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Autoren: 
Fengler, Matthias R.
Härdle, Wolfgang
Mammen, Enno
Datum: 
2003
Schriftenreihe/Nr.: 
SFB 373 Discussion Paper No. 2003,54
Zusammenfassung: 
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 naïve trader models. The model can be a backbone in risk management serving for value at risk computations and scenario analysis.
Schlagwörter: 
Implied Volatility Surface
Smile
Generalized Additive Models
Backfitting
Functional Principal Component Analysis
JEL: 
C14
G12
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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