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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/26888
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| Title: | Large Scale Conditional Covariance Matrix Modeling, Estimation and Testing |
| Authors: | Ding, Zhuanxin
Engle, Robert F. |
| Keywords: | conditional covariance
Multivariate ARCH
Hadamard product
M-test |
| Issue Date: | May-2001 |
| Series/Report no.: | S-DRP-01-07 |
| Abstract: | A new representation of the diagonal Vech model is given using the
Hadamard product. Sufficient conditions on parameter matrices are
provided to ensure the positive definiteness of covariance matrices from
the new representation. Based on this, some new and simple models are
discussed. A set of diagnostic tests for multivariate ARCH models is
proposed. The tests are able to detect various model misspecifications
by examing the orthogonality of the squared normalized residuals. A
small Monte-Carlo study is carried out to check the small sample
performance of the test. An empirical example is also given as guidance
for model estimation and selection in the multivariate framework. For
the specific data set considered, it is found that the simple one and
two parameter models and the constant conditional correlation model
perform fairly well. |
| URI: | http://hdl.handle.net/2451/26888 |
| Appears in Collections: | Derivatives Research
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