Projects per year
Abstract
The family of multiplicative error models is important for studying non-negative variables such as realized volatility, trading volume, and duration between consecutive financial transactions. Methods are developed for testing the parametric specification of a multiplicative error model, which consists of separate parametric models for the conditional mean and the error distribution. The same method can also be used for testing the specification of the error distribution provided the conditional mean is correctly specified. A bootstrap method is proposed for computing the p-values of the tests and is shown to be consistent. The proposed tests have nontrivial asymptotic power against a class of O(n -1/2)-local alternatives. The tests performed well in a simulation study, and they are illustrated using a data example on realized volatility.
Original language | English |
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Pages (from-to) | 413-438 |
Number of pages | 26 |
Journal | Econometric Theory |
Volume | 33 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Apr 2017 |
Projects
- 1 Finished
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Robust methods for heteroscedastic regression models for time series
Silvapulle, M. (Primary Chief Investigator (PCI)), La Vecchia, D. (Chief Investigator (CI)) & Hallin, M. (Partner Investigator (PI))
Australian Research Council (ARC), Monash University, Universität St. Gallen (University of St Gallen), European Centre for Advanced Research in Economics and Statistics
1/01/15 → 16/12/22
Project: Research