Modeling the Dynamics of Implied Volatility Surfaces
31 Pages Posted: 26 Feb 2009 Last revised: 4 Apr 2010
Date Written: February 23, 2009
The purpose of this study is to model implied volatility surfaces and identify risk factors that account for most of the randomness in the volatility surfaces. The approach is similar to that of the Dumas, Fleming and Whaley (DFW) (1998) study. We use moneyness in implied forward price and out-of-the-money put-call options on the FTSE 100 stock index. After adjustments, a nonlinear parametric optimization technique is used to estimate different DFW models to characterize and produce smooth implied volatility surfaces. Next, principal component analysis is applied to the implied volatility surfaces to extract principal components that account for most of the dynamics in the shape of the surfaces. We then estimate and obtain smooth implied volatility surfaces with the parametric models that account for both smirk(skew) and time to maturity. We find the constant volatility model fails to explain the variations in the surfaces. However, the first three principal components (or factors) can explain about 69-88% of the variances in the implied volatility surfaces: in which on average 56% explains by the level factor, 15% by the term structure factor, and additional 7% by the jump-fear factor. The applications of our study can be in options trading, hedging of derivatives positions, risk management of options, and policy making.
Keywords: implied volatility, implied volatility surface, options, principal component analysis, smirk
JEL Classification: G13
Suggested Citation: Suggested Citation