Implied Volatility String Dynamics
Implied Volatility String Dynamics
复制标题
隐含波动率字符串动态
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
E. Mammen
中科院分区：
文献类型：
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作者：
Matthias R. Fengler;W. Härdle;E. Mammen
对隐含波动率表面(IVS)的动态进行建模的一个主要目标是降低复杂性。为此，我们每天都要对IVS进行拟合，并使用函数范数进行主成分分析。然而，这种方法忽略了隐含波动率数据的退化字符串结构，可能导致严重的建模偏差。我们提出了一种动态半参数因子模型，它在有限维函数空间中逼近IVS。其主要特点是，我们只适合在局部邻域的设计点。我们的方法是泛函主成分分析方法和加性模型的回代技术的结合。与典型的朴素交易者模型相比，该模型的性能提高了近10%。该模型可以作为风险管理的中坚力量，为风险价值计算和情景分析服务。
A primary goal in modelling the dynamics of implied volatility surfaces (IVS) aims at reducing complexity. For this purpose one fits the IVS each day and applies a principal component analysis using a functional norm. This approach, however, neglects the degenerated string structure of the implied volatility data and may result in a severe modelling bias. We propose a dynamic semiparametric factor model, which approximates the IVS in a finite dimensional function space. The key feature is that we only fit in the local neighborhood of the design points. Our approach is a combination of methods from functional principal component analysis and backfitting techniques for additive models. The model is found to have an approximate 10% better performance than the typical naive trader models. The model can be a backbone in risk management serving for value at risk computations and scenario analysis.