An Efficient Calibration Method for a Stochastic Volatility L?vy Model

The purpose of this paper is to provide an efficient calibration method for a stochastic volatility lévy model which is a popular option pricing model. By minimizing the error between the vanilla option price and the corresponding market price the model is calibrated. Regularization by adding a penalty function to the square error term assures uniqueness and stability of solution. The model and calibration method are applied to the S&P 500 index options. The performance of the model is tested by the percentage of the mean price and the average relative percentage error. Results show that the calibration approach has perfect stability.