Value at Risk
Value at Risk
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DOI：
10.3905/jod.1997.407975
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发表时间：
1996-06
期刊：
影响因子：
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通讯作者：
Chris Marshall;Michael Siegel
中科院分区：
文献类型：
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作者：
Chris Marshall;Michael Siegel
在最近的风险管理失败之后，人们普遍呼吁改进企业面临的金融风险的量化。站在这一呼声最前线的是风险价值（Value At Risk）。先前的研究已经确定了模型或模型风险的差异，这是开发风险价值标准的重要障碍。与此相反，本文考虑了模型在软件中实现时的分歧，以及它如何影响风险度量标准的建立。不同的领先风险管理系统的供应商被给予相同的不同复杂性的工具组合，并被要求根据一个共同的模型（J.P. Morgan的RiskMetrics™）评估风险价值。我们在个案基础上分析VaR结果，并根据投资组合中金融工具结构的先前预期，以及先前供应商对不同资产类别相对复杂性的预期。由此可见，本研究表明，一个特定的风险模型可以在多大程度上提前有效地指定，而不依赖于该模型在实践中的详细实施和使用。关键词：风险管理，金融服务，模型管理。这篇论文是在金融机构中心1996年10月关于“
In the wake of recent failures of risk management, there has been a widespread call for improved quantification of the financial risks facing firms. At the forefront of this clamor has been Value at Risk. Previous research has identified differences in models, or Model Risk, as an important impediment to developing a Value at Risk standard. By contrast, this paper considers the divergence in a model's implementation in software and how it too, affects the establishment of a risk measurement standard. Different leading risk management systems' vendors were given identical portfolios of instruments of varying complexity, and were asked to assess the value at risk according to one common model, J.P. Morgan's RiskMetrics™. We analyzed the VaR results on a case by case basis, and in terms of prior expectations from the structure of financial instruments in the portfolio, as well as prior vendor expectations about the relative complexity of different asset classes. It follows that this research indicates the extent to which one particular model of risk can be effectively specified in advance, independent of the model's detailed implementation and use in practice. Key words: Risk Management, Financial Services, Model Management. This paper was presented at the Financial Institutions Center's October 1996 conference on "