Robust and Powerful Tests for Nonlinear Deterministic Components
提出一种基于傅里叶级数展开的检验方法，用于检测单变量时间序列中的非线性确定性成分，该方法对序列的积分阶数和弱依赖具有渐近稳健性，且比现有检验具有更高的局部渐近功效。
Abstract We develop a test for the presence of nonlinear deterministic components in a univariate time series, approximated using a Fourier series expansion, designed to be asymptotically robust to the order of integration of the process and to any weak dependence present. We show that our proposed test has uniformly greater local asymptotic power than the existing tests of Harvey, Leybourne and Xiao (2010) when the shocks are I(1), identical local asymptotic power when the shocks are I(0), and also improved finite sample properties. We also consider the issue of determining the number of Fourier frequencies used to specify any nonlinear deterministic components.