50 Pages Posted: 29 Jul 2011 Last revised: 10 Jun 2017
Date Written: June 9, 2017
Point processes are widely used in finance and economics to model the timing of defaults, market transactions, unemployment spells, births, and a range of other events. We develop and analyze likelihood estimators for the parameters of a marked point process and incompletely observed explanatory factors that influence the arrival intensity and mark distribution. We establish an approximation to the likelihood and analyze the convergence and large-sample properties of the associated estimators. Numerical results illustrate the behavior of our estimators.
Keywords: point process, filtering, parametric maximum likelihood, asymptotic theory, likelihood approximation
Suggested Citation: Suggested Citation