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Stochastic dominance and risk measure: A decision-theoretic foundation for VaR and C-VaR

机译:随机优势和风险衡量:VaR和C-VaR的决策理论基础

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Is it possible to obtain an objective and quantifiable measure of risk backed up by choices made by some specific groups of rational investors? To answer this question, in this paper we establish some behavior foundations for various types of VaR models, including VaR and conditional-VaR, as measures of downside risk. In this paper, we will establish some logical connections among VaRs, conditional-VaR, stochastic dominance, and utility maximization. Though supported to some extents with unanimous choices by some specific groups of expected or non-expected-utility investors, VaRs as profiles of risk measures at various levels of risk tolerance are not quantifiable - they can only provide partial and incomplete risk assessments for risky prospects. We also include in our discussion the relevant VaRs and several alternative risk measures for investors; these alternatives use somewhat weaker assumptions about risk-averse behavior by incorporating a mean-preserving-spread. For this latter group of investors, we provide arguments for and against the standard deviation versus VaR and conditional-VaRs as objective and quantifiable measures of risk in the context of portfolio choice.
机译:是否可以通过一些特定的理性投资者群体的选择来获得客观,可量化的风险支持措施?为了回答这个问题,在本文中,我们为各种类型的VaR模型建立了一些行为基础,包括VaR和有条件的VaR,作为衡量下行风险的方法。在本文中,我们将在VaR,条件VaR,随机支配地位和效用最大化之间建立一些逻辑联系。尽管某些特定类别的预期或非预期效用投资者在某种程度上获得了某些特定群体的支持,但无法量化VaR作为处于不同风险承受力水平的风险度量的概况,它们只能为有风险的潜在客户提供部分和不完整的风险评估。我们还将讨论相关的风险价值和针对投资者的几种替代风险衡量方法;这些选择通过合并均值保持点差,使用了对风险规避行为的较弱假设。对于后一组投资者,我们提供了支持和反对标准偏差与VaR和条件VaR的论点,以作为在投资组合选择背景下客观,可量化的风险度量。

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