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We study a static portfolio optimization problem with two risk measures: a principle risk measure in the objective function and a secondary risk measure whose value is controlled in the constraints. This problem is of interest when it is…

Portfolio Management · Quantitative Finance 2020-12-14 Çağın Ararat

This paper is the continuation of "Pricing with coherent risk" and deals with further applications of coherent risk measures to problems of finance. First, we study the optimization problem. Three forms of this problem are considered.…

Probability · Mathematics 2008-12-10 Alexander S. Cherny

We study invariant measures for random countable (finite or infinite) conformal iterated function systems (IFS) with arbitrary overlaps. We do not assume any type of separation condition. We prove, under a mild assumption of finite entropy,…

Dynamical Systems · Mathematics 2015-03-24 Eugen Mihailescu , Mariusz Urbanski

This paper concerns sequential computation of risk measures for financial data and asks how, given a risk measurement procedure, we can tell whether the answers it produces are `correct'. We draw the distinction between `external' and…

Risk Management · Quantitative Finance 2015-11-20 Mark H. A. Davis

We introduce the formalism of generalized Fourier transforms in the context of risk management. We develop a general framework to efficiently compute the most popular risk measures, Value-at-Risk and Expected Shortfall (also known as…

Risk Management · Quantitative Finance 2012-05-08 G. Bormetti , V. Cazzola , G. Livan , G. Montagna , O. Nicrosini

In multiple importance sampling we combine samples from a finite list of proposal distributions. When those proposal distributions are used to create control variates, it is possible (Owen and Zhou, 2000) to bound the ratio of the resulting…

Computation · Statistics 2014-11-18 Hera Y. He , Art B. Owen

Risk measures for random vectors have been considered in multi-asset markets with transaction costs and financial networks in the literature. While the theory of set-valued risk measures provide an axiomatic framework for assigning to a…

Risk Management · Quantitative Finance 2024-07-25 Çağın Ararat , Zachary Feinstein

The left tail of the implied volatility skew, coming from quotes on out-of-the-money put options, can be thought to reflect the market's assessment of the risk of a huge drop in stock prices. We analyze how this market information can be…

Risk Management · Quantitative Finance 2016-08-16 Ronnie Sircar , Stephan Sturm

In performative prediction, predictions guide decision-making and hence can influence the distribution of future data. To date, work on performative prediction has focused on finding performatively stable models, which are the fixed points…

Machine Learning · Computer Science 2021-06-17 John Miller , Juan C. Perdomo , Tijana Zrnic

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

Law-invariant functionals are central to risk management and assign identical values to random prospects sharing the same distribution under an atomless reference probability measure. This measure is typically assumed fixed. Here, we adopt…

Risk Management · Quantitative Finance 2026-02-10 Felix-Benedikt Liebrich , Ruodu Wang

This paper deals with multidimensional dynamic risk measures induced by conditional $g$-expectations. A notion of multidimensional $g$-expectation is proposed to provide a multidimensional version of nonlinear expectations. By a technical…

Risk Management · Quantitative Finance 2012-03-09 Yuhong Xu

We introduce set risk measures (SRMs), real-valued maps defined on the family of non-empty closed bounded sets of essentially bounded random variables. SRMs extend traditional scalar risk measures by assigning a single capital requirement…

Mathematical Finance · Quantitative Finance 2026-05-20 Marcelo Righi , Eduardo Horta , Marlon Moresco

Score-based generative modeling, informally referred to as diffusion models, continue to grow in popularity across several important domains and tasks. While they provide high-quality and diverse samples from empirical distributions,…

Machine Learning · Statistics 2023-12-29 Jacopo Teneggi , Matthew Tivnan , J. Webster Stayman , Jeremias Sulam

Generalized variational inference (GVI) provides an optimization-theoretic framework for statistical estimation that encapsulates many traditional estimation procedures. The typical GVI problem is to compute a distribution of parameters…

Optimization and Control · Mathematics 2023-10-27 Aurya S. Javeed , Drew P. Kouri , Thomas M. Surowiec

The paper analyzes risk assessment for cash flows in continuous time using the notion of convex risk measures for processes. By combining a decomposition result for optional measures, and a dual representation of a convex risk measure for…

Probability · Mathematics 2013-04-18 Irina Penner , Anthony Reveillac

We propose a multivariate extension of a well-known characterization by S. Kusuoka of regular and coherent risk measures as maximal correlation functionals. This involves an extension of the notion of comonotonicity to random vectors…

Theoretical Economics · Economics 2021-02-09 Ivar Ekeland , Alfred Galichon , Marc Henry

In this paper we present a theoretical framework for studying coherent acceptability indices in a dynamic setup. We study dynamic coherent acceptability indices and dynamic coherent risk measures, and we establish a duality between them. We…

Risk Management · Quantitative Finance 2011-05-23 Tomasz R. Bielecki , Igor Cialenco , Zhao Zhang

Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set…

Risk Management · Quantitative Finance 2017-09-12 Çağın Ararat , Andreas H. Hamel , Birgit Rudloff

Let $F$ be a finite model of cardinality $M$ and denote by $\operatorname {conv}(F)$ its convex hull. The problem of convex aggregation is to construct a procedure having a risk as close as possible to the minimal risk over $\operatorname…

Statistics Theory · Mathematics 2013-12-17 Guillaume Lecué
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