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In this paper we propose a problem-driven scenario generation approach to the single-period portfolio selection problem which use tail risk measures such as conditional value-at-risk. Tail risk measures are useful for quantifying potential…

Risk Management · Quantitative Finance 2019-11-14 Jamie Fairbrother , Amanda Turner , Stein Wallace

The estimation of loss distributions for dynamic portfolios requires the simulation of scenarios representing realistic joint dynamics of their components. We propose a novel data-driven approach for simulating realistic, high-dimensional…

Risk Management · Quantitative Finance 2025-05-19 Rama Cont , Mihai Cucuringu , Renyuan Xu , Chao Zhang

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

A novel forecast combination and weighted quantile based tail-risk forecasting framework is proposed, aiming to reduce the impact of modelling uncertainty in tail-risk forecasting. The proposed approach is based on a two-step estimation…

Risk Management · Quantitative Finance 2021-07-20 Giuseppe Storti , Chao Wang

Value-at-risk (VaR) has been playing the role of a standard risk measure since its introduction. In practice, the delta-normal approach is usually adopted to approximate the VaR of portfolios with option positions. Its effectiveness,…

Methodology · Statistics 2019-04-22 Junyao Chen , Tony Sit , Hoi Ying Wong

Scenario generation is the construction of a discrete random vector to represent parameters of uncertain values in a stochastic program. Most approaches to scenario generation are distribution-driven, that is, they attempt to construct a…

Optimization and Control · Mathematics 2021-05-21 Jamie Fairbrother , Amanda Turner , Stein Wallace

Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures…

Risk Management · Quantitative Finance 2011-07-14 Mikhail Voropaev

A method for quantile-based, semi-parametric historical simulation estimation of multiple step ahead Value-at-Risk (VaR) and Expected Shortfall (ES) models is developed. It uses the quantile loss function, analogous to how the…

Statistical Finance · Quantitative Finance 2025-03-06 Richard Gerlach , Antonio Naimoli , Giuseppe Storti

Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all the trades with each counterparty under both market and credit risk. We present a multi-Gaussian process regression approach,…

Computational Finance · Quantitative Finance 2019-10-18 Stéphane Crépey , Matthew Dixon

Value at Risk (VaR) and stress testing are two of the most widely used approaches in portfolio risk management to estimate potential market value losses under adverse market moves. VaR quantifies potential loss in value over a specified…

Computational Finance · Quantitative Finance 2024-10-01 Krishan Mohan Nagpal

Aggregate Risk Analysis is a computationally intensive and a data intensive problem, thereby making the application of high-performance computing techniques interesting. In this paper, the design and implementation of a parallel Aggregate…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-10 Blesson Varghese , Andrew Rau-Chaplin

We account for time-varying parameters in the conditional expectile-based value at risk (EVaR) model. The EVaR downside risk is more sensitive to the magnitude of portfolio losses compared to the quantile-based value at risk (QVaR). Rather…

Statistical Finance · Quantitative Finance 2020-09-29 Xiu Xu , Andrija Mihoci , Wolfgang Karl Härdle

In order to estimate the conditional risk of a portfolio's return, two strategies can be advocated. A multivariate strategy requires estimating a dynamic model for the vector of risk factors, which is often challenging, when at all…

Econometrics · Economics 2019-09-12 Christian Francq , Jean-Michel Zakoian

This paper proposes a semiparametric joint VaRES framework driven by realized information, mo tivated by the economic mechanisms underlying tail risk generation. Building on the CAViaR quantile recursion, the model introduces a dynamic…

General Economics · Economics 2026-01-06 Sicheng Fu

This paper considers the specification of covariance structures with tail estimates. We focus on two aspects: (i) the estimation of the VaR-CoVaR risk matrix in the case of larger number of time series observations than assets in a…

Econometrics · Economics 2023-07-25 Christis Katsouris

Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures…

Risk Management · Quantitative Finance 2010-08-02 Mikhail Voropaev

This report presents a comprehensive evaluation of three Value-at-Risk (VaR) modeling approaches: Historical Simulation (HS), GARCH with Normal approximation (GARCH-N), and GARCH with Filtered Historical Simulation (FHS), using both…

Risk Management · Quantitative Finance 2025-10-06 Xin Tian

Determining contributions by sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often economic capital is measured as Value-at-Risk (VaR) of the portfolio loss…

Statistics Theory · Mathematics 2009-06-18 Dirk Tasche

This paper proposes analytic forms of portfolio CoVaR and CoCVaR on the normal tempered stable market model. Since CoCVaR captures the relative risk of the portfolio with respect to a benchmark return, we apply it to the relative portfolio…

Portfolio Management · Quantitative Finance 2023-03-29 Young Shin Kim

The dynamic portfolio construction problem requires dynamic modeling of the joint distribution of multivariate stock returns. To achieve this, we propose a dynamic generative factor model which uses random variable transformation as an…

Portfolio Management · Quantitative Finance 2024-01-18 Chuting Sun , Qi Wu , Xing Yan
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