A suggestion for estimating large multivariate conditional covariance matricies april 2017.pdf (752.19 kB)
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A suggestion for constructing a large time-varying conditional covariance matrix

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journal contribution
posted on 13.06.2017, 12:16 by Heather D. Gibson, Stephen G. Hall, George S. Tavlas
The construction of large conditional covariance matrices has posed a problem in the empirical literature because the direct extension of the univariate GARCH model to a multivariate setting produces large numbers of parameters to be estimated as the number of equations rises. A number of procedures have previously aimed to simplify the model and restrict the number of parameters, but these procedures typically involve either invalid or undesirable restrictions. This paper suggests an alternative way forward, based on the GARCH approach, which allows conditional covariance matrices of unlimited size to be constructed. The procedure is computationally straightforward to implement. At no point in the procedure is it necessary to estimate anything other than a univariate GARCH model.

History

Citation

Economics Letters, 2017, 156, pp. 110-113

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/Department of Economics

Version

AM (Accepted Manuscript)

Published in

Economics Letters

Publisher

Elsevier

issn

0165-1765

Acceptance date

20/04/2017

Copyright date

2017

Available date

28/04/2019

Publisher version

http://www.sciencedirect.com/science/article/pii/S0165176517301684

Notes

The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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