B0186
Title: GMM estimation of stochastic volatility models using transform-based moments of derivatives prices
Authors: Yannick Dillschneider - University of Amsterdam (Netherlands) [presenting]
Raimond Maurer - Goethe University Frankfurt (Germany)
Abstract: Derivatives, especially equity and volatility options, contain valuable and oftentimes essential information for estimating stochastic volatility models. Absent strong assumptions, their typically highly nonlinear pricing dependence on the state vector prevents or at least severely impedes their inclusion into standard estimation approaches. A novel and unified methodology is developed to incorporate moments involving derivatives prices into a GMM estimation procedure. Invoking new results from generalized transform analysis, analytically tractable expressions are derived for exact moments and devise a computationally attractive approximation procedure. The methodology is exemplified by an estimation problem that jointly accounts for stock returns as well as prices of equity and volatility options. Finally, numerical results are provided that support the effectiveness of the methodology.
