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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

Designing dynamic portfolio insurance strategies under market conditions switching between two or more regimes is a challenging task in financial economics. Recently, a promising approach employing the value-at-risk (VaR) measure to assign…

Computational Finance · Quantitative Finance 2023-05-23 Peyman Alipour , Ali Foroush Bastani

Value-at-Risk (VaR) is an institutional measure of risk favored by financial regulators. VaR may be interpreted as a quantile of future portfolio values conditional on the information available, where the most common quantile used is 95%.…

Risk Management · Quantitative Finance 2016-05-18 Khizar Qureshi

In this paper we discuss a general methodology to compute the market risk measure over long time horizons and at extreme percentiles, which are the typical conditions needed for estimating Economic Capital. The proposed approach extends the…

Risk Management · Quantitative Finance 2014-08-12 Luca Spadafora , Marco Dubrovich , Marcello Terraneo

Risk measures are important key figures to measure the adequacy of the reserves of a company. The most common risk measures in practice are Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). Recently, quantum-based algorithms are…

Quantum Physics · Physics 2025-01-29 Christian Laudagé , Ivica Turkalj

In this paper we consider Fourier transform techniques to efficiently compute the Value-at-Risk and the Conditional Value-at-Risk of an arbitrary loss random variable, characterized by having a computable generalized characteristic…

Risk Management · Quantitative Finance 2015-06-01 Alessandro Ramponi

This paper addresses the ``curse of dimensionality'' in the loss valuation of credit risk models. A dimension reduction methodology based on the Bayesian filter and smoother is proposed. This methodology is designed to achieve a fast and…

Computational Engineering, Finance, and Science · Computer Science 2024-01-02 Jian He , Asma Khedher , Peter Spreij

We propose a risk-averse statistical learning framework wherein the performance of a learning algorithm is evaluated by the conditional value-at-risk (CVaR) of losses rather than the expected loss. We devise algorithms based on stochastic…

Machine Learning · Computer Science 2020-02-17 Tasuku Soma , Yuichi Yoshida

Estimation of the value-at-risk (VaR) of a large portfolio of assets is an important task for financial institutions. As the joint log-returns of asset prices can often be projected to a latent space of a much smaller dimension, the use of…

Machine Learning · Computer Science 2021-12-06 Robert Sicks , Stefanie Grimm , Ralf Korn , Ivo Richert

The Solvency II Directive and Solvency Assessment and Management (the South African equivalent) give a Solvency Capital Requirement which is based on a 99.5% Value-at-Risk (VaR) calculation. This calculation involves aggregating individual…

Applications · Statistics 2018-04-06 Sean van der Merwe , Darren Steven , Martinette Pretorius

Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo…

General Economics · Economics 2020-11-17 Seyed Mohammad Sina Seyfi , Azin Sharifi , Hamidreza Arian

This paper explores option portfolio optimization when the underlying returns are skew-elliptical t-distributed. We use the variance and value at risk (VaR) to measure portfolio risk. The novelty of our work is the departure from the…

Portfolio Management · Quantitative Finance 2026-05-01 Kyle Sung , Traian A. Pirvu

The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the…

Portfolio Management · Quantitative Finance 2020-07-21 Kei Nakagawa , Shuhei Noma , Masaya Abe

Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are two risk measures which are widely used in the practice of risk management. This paper deals with the problem of computing both VaR and CVaR using stochastic approximation (with…

Computational Finance · Quantitative Finance 2010-12-06 Olivier Aj Bardou , Noufel Frikha , G. Pagès

By mid 2004, the Basel Committee on Banking Supervision (BCBS) is epected to launch its final recommendations on minimum capital requirements in the banking industry. Although there is the intention to arrive at capital charges which concur…

Other Condensed Matter · Physics 2008-12-02 Dirk Tasche , Ursula Theiler

The joint Value at Risk (VaR) and expected shortfall (ES) quantile regression model of Taylor (2017) is extended via incorporating a realized measure, to drive the tail risk dynamics, as a potentially more efficient driver than daily…

Risk Management · Quantitative Finance 2018-05-23 Richard Gerlach , Chao Wang

Determining risk contributions of unit exposures to portfolio-wide economic capital is an important task in financial risk management. Computing risk contributions involves difficulties caused by rare-event simulations. In this study, we…

Risk Management · Quantitative Finance 2019-01-18 Takaaki Koike , Mihoko Minami

Recent financial disasters emphasised the need to investigate the consequence associated with the tail co-movements among institutions; episodes of contagion are frequently observed and increase the probability of large losses affecting…

Methodology · Statistics 2013-11-05 Mauro Bernardi , Ghislaine Gayraud , Lea Petrella

This paper presents analytical solutions to the problem of how to calculate sensible VaR (Value-at-Risk) and ES (Expected Shortfall) contributions in the CreditRisk+ methodology. Via the ES contributions, ES itself can be exactly computed…

Condensed Matter · Physics 2011-08-09 Alexandre Kurth , Dirk Tasche

A new realized conditional autoregressive Value-at-Risk (VaR) framework is proposed, through incorporating a measurement equation into the original quantile regression model. The framework is further extended by employing various Expected…

Risk Management · Quantitative Finance 2021-01-18 Chao Wang , Richard Gerlach , Qian Chen