The Impact of Jump Dynamics on the Predictive Power of Option-implied Densities

This study examines whether incorporating jumps with stochastic volatility can improve the predictive power of option-implied densities of the FTSE 100 index. A general double-jump model, as proposed by Duffie et al. (2000), is used to fit the market prices of options and to estimate 'risk-neutral' densities. 'Real-world' densities are then converted from their risk-neutral form by means of alternative statistical calibrations. Both the risk-neutral and real-world densities are evaluated, over five forecast horizons, using two different tests. Our empirical results indicate that adding jumps into the price and/or volatility processes not only substantially lowers the fitting errors of option prices, but also improves the predictive power of risk-neutral densities. Furthermore, satisfactory density prediction was consistently provided by the real-world densities, which were not dependent on the addition of jumps, the approach used to construct the densities, or the prediction horizon