Quadratic hedging schemes for non-Gaussian GARCH models

被引:14
作者
Badescu, Alexandru [1 ]
Elliott, Robert J. [1 ,2 ]
Ortega, Juan-Pablo [3 ]
机构
[1] Univ Calgary, Dept Math & Stat, Calgary, AB T2N 1N4, Canada
[2] Univ Adelaide, Sch Math Sci, Adelaide, SA 5005, Australia
[3] Univ Franche Comte, CNRS, Dept Math Besancon, UFR Sci & Tech, F-25030 Besancon, France
关键词
GARCH models; Local risk minimization; Martingale measure; Bivariate diffusion limit; Minimum variance hedge; VARIANCE; OPTIONS; RISK;
D O I
10.1016/j.jedc.2014.03.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2014 Elsevier B.V. All rights reserved.
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页码:13 / 32
页数:20
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