GARCH models have been applied to option pricing with a good success. The main advantage of GARCH models is that the volatility dynamics can be characterized in imaginative ways. In fact, the family of GARCH models amounts to an infinite state space setups.
However, there is a drawback: In most GARCH option pricing models, no closed-form analytical solution for the option price is available and the price is available only through Monte Carlo simulation. This makes the model calibration computationally expensive, even if we use variance reduction techniques.
In his Global Derivatives Trading & Risk Management presentation, Associate Professor Juho Kanniainen shows how the performance of GARCH models can be assessed using distributed computing. With the accuracy used in the presentation, the calibration of the leverage model could take about 800 – 1200 hours of CPU time. When using the Techila Distributed Computing Engine, the total time will be reduced to 3-6 hours.