Option Implied Volatility Estimation:A Computational Intelligent Approach

摘要：

Generally,option implied volatility is estimated by the inverse function of the Black-Scholes formula.The structure of Black-Scholes formula is fixed and it can not updated with new information.Therefore,in this paper,the Least Square Support Vector Machine (LSSVM) model,a novel version of Neural Networks,is proposed to estimate optionsimplied volatility.It has excellent performance in approximation of complex functions.In the end,Hang Seng Index options are used to verify the performance of the LSSVM.

关键词： implied volatility Black-Scholes model Least Square Support Vector Machine Hung Seng Index option

作者: Stanley CHOI Gang DONG Kin Keung LAI

作者单位: Head & Shoulders Securities Limited Hong Kong,SAR Department of Management Sciences City University of Hong Kong Hong Kong,SAR Department of Management Sciences City University of ong Kong Hong Kong,SAR

会议类型: 国际会议

会议名称: The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

会议地点: 昆明、丽江

会议语种:英文

页码: 545-547

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）