Wavelet variance ratio cointegration test and wavestrapping

Abstract

In this paper, we propose a wavelet-based cointegration test for fractionally integrated time series. The proposed test is nonparametric and asymptotically invariant to different forms of short-run dynamics. The use of wavelets allows us to take advantage of the wavelet-based bootstrapping method mainly known as wavestrapping. In this regard, we introduce to the literature a new wavestrapping algorithm for multivariate time series processes specifically for cointegration tests. The Monte Carlo simulations indicate that this new wavestrapping procedure can alleviate the severe size distortions which we generally observe in cointegration tests with time series containing innovations that possess highly negative moving average roots.