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The value-at-risk of a delta-gamma approximated derivatives portfolio can be computed by numerical integration of the characteristic function. However, while the choice of parameters in any numerical integration scheme is paramount, in…

Applications · Statistics 2014-02-27 Johannes Vitalis Siven , Jeffrey Todd Lins , Anna Szymkowiak-Have

In this paper we propose a multivariate quantile regression framework to forecast Value at Risk (VaR) and Expected Shortfall (ES) of multiple financial assets simultaneously, extending Taylor (2019). We generalize the Multivariate…

Risk Management · Quantitative Finance 2021-07-19 Luca Merlo , Lea Petrella , Valentina Raponi

This paper introduces a novel approach to financial risk assessment by incorporating topological data analysis (TDA), specifically cohomology groups, into the evaluation of equities portfolios. The study aims to go beyond traditional risk…

Risk Management · Quantitative Finance 2023-10-30 Amit Kumar Jha

Credit Value Adjustment (CVA) is the difference between the value of the default-free and credit-risky derivative portfolio, which can be regarded as the cost of the credit hedge. Default probabilities are therefore needed, as input…

Mathematical Finance · Quantitative Finance 2018-06-21 Ola Hammarlid , Marta Leniec

We develop a risk-averse safety analysis method for stochastic systems on discrete infinite time horizons. Our method quantifies the notion of risk for a control system in terms of the severity of a harmful random outcome in a fraction of…

Systems and Control · Electrical Eng. & Systems 2022-03-14 Chuanning Wei , Michael Fauss , Margaret P. Chapman

The present article is devoted to the semi-parametric estimation of multivariate expectiles for extreme levels. The considered multivariate risk measures also include the possible conditioning with respect to a functional covariate,…

Statistics Theory · Mathematics 2023-03-30 Elena Di Bernardino , Thomas Laloë , Cambyse Pakzad

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

This paper tackles the risk averse multi-armed bandits problem when incurred losses are non-stationary. The conditional value-at-risk (CVaR) is used as the objective function. Two estimation methods are proposed for this objective function…

Machine Learning · Computer Science 2021-09-30 Leo Benac , Frédéric Godin

We consider an optimal investment and risk control problem for an insurer under the mean-variance (MV) criterion. By introducing a deterministic auxiliary process defined forward in time, we formulate an alternative time-consistent problem…

Portfolio Management · Quantitative Finance 2021-01-12 Yang Shen , Bin Zou

Conditional Value-at-Risk (CVaR) is a widely used risk metric in applications such as finance. We derive concentration bounds for CVaR estimates, considering separately the cases of light-tailed and heavy-tailed distributions. In the…

Machine Learning · Computer Science 2019-08-27 Prashanth L. A. , Krishna Jagannathan , Ravi Kumar Kolla

Systemic risk measures quantify the potential risk to an individual financial constituent arising from the distress of entire financial system. As a generalization of two widely applied risk measures, Value-at-Risk and Expected Shortfall,…

Methodology · Statistics 2025-11-24 Qingzhao Zhong , Yanxi Hou

This paper presents a new method to compute VaR (value at risk) and perform corresponding variance based sensitivity analysis. VaR has a long history of being applied in stock price prediction and investment portfolio analysis. Traditional…

Applications · Statistics 2015-03-19 Wendy Li

In todays global economy, accuracy in predicting macro-economic parameters such as the foreign the exchange rate or at least estimating the trend correctly is of key importance for any future investment. In recent times, the use of…

Statistical Finance · Quantitative Finance 2020-02-25 Manav Kaushik , A K Giri

In this article, we combine replication pricing with expectation pricing for derivative trades that are partially collateralized by cash. The derivatives are replicated by underlying assets and cash, using repurchasing agreement (repo) and…

Pricing of Securities · Quantitative Finance 2013-02-05 Lixin Wu

The geology of oil reservoirs is largely unknown. Consequently, the reservoir models used for production optimization are subject to significant uncertainty. To minimize the associated risk, the oil literature has mainly used ensemble-based…

Optimization and Control · Mathematics 2018-01-03 Andrea Capolei , Lasse Hjuler Christiansen , John Bagterp Jørgensen

In real-world scenarios, risk-averse learning is valuable for mitigating potential adverse outcomes. However, the delayed feedback makes it challenging to assess and manage risk effectively. In this paper, we investigate risk-averse…

Machine Learning · Computer Science 2025-08-06 Siyi Wang , Zifan Wang , Karl Henrik Johansson , Sandra Hirche

Monitoring downside risk and upside risk to the key macroeconomic indicators is critical for effective policymaking aimed at maintaining economic stability. In this paper I propose a parametric framework for modelling and forecasting…

Econometrics · Economics 2023-11-21 Andrea Renzetti

Motivated by the equations of cross valuation adjustments (XVAs) in the realistic case where capital is deemed fungible as a source of funding for variation margin, we introduce a simulation/regression scheme for a class of anticipated…

Risk Management · Quantitative Finance 2024-01-25 Lokman Abbas-Turki , Stéphane Crépey , Botao Li , Bouazza Saadeddine

There are various metrics for financial risk, such as value at risk (VaR), expected shortfall, expected/unexpected loss, etc. When estimating these metrics, it was very common to assume Gaussian distribution for the asset returns, which may…

Applications · Statistics 2020-02-17 Shuguang Zhang , Minjing Tao , Xu-Feng Niu , Fred Huffer

This paper studies optimization of Conditional Value-at-Risk (CVaR) for Markov Decision Processes (MDPs) with finite state and action sets. It introduces the Dynamically augmented CVaR (DCVaR) risk measure and provides an algorithm for its…

Optimization and Control · Mathematics 2026-03-12 Eugene A. Feinberg , Rui Ding