Acceso usuarios
Inclan and Tiao (1994) proposed a test for the detection of changes in unconditional variance which has been used in financial time series analyses. In this article we demonstrate some serious drawbacks to the test when used with this type of data. More specifically, it has big size distortions for leptokurtic and platykurtic innovations. Moreover, the size distortions are more extreme for heteroskedastic conditional variance processes. These results invalidate the test's practical use for financial time series. To overcome these problems, we propose new tests that take the fourth order moment properties of disturbances and conditional heteroskedasticity into explicit account. Monte Carlo experiments demonstrate the better performance of these tests. The new tests' application to the same series in Aggarwal, Inclan and Leal (1999) reveal that the changes in variance they detect are spurious.
