Testing for changes in the unconditional variance of financial time series

Abstract

[eng] Inclan and Tiao (1994) proposed a test for the detection of changes of the unconditional variance which has been used in financial time series analysis. In this article we show some serious drawbacks for using this test with this type of data. Specifically, it suffers important size distortions for leptokurtic and platykurtic innovations. Moreover, the size distortions are more extreme for heteroskedastic conditional variance processes. These results invalidate in practice the use of the test for financial time series. To overcome these problems we propose new tests that explicitly consider the fourth moment properties of the disturbances and the conditional heteroskedasticity. Monte Carlo experiments show the good performance of these tests. The application of the new tests to the same series in Aggarwal, Inclan and Leal (1999) reveal that the changes in variance they detect are spurious.