Results 21 to 30 of about 141,957 (261)
Statistical Learning with Conditional Value at Risk
CoRR, 2020 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 gradient descent for this framework.
Tasuku Soma, Yuichi Yoshida
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Incorporating stand level risk management options into forest decision support systems
Forest Systems, 2018 Aim of study: To examine methods of incorporating risk and uncertainty to stand level forest decisions. Area of study: A case study examines a small forest holding from Jönköping, Sweden.
Kyle Eyvindson +2 more
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Optimization with Multivariate Conditional Value-at-Risk Constraints [PDF]
Operations Research, 2013 For many decision-making problems under uncertainty, it is crucial to develop risk-averse models and specify the decision makers' risk preferences based on multiple stochastic performance measures (or criteria). Incorporating such multivariate preference rules into optimization models is a fairly recent research area.
Nilay Noyan, Gábor Rudolf
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Optimizing conditional value-at-risk in dynamic pricing [PDF]
OR Spectrum, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jochen Gönsch +2 more
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Asset Allocation with Conditional Value-at-Risk Budgets [PDF]
SSRN Electronic Journal, 2012 Risk budgets are frequently used to allocate the risk of a portfolio by decomposing the total portfolio risk into the risk contribution of each component position. Many approaches to portfolio allocation use ex post methods for constructing risk budgets and take the variance as a risk measure.
Boudt, Kris +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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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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Conditional Value-at-Risk: Aspects of Modeling and Estimation [PDF]
SSRN Electronic Journal, 2001 This paper considers flexible conditional (regression) measures of market risk. Value-at-Risk modeling is cast in terms of the quantile regression function – the inverse of the conditional distribution function. A basic specification analysis relates its functional forms to the benchmark models of returns and asset pricing.
Chernozhukov, Victor, Umantsev, Len
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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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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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