A0806
Title: Estimating Hawkes processes from observations of a sample path at discrete times points
Authors: Feng Chen - UNSW Syd (Australia) [presenting]
Abstract: Estimation of the Hawkes process from complete observations of a sample path is relatively straightforward using either the maximum likelihood or other methods. However, estimating the parameters of a Hawkes process from observations of a sample path at discrete time points only is challenging due to the intractability of the likelihood with such data. A method is introduced to estimate the Hawkes process from a discretely observed sample path. The work relies on a state-space representation of the problem and a sequence Monte Carlo (aka particle filtering) approximation to the likelihood function. The performance of the proposed method is evaluated using simulation experiments and it is compared with some recently published benchmark methods in the literature.
