Abstract
In this paper, we adopt a wavelet-based option pricing model and empirically compare its forecasting and hedging performance with that of other popular models, including the stochastic volatility model with jumps, the practitioner Black-Scholes model and the neural network based model. We use daily index options written on the German DAX 30 index from January 2009 to December 2012. Our results show that the wavelet-based model compares favorably with all other models except the neural network based one, especially for long-term options, and that it provides an excellent alternative for valuing option prices. Its strong performance comes from the powerful ability of the wavelet method in approximating the risk-neutral moment-generating functions.