Implementation of DynamicSemiparametric Factor Model forImplied Volatilities

Abstract

Dynamic Semiparametric Factor Model (DSFM) is a convenient tool for analysis of implied volatility surfice (IVS). It offers dimension reduction of the IVS and can be therefore applied in hedging, prediction or risk mangement. However the estimation of the DSFM parameters is a complex procedure since it requires huge number of observation. Therefore the efficient implementation is a key issue for application possibilites of this model. In this master thesis we discuss implementation issues of DSFM. We describe key features of the model and present its implementation in statistical computing enviroment XploRe.