Testing for Changes in the Unconditional Variance of Financial Time Series
AbstractInclan 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 su.ers 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.
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Bibliographic InfoPaper provided by Universitat de les Illes Balears, Departament d'Economía Aplicada in its series DEA Working Papers with number 5.
Date of creation: Nov 2003
Date of revision:
ICSS; Changes in Variance; Kurtosis; ARCH; IGARCH.;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- G19 - Financial Economics - - General Financial Markets - - - Other
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