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, 2000 In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics and high-frequency duration models) and non-parametric (empirical quantile, extreme distributions models) Value-at-Risk (VaR) techniques to intraday data for three stocks traded on the NewY ork Stock Exchange.
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Hedging Conditional Value at Risk with Options [PDF]
, 2015 We present a method of hedging Conditional Value at Risk of a position in stock using put options. The result leads to a linear programming problem that can be solved to optimise risk hedging.Comment: 10 pages, 0 ...
Capiński, Maciej J.
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Multi-Variate Risk Measures under Wasserstein Barycenter
Risks, 2022 When the uni-variate risk measure analysis is generalized into the multi-variate setting, many complex theoretical and applied problems arise, and therefore the mathematical models used for risk quantification usually present model risk.
M. Andrea Arias-Serna +2 more
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Journal of Modern Power Systems and Clean Energy, 2019 In power market environment, the growing importance of demand response (DR) and renewable energy source (RES) attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.
Tirthadip Ghose +2 more
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THE ROLE OF VALUE AT RISK IN THE MANAGEMENT OF ASSET AND LIABILITIES [PDF]
Annals of the University of Oradea: Economic Science, 2012 ALM is the management of risk at enterprise level, the models used in ALM can be static or dynamic: single period-static models, multiple period static model, single period stochastic model, multi period stochastic model. While single period-static don't
Petria Nicolae +2 more
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The Journal of Risk Finance, 2010 Value at risk (VaR) is one of the most widely used models in risk management. It is based on probability and statistics. VaR can be characterized as a maximum expected loss, given some time horizon and within a given confidence interval. Its utility is in providing a measure of risk that illustrates the risk inherent in a portfolio with multiple risk ...
Christian Gourieroux, Joann Jasiak
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Optimal reinsurance designs based on risk measures: a review
Statistical Theory and Related Fields, 2020 Reinsurance is an effective way for an insurance company to control its risk. How to design an optimal reinsurance contract is not only a key topic in actuarial science, but also an interesting research question in mathematics and statistics.
Jun Cai, Yichun Chi
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Presenting a Model for Multiple-Step-Ahead-Forecasting of Volatility and Conditional Value at Risk in Fossil Energy Markets [PDF]
AUT Journal of Modeling and Simulation, 2018 Fossil energy markets have always been known as strategic and important markets. They have a significant impact on the macro economy and financial markets of the world.
E. Mohammadian Amiri, S. B. Ebrahimi
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Markov-Switching GARCH Modelling of Value-at-RisK [PDF]
, 2008 This paper proposes an asymmetric Markov regime-switching (MS) GARCH model to estimate value-at-risk (VaR) for both long and short positions. This model improves on existing VaR methods by taking into account both regime change and skewness or leverage ...
Coakley, J, Nankervis, JC, Sajjad, R
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Classification of methods for risk measures VaR and CVaR calculation and estimation
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2016 A systematic classification of the existing approaches for popular risk measures VaR and CVaR calculating and estimating is fulfilled. A review of the most used methods is done.
Nataliia G. Zrazhevska, A. G. Zrazhevsky
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