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风险管理基础之风险矩阵法

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 【概念】
风险矩阵(RiskMetricsTM)的概念由J.P.Morgan提出,该模型以指数加权平均法来计算风险值,主要的核心在于计算观察值的权数会随着时间不同而异,也就是说距观察时点愈近其权数愈小。在FRM一级学习中,重要需要掌握的就GARCH 风险矩阵预测模型,它的公式是:
ht=λh(t-1)+(1-λ) (r (t-1) )2  ,
这里的r t-1是t-1时期的回报率,ht−1和ht分别是预测的t-1时期和t时期的方差,λ是指数延迟因子(decay factor)。在一级实际考察中,由于这个知识点知识了解层面,所以只需要记住公式,会运用公式就行。
【典型考题】:
[Single choice] You need to update a daily volatility forecast using the RiskMetricsTM exponential method with a decay factor of 0.97. Yesterday´s forecast of standard deviation was 1%.  Given that you just observed a return of 2%, what will be the new forecast of standard deviation?
A. 1.030%   B. 1.044%
C. 1.970%   D. 1.977%
答案:B
解析:风险矩阵模型来预测的公式为:ht=λh(t-1)+(1-λ) (r (t-1) )2
其中r t-1是t-1时期的回报率,ht−1和ht分别是预测的t-1时期和t时期的方差,λ是指数延迟因子,通过题目中的数据可以得到新的预测标准差为:
ht0.5=(0.97×0.012+(1-0.97)×0.022)0.5=1.044%.

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