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Titlebook: Probabilistic Constrained Optimization; Methodology and Appl Stanislav P. Uryasev Book 2000 Springer-Verlag US 2000 Computer.Finance.Multim

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书目名称Probabilistic Constrained Optimization
副标题Methodology and Appl
编辑Stanislav P. Uryasev
视频video
丛书名称Nonconvex Optimization and Its Applications
图书封面Titlebook: Probabilistic Constrained Optimization; Methodology and Appl Stanislav P. Uryasev Book 2000 Springer-Verlag US 2000 Computer.Finance.Multim
描述Probabilistic and percentile/quantile functions play animportant role in several applications, such as finance(Value-at-Risk), nuclear safety, and the environment. Recently,significant advances have been made in sensitivity analysis andoptimization of probabilistic functions, which is the basis forconstruction of new efficient approaches. This book presents the stateof the art in the theory of optimization of probabilistic functionsand several engineering and finance applications, including materialflow systems, production planning, Value-at-Risk, asset and liabilitymanagement, and optimal trading strategies for financial derivatives(options). ..Audience:. The book is a valuable source of information forfaculty, students, researchers, and practitioners in financialengineering, operation research, optimization, computer science, andrelated areas.
出版日期Book 2000
关键词Computer; Finance; Multimedia; Options; Simulation; Stochastic Optimization; calculus; computer science; mod
版次1
doihttps://doi.org/10.1007/978-1-4757-3150-7
isbn_softcover978-1-4419-4840-3
isbn_ebook978-1-4757-3150-7Series ISSN 1571-568X
issn_series 1571-568X
copyrightSpringer-Verlag US 2000
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发表于 2025-3-21 20:21:03 | 显示全部楼层
Structure of Optimal Stopping Strategies for American Type Options,ed as a price process and the second one as an index process controlling the price component. American type options with convex pay-off functions are studied. The structure optimal and ε-optimal buyer stopping strategies is investigated for various classes of convex pay-off functions.
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https://doi.org/10.1007/978-1-4757-3150-7Computer; Finance; Multimedia; Options; Simulation; Stochastic Optimization; calculus; computer science; mod
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978-1-4419-4840-3Springer-Verlag US 2000
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On the Numerical Solution of Jointly Chance Constrained Problems,This paper considers jointly chance constrained problems from the numerical point of view. The main numerical difficulties as well as techniques for overcoming these difficulties are discussed. The efficiency of the approach is illustrated by presenting computational results for large-scale jointly chance constrained test problems.
发表于 2025-3-23 01:03:46 | 显示全部楼层
Some Remarks on the Value-at-Risk and the Conditional Value-at-Risk,The value-at-risk (VaR) and the conditional value-at-risk (CVaR) are two commonly used risk measures. We state some of their properties and make a comparison. Moreover, the structure of the portfolio optimization problem using the VaR and CVaR objective is studied.
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