Panel versus GARCH information in unit root testing with an application to financial markets

In a search for more powerful unit root tests, some researchers have recently proposed accounting for the information contained in the GARCH of the innovations. However, while promising, tests with GARCH are difficult to implement, which has made them quite uncommon in the empirical literature. A computationally attractive alternative is to account not for GARCH but the information contained in a panel of multiple time series. The purpose of the current note is to compare the relative power achievable from these two information sources. © 2014 Elsevier B.V.

A GARCH model for testing market efficiency

In this paper we propose a generalised autoregressive conditional heteroskedasticity (GARCH) model-based test for a unit root. The model allows for two endogenous structural breaks. We test for unit roots in 156 US stocks listed on the NYSE over the period 1980 to 2007. We find that the unit root null hypothesis is rejected in 40% of the stocks, and only in four out of the nine sectors the null is rejected for over 50% of stocks. We conclude with an economic significance analysis, showing that mostly stocks with mean reverting prices tend to outperform stocks with non-stationary prices.