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Inference and testing on the boundary in extended constant conditional correlation GARCH models

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We consider inference and testing in extended constant conditional correlation GARCH models in the case where the true parameter vector is a boundary point of the parameter space. This is of particular importance when testing for volatility spillovers in the model. The large-sample properties of the QMLE are derived together with the limiting distributions of the related LR, Wald, and score statistics. Due to the boundary problem, these large-sample properties become nonstandard. The size and power properties of the tests are investigated in a simulation study. As an empirical illustration we test for (no) volatility spillovers between foreign exchange rates.

OriginalsprogEngelsk
TidsskriftJournal of Econometrics
Vol/bind196
Udgave nummer1
Sider (fra-til)25-36
Antal sider12
ISSN0304-4076
DOI
StatusUdgivet - 1 jan. 2017

ID: 186156997