We explore the pricing performance of Support Vector Regression for pricing S&P 500 index call options.
We combine parametric models and feedforward artificial neural networks to price and trade European S&P500 Index options. Artificial neural networks are optimised on a hybrid target function consisted by the standardised residual term between the actual market price and the option estimate of a certain parametric model.
In this paper we compare the predictive ability of the Black-Scholes Formula (BSF) and Artificial Neural Networks (ANNs) to price call options by exploiting historical volatility measures.
