Latent jump diffusion factor estimation for commodity futures

Abstract We introduce a new methodology to estimate the latent factors of a jump diffusion illustrated with an application to the commodity futures term structure. Specifically, we propose a new state space form and then use a modified Kalman filter to estimate models with latent jump-diffusion factors. The method is applied to oil and copper futures prices to pin down long and short term jumps in their futures term structure. Estimates of jump arrival times indicate that both important information surprises and market activities generate jumps of different intensities.