Abstracts

We aim to calibrate stochastic volatility models from option prices. We develop a Tikhonov regularization approach and an efficient numerical algorithm to recover the stochastic volatility model. In contrast to most existing literature, we do not assume that the model has any special structure. As such, our algorithm applies to calibration of general stochastic volatility models. An extensive numerical analysis is presented to demonstrate the efficiency of our approach.