-05-17 Baishuai Zuo , Chuancun Yin , Jing Yao

Due to their heterogeneity, insurance risks can be properly described as a mixture of different fixed models, where the weights assigned to each model may be estimated empirically from a sample of available data. If a risk measure is…

Risk Management · Quantitative Finance 2018-02-12 Valeria Bignozzi , Claudio Macci , Lea Petrella

The family of admissible positions in a transaction costs model is a random closed set, which is convex in case of proportional transaction costs. However, the convexity fails, e.g. in case of fixed transaction costs or when only a finite…

Risk Management · Quantitative Finance 2021-01-15 Andreas Haier , Ilya Molchanov

We develop a general theory of risk measures that determines the optimal amount of capital to raise and invest in a portfolio of reference traded securities in order to meet a pre-specified regulatory requirement. The distinguishing feature…

Mathematical Finance · Quantitative Finance 2021-11-17 Maria Arduca , Cosimo Munari

Data depths are score functions that quantify in an unsupervised fashion how central is a point inside a distribution, with numerous applications such as anomaly detection, multivariate or functional data analysis, arising across various…

Machine Learning · Statistics 2025-07-14 Arturo Castellanos , Pavlo Mozharovskyi