Reading the Smile: The Message Conveyed by Methods which Infer Risk Neutral Densities
Abstract
In this study, we compare the quality and information content of risk neutral densities obtained by various methods. We consider a non-parametric method based on a mixture of log-normal densities, the semi-parametric ones based on an Hermite approximation or based on an Edgeworth expansion, the parametric approach of Malz which assumes a jump-diffusion for the underlying process, and Heston's approach assuming a stochastic volatility model. We apply those models on FF/DM exchange rate options for two dates. Models differ when important news hits the market (here anticipated elections). The non-parametric model provides a good fit to options prices but is unable to provide as much information about market participants expectations than the jump-diffusion model.