考虑股票收益率在GARCH模型下的非正态特征,以及收益率标准差序列的非对称特征,首先给出几种真实测度下服从Levy分布的条件异方差模型,接着对随机扰动项和波动率进行风险中性调整,最后通过蒙特卡罗模拟进行大陆和香港权证的实证.结果表明:Levy过程修正下的GJR-GARCH模型能够很好地捕捉到金融数据“跳跃特征”、“群聚现象”和“杠杆效应”.同时,该模型显著提升了权证的定价精度.市场间对比显示,香港权证的定价精度高于大陆权证,且大陆权证的市场价格显著偏离无套利假设下的理论价值.
GARCH models with filtered historical innovations in option pricing gain a large number of important researches, we introduce asymmetric GARCH and non-normal Levy into this model based on "fat tail", skewness and other statistical characteristic of financial data. We build several GARCH models with Levy random numbers under physical measure, and then we transform heteroscedasticity sequence into risk neutral measure. Through the empirical Monte-Carlo pricing method in Mainland warrants market and Hong Kong warrants market, we demonstrate this method can improve pricing precision significant, the "leverage effect" and "clustering effect" of volatility are well reflected, by comparing pricing results between these two warrant markets, we demonstrate Hong Kong warrant market is more effective.