Option Implied Volatility Estimation: A Computational Intelligent Approach
Stanley Choi, Gang Dong, Kin Keung Lai · 2011
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 options' implied 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.