Implied volatility string dynamics

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 373 Discussion Paper ; No. 2003,54

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Asset Pricing; Trading Volume; Bond Interest Rates
• Subject: Implied Volatility Surface ; Smile ; Generalized Additive Models ; Backfitting ; Functional Principal Component Analysis

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Fengler, Matthias R. ; Härdle, Wolfgang ; Mammen, Enno
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
• (where): Berlin
• (when): 2003

Further information

• Handle: http://hdl.handle.net/10419/66280
• URN: urn:nbn:de:kobv:11-10050885
• Last update: 10.03.2025, 11:45 AM CET