26 Pages Posted: 27 Sep 2012 Last revised: 13 May 2014
Date Written: September 26, 2012
We propose different schemes for option hedging when asset returns are modeled using a general class of GARCH models. More specifically, we implement local risk minimization and a minimum variance hedge approximation based on an extended Girsanov principle that generalizes Duan's (1995) delta hedge. Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a pricing kernel. These approaches are investigated in the context of non-Gaussian driven models. Furthermore, we analyze these methods for non-Gaussian GARCH diffusion limit processes and link them to the corresponding discrete time counterparts. A detailed numerical analysis based on S&P 500 European Call options is provided to assess the empirical performance of the proposed schemes. We also test the sensitivity of the hedging strategies with respect to the risk neutral measure used by recomputing some of our results with an exponential affine pricing kernel.
Keywords: GARCH models, hedging scheme, local risk minimization, conditional Esscher transform, Extended Girsanov Principle, bivariate diffusion limit, minimum variance hedge
JEL Classification: C22, C32, C5
Suggested Citation: Suggested Citation
Badescu, Alex and Elliott, Robert J. and Ortega, Juan-Pablo, Quadratic Hedging Schemes for Non-Gaussian GARCH Models (September 26, 2012). Journal of Economic Dynamics and Control, Vol. 32, 13-32, 2014. Available at SSRN: https://ssrn.com/abstract=2152462 or http://dx.doi.org/10.2139/ssrn.2152462