中文摘要：

由于波动率微笑的存在,不同种类的期权的隐含波动率不同,如何衡量不同种类期权的隐含波动率的最优权重一直是期权定价领域中的重要问题.提出了新的基于Black-Scholes模型的混合小波神经网络,建立了混合小波神经网络和遗传算法相结合的模型,将期权按钱性进行分类,提出了加权的隐含波动率作为神经网络的输入变量,通过遗传算法来求取不同种类期权的隐含波动率的最优权重.在香港衍生品市场的实证中表明,所提出的模型要优于传统的Black-Scholes模型和其它的神经网络模型.

英文摘要：

The implied volatility rates of varied kinds of options are different because of volatility smile effects.How to determine the optimal weights of the implied volatility rates of varied kinds of options is an important issue in option pricing.A hybrid wavelet neural network based on the Black-Scholes model is proposed in this paper,and some hybrid forecasting models combining the hybrid wavelet neural network and genetic algorithm are built.In such an approach options are classified according to their moneyn...