基于人工智能的隐含波动率的敏感度的研究

隐含波动率是指在市场中观察的期权价格所蕴涵的波动率。不同种类的期权价格对波动率的敏感度不同,本文建立了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,本文所提出的模型要优于传统的Black-Scholes模型和其它在本文中提到的神经网络模型。

Study on the Sensitivity of Implied volatility Based on Artificial Intelligence

Implied volatility is the volatility implied by an option price observed in the market.The sensi- tivity of the volatility among varied kinds of option price ise different.In this work,we build hybrid fore- casting models combining wavelet neural network with genetic algorithm.Using these models,option par- tition according to moneyness is applied and weighted implied volatility measures are regarded as input of the neural network.The genetic algorithm is used to determine the optimal weight of the implied ...