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We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in a classic expected return maximization problem. For what we call the infimum of expectations class of risk measures, we show…

Risk Management · Quantitative Finance 2009-06-19 Laetitia Andrieu , Michel De Lara , Babacar Seck

The probabilistic satisfiability of a logical expression is a fundamental concept known as the partition function in statistical physics and field theory, an evaluation of a related graph's Tutte polynomial in mathematics, and the…

Discrete Mathematics · Computer Science 2022-06-09 Stephen Eubank , Madhurima Nath , Yihui Ren , Abhijin Adiga

In risk management, often the probability must be estimated that a random vector falls into an extreme failure set. In the framework of bivariate extreme value theory, we construct an estimator for such failure probabilities and analyze its…

Methodology · Statistics 2015-06-04 Holger Drees , Laurens de Haan

Recently, the concept of tail dependence has been discussed in financial applications related to market or credit risk. The multivariate extreme value theory is a proper tool to measure and model dependence, for example, of large loss…

Applications · Statistics 2011-09-27 Marta Ferreira

The purpose of this paper is to give a selective survey on recent progress in random metric theory and its applications to conditional risk measures. This paper includes eight sections. Section 1 is a longer introduction, which gives a…

Risk Management · Quantitative Finance 2011-03-18 Tiexin Guo

We prove the large deviation principle for several entropy and cross entropy estimators based on return times and waiting times on shift spaces over finite alphabets. We consider shift-invariant probability measures satisfying some…

Probability · Mathematics 2024-08-07 Noé Cuneo , Renaud Raquépas

We study time-consistency questions for processes of monetary risk measures that depend on bounded discrete-time processes describing the evolution of financial values. The time horizon can be finite or infinite. We call a process of…

Probability · Mathematics 2008-12-10 Patrick Cheridito , Freddy Delbaen , Michael Kupper

We consider the problem of adaptive inference on a regression function at a point under a multivariate nonparametric regression setting. The regression function belongs to a H\"older class and is assumed to be monotone with respect to some…

Statistics Theory · Mathematics 2020-12-01 Koohyun Kwon , Soonwoo Kwon

Assumptions on a likelihood function, including a local Glivenko-Cantelli condition, imply the existence of M-estimators converging to an M-functional. Scatter matrix-valued estimators, defined on all empirical measures on ${\Bbb{R}}^d$ for…

Statistics Theory · Mathematics 2007-06-13 R. M. Dudley

We consider (robust) inference in the context of a factor model for tensor-valued sequences. We study the consistency of the estimated common factors and loadings space when using estimators based on minimising quadratic loss functions.…

Methodology · Statistics 2023-08-29 Matteo Barigozzi , Yong He , Lingxiao Li , Lorenzo Trapani

We investigate large deviations properties for centered stationary AR(1) and MA(1) processes with independent Gaussian innovations, by giving the explicit bivariate rate functions for the sequence of random vectors $(\boldsymbol{S}_n)_{n…

Probability · Mathematics 2021-02-22 M. J. Karling , A. O. Lopes , S. R. C. Lopes

We extend the duality between exponential integrals and relative entropy to a variational formula for exponential integrals involving the Renyi divergence. This formula characterizes the dependence of risk-sensitive functionals and related…

Probability · Mathematics 2013-10-25 Rami Atar , Kamaljit Chowdhary , Paul Dupuis

This article studies an integral representation of functionals of linear growth on metric measure spaces with a doubling measure and a Poincar\'e inequality. Such a functional is defined through relaxation, and it defines a Radon measure on…

Functional Analysis · Mathematics 2014-01-23 Heikki Hakkarainen , Juha Kinnunen , Panu Lahti , Pekka Lehtelä

We establish necessary and sufficient conditions for the N-representability of the universal one-electron reduced density matrix functional. Functionals satisfying these conditions are guaranteed to yield variational upper bounds on the…

Quantum Physics · Physics 2026-04-08 Jannis Erhard , Paul W. Ayers

In this paper we introduce a biparametric family of transformations which can be seen as an extension of the so-called up and down transformations. This new class of transformations allows to us to introduce new informational functionals,…

Information Theory · Computer Science 2025-11-05 Razvan Gabriel Iagar , David Puertas-Centeno

Motivated by questions in lossy data compression and by theoretical considerations, we examine the problem of estimating the rate-distortion function of an unknown (not necessarily discrete-valued) source from empirical data. Our focus is…

Information Theory · Computer Science 2013-01-18 M. T. Harrison , I. Kontoyiannis

We show in this paper that many risk measures arising in Actuarial Sciences, Finance, Medicine, Welfare analysis, etc. are garthered in classes of Weighted Mean Loss or Gain (WMLG) statistics. Some of them are Upper Threshold Based (UTH) or…

Methodology · Statistics 2014-05-23 Gane Samb Lo , Serigne Touba Sall , Pape Djiby Mergane

We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle. We provide numerical results along with efficient and…

Mathematical Finance · Quantitative Finance 2020-11-03 Chloe Lacombe , Aitor Muguruza , Henry Stone

The behavior of maximum likelihood estimates (MLEs) and the likelihood ratio statistic in a family of problems involving pointwise nonparametric estimation of a monotone function is studied. This class of problems differs radically from the…

Statistics Theory · Mathematics 2009-09-29 Moulinath Banerjee

A large deviations principle is established for the joint law of the empirical measure and the flow measure of a renewal Markov process on a finite graph. We do not assume any bound on the arrival times, allowing heavy tailed distributions.…

Probability · Mathematics 2014-02-18 Mauro Mariani , Lorenzo Zambotti
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