英文标题：
《Tail Risk Constraints and Maximum Entropy》
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作者：
Donald Geman, H\\\'elyette Geman, and Nassim Nicholas Taleb
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最新提交年份：
2014
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英文摘要：
  In the world of modern financial theory, portfolio construction has traditionally operated under at least one of two central assumptions: the constraints are derived from a utility function and/or the multivariate probability distribution of the underlying asset returns is fully known. In practice, both the performance criteria and the informational structure are markedly different: risk-taking agents are mandated to build portfolios by primarily constraining the tails of the portfolio return to satisfy VaR, stress testing, or expected shortfall (CVaR) conditions, and are largely ignorant about the remaining properties of the probability distributions. As an alternative, we derive the shape of portfolio distributions which have maximum entropy subject to real-world left-tail constraints and other expectations. Two consequences are (i) the left-tail constraints are sufficiently powerful to overide other considerations in the conventional theory, rendering individual portfolio components of limited relevance; and (ii) the \"barbell\" payoff (maximal certainty/low risk on one side, maximum uncertainty on the other) emerges naturally from this construction.
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中文摘要：
在现代金融理论界，投资组合构建通常至少在两个中心假设中的一个下进行：约束来自效用函数和/或基本资产回报的多元概率分布是完全已知的。在实践中，绩效标准和信息结构明显不同：承担风险的代理人被要求通过主要限制投资组合回报的尾部来构建投资组合，以满足VaR、压力测试或预期短缺（CVaR）条件，并且基本上不知道概率分布的剩余属性。作为替代方案，我们推导了在真实世界的左尾约束和其他期望下具有最大熵的投资组合分布的形状。两个后果是（i）左尾约束足够强大，足以超越传统理论中的其他考虑，使得单个投资组合组成部分的相关性有限；（ii）“杠铃”回报（一方面是最大确定性/低风险，另一方面是最大不确定性）自然从这种结构中产生。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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