Testing Garch-X Type Models

Research output: Working paperResearch

Standard

Testing Garch-X Type Models. / Pedersen, Rasmus Søndergaard; Rahbek, Anders.

2017.

Research output: Working paperResearch

Harvard

Pedersen, RS & Rahbek, A 2017 'Testing Garch-X Type Models'.

APA

Pedersen, R. S., & Rahbek, A. (2017). Testing Garch-X Type Models. University of Copenhagen. Institute of Economics. Discussion Papers (Online), No. 17-15

Vancouver

Pedersen RS, Rahbek A. Testing Garch-X Type Models. 2017.

Author

Pedersen, Rasmus Søndergaard ; Rahbek, Anders. / Testing Garch-X Type Models. 2017. (University of Copenhagen. Institute of Economics. Discussion Papers (Online); No. 17-15).

Bibtex

@techreport{3dbd63c3431247628714ad77cd13a28a,
title = "Testing Garch-X Type Models",
abstract = "We present novel theory for testing for reduction of GARCH-X type models with an exogenous (X) covariate to standard GARCH type models. To deal with the problems of potential nuisance parameters on the boundary of the parameter space as well as lack of identification under the null, we exploit a noticeable property of specific zero-entries in the inverse information of the GARCH-X type models. Specifically, we consider sequential testing based on two likelihood ratio tests and as demonstrated the structure of the inverse information implies that the proposed test neither depends on whether the nuisance parameters lie on the boundary of the parameter space, nor on lack of identification. Our general results on GARCH-X type models are applied to Gaussian based GARCH-X models, GARCH-X models with Student's t-distributed innovations as well as the integer-valued GARCH-X (PAR-X) models.",
keywords = "Faculty of Social Sciences, Testing on the Boundary, Likelihood-Ratio Test, Non-Identification, GARCH-X, PAR-X, GARCH Models, Integer-Valued",
author = "Pedersen, {Rasmus S{\o}ndergaard} and Anders Rahbek",
year = "2017",
language = "English",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - Testing Garch-X Type Models

AU - Pedersen, Rasmus Søndergaard

AU - Rahbek, Anders

PY - 2017

Y1 - 2017

N2 - We present novel theory for testing for reduction of GARCH-X type models with an exogenous (X) covariate to standard GARCH type models. To deal with the problems of potential nuisance parameters on the boundary of the parameter space as well as lack of identification under the null, we exploit a noticeable property of specific zero-entries in the inverse information of the GARCH-X type models. Specifically, we consider sequential testing based on two likelihood ratio tests and as demonstrated the structure of the inverse information implies that the proposed test neither depends on whether the nuisance parameters lie on the boundary of the parameter space, nor on lack of identification. Our general results on GARCH-X type models are applied to Gaussian based GARCH-X models, GARCH-X models with Student's t-distributed innovations as well as the integer-valued GARCH-X (PAR-X) models.

AB - We present novel theory for testing for reduction of GARCH-X type models with an exogenous (X) covariate to standard GARCH type models. To deal with the problems of potential nuisance parameters on the boundary of the parameter space as well as lack of identification under the null, we exploit a noticeable property of specific zero-entries in the inverse information of the GARCH-X type models. Specifically, we consider sequential testing based on two likelihood ratio tests and as demonstrated the structure of the inverse information implies that the proposed test neither depends on whether the nuisance parameters lie on the boundary of the parameter space, nor on lack of identification. Our general results on GARCH-X type models are applied to Gaussian based GARCH-X models, GARCH-X models with Student's t-distributed innovations as well as the integer-valued GARCH-X (PAR-X) models.

KW - Faculty of Social Sciences

KW - Testing on the Boundary

KW - Likelihood-Ratio Test

KW - Non-Identification

KW - GARCH-X

KW - PAR-X

KW - GARCH Models

KW - Integer-Valued

M3 - Working paper

BT - Testing Garch-X Type Models

ER -

ID: 182540556