Common Functional Implied Volatility Analysis
AbstractTrading, hedging and risk analysis of complex option portfolios depend on accurate pricing models. The modelling of implied volatilities (IV) plays an important role, since volatility is the crucial parameter in the Black-Scholes (BS) pricing formula. It is well known from empirical studies that the volatilities implied by observed market prices exhibit patterns known as volatility smiles or smirks that contradict the assumption of constant volatility in the BS pricing model. On the other hand, the IV is a function of two parameters: the strike price and the time to maturity and it is desirable in practice to reduce the dimension of this object and characterize the IV surface through a small number of factors. Clearly, a dimension reduced pricing-model that should reflect the dynamics of the IV surface needs to contain factors and factor loadings that characterize the IV surface itself and their movements across time.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2005-012.
Length: 22 pages
Date of creation: Mar 2005
Date of revision:
implied volatility; Black-Scholes; option portfolio; pricing;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- G19 - Financial Economics - - General Financial Markets - - - Other
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-03-11 (All new papers)
- NEP-ETS-2006-03-11 (Econometric Time Series)
- NEP-FIN-2006-03-11 (Finance)
- NEP-FMK-2006-03-11 (Financial Markets)
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- Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Tamine, Julien & Čížek, Pavel & Härdle, Wolfgang, 2002.
"Smoothed L-estimation of regression function,"
SFB 373 Discussion Papers
2002,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
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