Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
417558 | Computational Statistics & Data Analysis | 2012 | 12 Pages |
Abstract
Goodness-of-fit and symmetry tests are proposed for the innovation distribution in generalized autoregressive conditionally heteroscedastic models. The tests utilize an integrated distance involving the empirical characteristic function (or the empirical Laplace transform) computed from properly standardized observations. A bootstrap version of the tests serves the purpose of studying the small sample behaviour of the proclaimed procedures in comparison with more classical approaches. Finally, all tests are applied to some financial data sets.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
B. Klar, F. Lindner, S.G. Meintanis,