报告时间: 2017年6月9日(周五), 上午10:00
报告主题: Simultaneous Specification Testing for Nonlinear Time Series Models
This paper proposes a simultaneous test for the specification of the conditional mean and conditional variance functions as well as the error distribution in nonlinear time series models. Constructed by comparing two different density estimators for the response variable, the proposed test has a Gumbel limiting distribution under the null hypothesis and is consistent against a general class of alternative hypotheses. A parametric bootstrap procedure is proposed to approximate its finite sample distribution. The proposed test is shown to have nice performances in extensive simulations. The application to the continuous time diffusion model is illustrated via an analysis on the U.S. Federal fund rate data. This is a joint work with Bin Guo and Yundong Tu.