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Related papers: Adjusted Expected Shortfall

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We address the problem of estimating the expected shortfall risk of a financial loss using a finite number of i.i.d. data. It is well known that the classical plug-in estimator suffers from poor statistical performance when faced with…

Risk Management · Quantitative Finance 2026-02-13 Daniel Bartl , Stephan Eckstein

We study a non-concave optimization problem in which a financial company maximizes the expected utility of the surplus under a risk-based regulatory constraint. For this problem, we consider four different prevalent risk constraints…

Optimization and Control · Mathematics 2022-06-22 An Chen , Mitja Stadje , Fangyuan Zhang

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

The estimation of risk measures recently gained a lot of attention, partly because of the backtesting issues of expected shortfall related to elicitability. In this work we shed a new and fundamental light on optimal estimation procedures…

Risk Management · Quantitative Finance 2017-08-25 Marcin Pitera , Thorsten Schmidt

We derive new approximations for the Value at Risk and the Expected Shortfall at high levels of loss distributions with positive skewness and excess kurtosis, and we describe their precisions for notable ones such as for exponential, Pareto…

Risk Management · Quantitative Finance 2023-12-25 Matyas Barczy , Adam Dudas , Jozsef Gall

We introduce a method to estimate simultaneously the tail and the threshold parameters of an extreme value regression model. This standard model finds its use in finance to assess the effect of market variables on extreme loss distributions…

Methodology · Statistics 2023-04-17 Julien Hambuckers , Marie Kratz , Antoine Usseglio-Carleve

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

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up…

Economics · Quantitative Finance 2017-07-18 Andrew J. Patton , Johanna F. Ziegel , Rui Chen

This paper proposes a novel class of generalized Expected-Shortfall (ES) norms constructed via distortion risk measures, establishing a unified analytical framework for risk quantification. The proposed norms extend conventional ES…

Risk Management · Quantitative Finance 2025-07-15 Shuyu Gong , Taizhong Hu , Zhenfeng Zou

We present a general framework for a comparative theory of variability measures, with a particular focus on the recently introduced one-parameter families of inter-Expected Shortfall differences and inter-expectile differences, that are…

Risk Management · Quantitative Finance 2022-04-05 Fabio Bellini , Tolulope Fadina , Ruodu Wang , Yunran Wei

We address the problem of portfolio optimization under the simplest coherent risk measure, i.e. the expected shortfall. As it is well known, one can map this problem into a linear programming setting. For some values of the external…

Physics and Society · Physics 2008-12-02 Stefano Ciliberti , Imre Kondor , Marc Mezard

The contour map of estimation error of Expected Shortfall (ES) is constructed. It allows one to quantitatively determine the sample size (the length of the time series) required by the optimization under ES of large institutional portfolios…

Risk Management · Quantitative Finance 2015-02-24 Imre Kondor , Fabio Caccioli , Gábor Papp , Matteo Marsili

Expectiles define the only law-invariant, coherent and elicitable risk measure apart from the expectation. The popularity of expectile-based risk measures is steadily growing and their properties have been studied for independent data, but…

Methodology · Statistics 2021-10-13 Anthony C. Davison , Simone A. Padoan , Gilles Stupfler

We consider a multi-step algorithm for the computation of the historical expected shortfall such as defined by the Basel Minimum Capital Requirements for Market Risk. At each step of the algorithm, we use Monte Carlo simulations to reduce…

Computational Finance · Quantitative Finance 2020-05-27 Bruno Bouchard , Adil Reghai , Benjamin Virrion

Based on supermodularity ordering properties, we show that convex risk measures of credit losses are nondecreasing w.r.t. credit-credit and, in a wrong-way risk setup, credit-market, covariances of elliptically distributed latent factors.…

Risk Management · Quantitative Finance 2024-12-09 Dorinel Bastide , Stéphane Crépey

In financial risk management, Value at Risk (VaR) is widely used to estimate potential portfolio losses. VaR's limitation is its inability to account for the magnitude of losses beyond a certain threshold. Expected Shortfall (ES) addresses…

Risk Management · Quantitative Finance 2024-07-10 Federico Gatta , Fabrizio Lillo , Piero Mazzarisi

Maximum drawdown, the largest cumulative loss from peak to trough, is one of the most widely used indicators of risk in the fund management industry, but one of the least developed in the context of measures of risk. We formalize drawdown…

Portfolio Management · Quantitative Finance 2016-09-22 Lisa R. Goldberg , Ola Mahmoud

The paper discusses capital allocation using the Euler formula and focuses on the risk measures Value-at-Risk (VaR) and Expected shortfall (ES). Some new results connected to this capital allocation is known. Two examples illustrate that…

Risk Management · Quantitative Finance 2024-05-02 Lars Holden

Expected risk minimization (ERM) is at the core of many machine learning systems. This means that the risk inherent in a loss distribution is summarized using a single number - its average. In this paper, we propose a general approach to…

Machine Learning · Computer Science 2023-01-24 Christian Fröhlich , Robert C. Williamson

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