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To provide a solid analytic foundation for the module approach to conditional risk measures, this paper establishes a complete random convex analysis over random locally convex modules by simultaneously considering the two kinds of…

Functional Analysis · Mathematics 2013-08-03 Tiexin Guo , Shien Zhao , Xiaolin Zeng

In this paper, we continue to study random convex analysis. First, we introduce the notion of an $L^0$--pre--barreled module. Then, we develop the theory of random duality under the framework of a random locally convex module endowed with…

Functional Analysis · Mathematics 2015-11-11 Tiexin Guo , Shien Zhao , Xiaolin Zeng

To provide a solid analytic foundation for the module approach to conditional risk measures, our purpose is to establish a complete random convex analysis over random locally convex modules by simultaneously considering the two kinds of…

Functional Analysis · Mathematics 2015-11-11 Tiexin Guo , Shien Zhao , Xiaolin Zeng

Based on the idea of randomizing the traditional space theory of functional analysis, random functional analysis has been developed as functional analysis over random metric spaces, random normed modules and random locally convex modules.…

Functional Analysis · Mathematics 2026-03-31 Tiexin Guo , Qiang Tu , Xiaohuan Mu , Yuanyuan Sun

Recently, based on the idea of randomizing space theory, random convex analysis has been being developed in order to deal with the corresponding problems in random environments such as analysis of conditional convex risk measures and the…

Functional Analysis · Mathematics 2017-09-11 Tiexin Guo , Erxin Zhang , Mingzhi Wu , Bixuan Yang , George Yuan , Xiaolin Zeng

Optimization of conditional convex risk measure is a central theme in dynamic portfolio selection theory, which has not yet systematically studied in the previous literature perhaps since conditional convex risk measures are neither random…

Optimization and Control · Mathematics 2019-10-24 Tiexin Guo

The purpose of this paper is to make a comprehensive connection between the basic results and properties derived from the two kinds of topologies (namely the $(\epsilon,\lambda)-$topology introduced by the author and the stronger locally…

Functional Analysis · Mathematics 2010-06-22 Tiexin Guo

Our paper contributes to the theory of conditional risk measures and conditional certainty equivalents. We adopt a random modular approach which proved to be effective in the study of modular convex analysis and conditional risk measures.…

Mathematical Finance · Quantitative Finance 2022-11-10 Giulio Principi , Fabio Maccheroni

This paper gives an overview of the theory of dynamic convex risk measures for random variables in discrete time setting. We summarize robust representation results of conditional convex risk measures, and we characterize various time…

Risk Management · Quantitative Finance 2010-02-22 Beatrice Acciaio , Irina Penner

We study combinations of risk measures under no restrictive assumption on the set of alternatives. We develop and discuss results regarding the preservation of properties and acceptance sets for the combinations of risk measures. One of the…

Mathematical Finance · Quantitative Finance 2023-05-09 Marcelo Brutti Righi

By means of the techniques of Boolean valued analysis, we provide a transfer principle between duality theory of classical convex risk measures and duality theory of conditional risk measures. Namely, a conditional risk measure can be…

Functional Analysis · Mathematics 2019-10-09 José Miguel Zapata

Mean-deviation models, along with the existing theory of coherent risk measures, are well studied in the literature. In this paper, we characterize monotonic mean-deviation (risk) measures from a general mean-deviation model by applying a…

Risk Management · Quantitative Finance 2024-08-12 Xia Han , Ruodu Wang , Qinyu Wu

Locally $L^0$-convex modules were introduced in [D. Filipovic, M. Kupper, N. Vogelpoth. Separation and duality in locally $L^0$-convex modules. J. Funct. Anal. 256(12), 3996-4029 (2009)] as the analytic basis for the study of conditional…

Functional Analysis · Mathematics 2017-01-04 José Orihuela , José Miguel Zapata

We establish strong duality relations for functional two-step compositional risk-constrained learning problems with multiple nonconvex loss functions and/or learning constraints, regardless of nonconvexity and under a minimal set of…

Machine Learning · Computer Science 2023-12-05 Dionysis Kalogerias , Spyridon Pougkakiotis

We show that a wide class of risk-constrained nonconvex functional optimization problems exhibit strong duality, regardless of nonconvexity. We develop two novel results under distinct sets of assumptions, establishing strong duality over…

Optimization and Control · Mathematics 2025-11-17 Dionysis Kalogerias , Spyridon Pougkakiotis

We axiomatically introduce risk-consistent conditional systemic risk measures defined on multidimensional risks. This class consists of those conditional systemic risk measures which can be decomposed into a state-wise conditional…

Risk Management · Quantitative Finance 2016-09-27 Hannes Hoffmann , Thilo Meyer-Brandis , Gregor Svindland

Expanding on techniques of concentration of measure, we develop a quantitative framework for modeling liquidity risk using convex risk measures. The fundamental objects of study are curves of the form $(\rho(\lambda X))_{\lambda \ge 0}$,…

Risk Management · Quantitative Finance 2015-10-28 Daniel Lacker

In this article, we propose a novel characterization of law-invariant and coherent risk measures, based on a generalized optimal transport problem in which the second marginal of the admissible plans is not fixed, but required to lie within…

Optimization and Control · Mathematics 2025-12-23 Riccardo Bonalli , Benoît Bonnet-Weill , Laurent Pfeiffer

Geometrically convex functions constitute an interesting class of functions obtained by replacing the arithmetic mean with the geometric mean in the definition of convexity. As recently suggested, geometric convexity may be a sensible…

Risk Management · Quantitative Finance 2024-03-12 Mücahit Aygün , Fabio Bellini , Roger J. A. Laeven

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
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