Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6869943 | Computational Statistics & Data Analysis | 2014 | 18 Pages |
Abstract
The predictive power of recently introduced components affecting correlations is investigated. The focus is on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover, models allowing the correlation dynamics to be subjected to regime-shift caused by threshold-based structural breaks of a different nature are also considered. The results indicate that in some cases there may be a superimposition of the long-term and short-term movements in correlations. Therefore, care is called for in interpretations when estimating the two components. Testing the forecasting accuracy of correlations during the late-2000s financial crisis yields mixed results. In general, component models allowing for a richer correlation specification possess an increased predictive accuracy. Economically speaking, no relevant gains are found by allowing for more flexibility in the correlation dynamics.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Francesco Audrino,