英文标题：
《Process-Based Risk Measures and Risk-Averse Control of Discrete-Time
Systems》
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作者：
Jingnan Fan, Andrzej Ruszczynski
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最新提交年份：
2016
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英文摘要：
For controlled discrete-time stochastic processes we introduce a new class of dynamic risk measures, which we call process-based. Their main features are that they measure risk of processes that are functions of the history of a base process. We introduce a new concept of conditional stochastic time consistency and we derive the structure of process-based risk measures enjoying this property. We show that they can be equivalently represented by a collection of static law-invariant risk measures on the space of functions of the state of the base process. We apply this result to controlled Markov processes and we derive dynamic programming equations.
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中文摘要：
对于受控离散随机过程，我们引入了一类新的动态风险度量，我们称之为基于过程的风险度量。它们的主要特点是，它们衡量的是作为基本流程历史函数的流程的风险。我们引入了一个新的条件随机时间一致性概念，并推导了基于过程的风险度量的结构。我们证明了它们可以等价地表示为基过程状态函数空间上的一组静态律不变风险测度。我们将这个结果应用于受控马尔可夫过程，并导出了动态规划方程。
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分类信息：

一级分类：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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