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The negative externalities from an individual bank failure to the whole system can be huge. One of the key purposes of bank regulation is to internalize the social costs of potential bank failures via capital charges. This study proposes a…

General Finance · Quantitative Finance 2014-04-24 Xiaobing Feng , Haibo Hu

Reliability-oriented sensitivity analysis aims at combining both reliability and sensitivity analyses by quantifying the influence of each input variable of a numerical model on a quantity of interest related to its failure. In particular,…

Statistics Theory · Mathematics 2022-10-25 Julien Demange-Chryst , François Bachoc , Jérôme Morio

The quantification of diversification benefits due to risk aggregation plays a prominent role in the (regulatory) capital management of large firms within the financial industry. However, the complexity of today's risk landscape makes a…

Risk Management · Quantitative Finance 2009-12-19 Matthias Degen , Dominik D. Lambrigger , Johan Segers

The existing approaches to sparse wealth allocations (1) are limited to low-dimensional setup when the number of assets is less than the sample size; (2) lack theoretical analysis of sparse wealth allocations and their impact on portfolio…

Econometrics · Economics 2021-04-27 Ekaterina Seregina

The risk of financial positions is measured by the minimum amount of capital to raise and invest in eligible portfolios of traded assets in order to meet a prescribed acceptability constraint. We investigate nondegeneracy, finiteness and…

Risk Management · Quantitative Finance 2014-03-05 Walter Farkas , Pablo Koch-Medina , Cosimo Munari

We study resource allocation in two-sided markets from a fundamental perspective and introduce a general modeling and algorithmic framework to effectively incorporate the complex and multidimensional aspects of fairness. Our main technical…

Computer Science and Game Theory · Computer Science 2025-06-03 Javier Cembrano , Andrés Moraga , Victor Verdugo

We study the consistency of sample mean-variance portfolios of arbitrarily high dimension that are based on Bayesian or shrinkage estimation of the input parameters as well as weighted sampling. In an asymptotic setting where the number of…

Portfolio Management · Quantitative Finance 2015-05-30 Francisco Rubio , Xavier Mestre , Daniel P. Palomar

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is the single largest and most detailed scientific effort ever conducted to quantify levels and trends in health. This global health model to estimate mortality rates and…

The Basel II internal ratings-based (IRB) approach to capital adequacy for credit risk implements an asymptotic single risk factor (ASRF) model. Measurements from the ASRF model of the prevailing state of Australia's economy and the level…

Risk Management · Quantitative Finance 2016-07-26 Silvio Tarca , Marek Rutkowski

We consider a variation on the classical finance problem of optimal portfolio design. In our setting, a large population of consumers is drawn from some distribution over risk tolerances, and each consumer must be assigned to a portfolio of…

This paper explores the applications of the 20/60/20 rule-a heuristic method that segments data into top-performing, average-performing, and underperforming groups-in mathematical finance. We review the statistical foundations of this rule…

Portfolio Management · Quantitative Finance 2025-04-07 Kewin Pączek , Damian Jelito , Marcin Pitera , Agnieszka Wyłomańska

Risk control and optimal diversification constitute a major focus in the finance and insurance industries as well as, more or less consciously, in our everyday life. We present a discussion of the characterization of risks and of the…

Statistical Mechanics · Physics 2015-06-25 Didier Sornette

This article develops the theory of risk budgeting portfolios, when we would like to impose weight constraints. It appears that the mathematical problem is more complex than the traditional risk budgeting problem. The formulation of the…

Portfolio Management · Quantitative Finance 2019-02-18 Jean-Charles Richard , Thierry Roncalli

In the context of risk measures, the capital allocation problem is widely studied in the literature where different approaches have been developed, also in connection with cooperative game theory and systemic risk. Although static capital…

Probability · Mathematics 2023-05-17 Emanuela Rosazza Gianin , Marco Zullino

Robust optimization provides a principled framework for decision-making under uncertainty, with broad applications in finance, engineering, and operations research. In portfolio optimization, uncertainty in expected returns and covariances…

Statistical Finance · Quantitative Finance 2025-10-15 Daniel Cunha Oliveira , Grover Guzman , Nick Firoozye

Evaluations of generative AI models often collapse nuanced behaviour into a single number computed for a single decoding configuration. Such point estimates obscure tail risks, demographic disparities, and the existence of multiple…

Artificial Intelligence · Computer Science 2026-01-23 Yanan Long

We propose a variant of the Shapley value, the group Shapley value, to interpret counterfactual simulations in structural economic models by quantifying the importance of different components. Our framework compares two sets of parameters,…

Econometrics · Economics 2024-10-10 Yongchan Kwon , Sokbae Lee , Guillaume A. Pouliot

We consider settings in which the distribution of a multivariate random variable is partly ambiguous. We assume the ambiguity lies on the level of the dependence structure, and that the marginal distributions are known. Furthermore, a…

Mathematical Finance · Quantitative Finance 2020-05-27 Stephan Eckstein , Michael Kupper , Mathias Pohl

This paper focuses on the study of an original combination of the Multilevel Monte Carlo method introduced by Giles [10] and the popular importance sampling technique. To compute the optimal choice of the parameter involved in the…

Probability · Mathematics 2017-09-05 Mohamed Ben Alaya , Kaouther Hajji , Ahmed Kebaier

Basel II and Solvency 2 both use the Value-at-Risk (VaR) as the risk measure to compute the Capital Requirements. In practice, to calibrate the VaR, a normal approximation is often chosen for the unknown distribution of the yearly log…

Methodology · Statistics 2013-11-04 Marie Kratz
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