压力VaR：一种新的优化配置风险概念

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摘要翻译：
本文介绍了一种新的基于非线性因素模型的风险估计方法--“压力风险”(SVaR)。SVaR是为了评估对冲基金的风险而发展起来的，它似乎适用于广泛的投资领域。它的原理是利用对冲基金回报的相当短和稀疏的历史，在一组非常广泛的可能风险来源中识别相关的风险因素。这种风险简介是通过校准一系列非线性单因素模型而不是单个多因素模型来获得的。然后，我们利用风险简介和这些因素的悠久而丰富的历史来评估已知的过去危机对基金的可能影响，揭示它们隐藏的风险和所谓的“黑天鹅”。在使用1060个对冲基金数据的回溯测试中，我们证明了SVaR比几个常见的VaR度量具有更好的或可比的属性--显示了更少的VaR例外，甚至更重要的是，在例外的情况下，以更小的数量。然而，对压力风险值的最终考验在于它作为资金分配工具的使用。通过模拟一个对冲基金投资组合的实际投资，我们发现使用压力VaR构建的投资组合的平均表现优于市场和使用普通VaR度量构建的投资组合。在2003年2月至2009年6月期间，StressVaR构建的投资组合每年超过市场约6%，平均超过竞争VaR指标约3%。2007年8月至2009年6月的业绩数字更是令人印象深刻。SVaR投资组合的表现优于市场20%，最佳竞争指标的表现优于市场4%。
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英文标题：
《The StressVaR: A New Risk Concept for Superior Fund Allocation》
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作者：
Cyril Coste, Raphael Douady, Ilija I. Zovko
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最新提交年份：
2009
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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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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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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  In this paper we introduce a novel approach to risk estimation based on nonlinear factor models - the "StressVaR" (SVaR). Developed to evaluate the risk of hedge funds, the SVaR appears to be applicable to a wide range of investments. Its principle is to use the fairly short and sparse history of the hedge fund returns to identify relevant risk factors among a very broad set of possible risk sources. This risk profile is obtained by calibrating a collection of nonlinear single-factor models as opposed to a single multi-factor model. We then use the risk profile and the very long and rich history of the factors to asses the possible impact of known past crises on the funds, unveiling their hidden risks and so called "black swans".   In backtests using data of 1060 hedge funds we demonstrate that the SVaR has better or comparable properties than several common VaR measures - shows less VaR exceptions and, perhaps even more importantly, in case of an exception, by smaller amounts.   The ultimate test of the StressVaR however, is in its usage as a fund allocating tool. By simulating a realistic investment in a portfolio of hedge funds, we show that the portfolio constructed using the StressVaR on average outperforms both the market and the portfolios constructed using common VaR measures.   For the period from Feb. 2003 to June 2009, the StressVaR constructed portfolio outperforms the market by about 6% annually, and on average the competing VaR measures by around 3%. The performance numbers from Aug. 2007 to June 2009 are even more impressive. The SVaR portfolio outperforms the market by 20%, and the best competing measure by 4%.
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PDF链接：
https://arxiv.org/pdf/0911.4030

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关键词：VaR Quantitative Applications Optimization Econophysics 例外 属性 hedge 情况 对冲