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

TY - JOUR

T1 - Inference and testing on the boundary in extended constant conditional correlation GARCH models

AU - Pedersen, Rasmus Søndergaard

PY - 2017/1/1

Y1 - 2017/1/1

N2 - 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.

AB - 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.

KW - Boundary

KW - ECCC-GARCH

KW - QML

KW - Spillovers

KW - C32

KW - C51

KW - C58

U2 - 10.1016/j.jeconom.2016.09.004

DO - 10.1016/j.jeconom.2016.09.004

M3 - Journal article

AN - SCOPUS:84992481921

SN - 0304-4076

VL - 196

SP - 25

EP - 36

JO - Journal of Econometrics

JF - Journal of Econometrics

IS - 1

ER -