We reformulate the Lévy-Kintchine formula to make it suitable for modelling the stochastic time-changing effects of Lévy processes. Using Variance-Gamma (VG) process as an example, it illustrates the dynamic properties of a Lévy process and revisits the earlier work of Geman (2002). It also shows how the model can be calibrated to price options under a Lévy VG process, and calibrates the model on recent S&P500 index options data. It then compares the pricing performance of Fast Fourier Transform (FFT) and Fractional Fourier Transform (FRFT) approaches to model calibration and investigates the trade-off between calibration performance and required calculation time
