Joint modeling of cointegration and conditional heteroscedasticity with applications

Heung Wong; W. K. Li; Shiqing Ling

doi:10.1007/BF02506881

Joint modeling of cointegration and conditional heteroscedasticity with applications

Heung Wong^*, W. K. Li, Shiqing Ling

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal Article › peer-review

3 Citations (Scopus)

Abstract

A cointegrated vector AR-GARCH time series model is introduced. Least squares estimator, full rank maximum likelihood estimator (MLE), and reduced rank MLE of the model are presented. Monte Carlo experiments are conducted to illustrate the finite sample properties of the estimators. Its applicability is then demonstrated with the modeling of international stock indices and exchange rates. The model leads to reasonable financial interpretations.

Original language	English
Pages (from-to)	83-103
Number of pages	21
Journal	Annals of the Institute of Statistical Mathematics
Volume	57
Issue number	1
DOIs	https://doi.org/10.1007/BF02506881
Publication status	Published - Mar 2005

Keywords

Cointegration
Full rank maximum likelihood estimator
Least squares estimator
Partially nonstationary
Reduced rank MLE
Vector AR-GARCH model

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10.1007/BF02506881

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title = "Joint modeling of cointegration and conditional heteroscedasticity with applications",

abstract = "A cointegrated vector AR-GARCH time series model is introduced. Least squares estimator, full rank maximum likelihood estimator (MLE), and reduced rank MLE of the model are presented. Monte Carlo experiments are conducted to illustrate the finite sample properties of the estimators. Its applicability is then demonstrated with the modeling of international stock indices and exchange rates. The model leads to reasonable financial interpretations.",

keywords = "Cointegration, Full rank maximum likelihood estimator, Least squares estimator, Partially nonstationary, Reduced rank MLE, Vector AR-GARCH model",

author = "Heung Wong and Li, \{W. K.\} and Shiqing Ling",

year = "2005",

month = mar,

doi = "10.1007/BF02506881",

language = "English",

volume = "57",

pages = "83--103",

journal = "Annals of the Institute of Statistical Mathematics",

issn = "0020-3157",

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T1 - Joint modeling of cointegration and conditional heteroscedasticity with applications

AU - Wong, Heung

AU - Li, W. K.

AU - Ling, Shiqing

PY - 2005/3

Y1 - 2005/3

N2 - A cointegrated vector AR-GARCH time series model is introduced. Least squares estimator, full rank maximum likelihood estimator (MLE), and reduced rank MLE of the model are presented. Monte Carlo experiments are conducted to illustrate the finite sample properties of the estimators. Its applicability is then demonstrated with the modeling of international stock indices and exchange rates. The model leads to reasonable financial interpretations.

AB - A cointegrated vector AR-GARCH time series model is introduced. Least squares estimator, full rank maximum likelihood estimator (MLE), and reduced rank MLE of the model are presented. Monte Carlo experiments are conducted to illustrate the finite sample properties of the estimators. Its applicability is then demonstrated with the modeling of international stock indices and exchange rates. The model leads to reasonable financial interpretations.

KW - Cointegration

KW - Full rank maximum likelihood estimator

KW - Least squares estimator

KW - Partially nonstationary

KW - Reduced rank MLE

KW - Vector AR-GARCH model

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000228816600007

UR - https://openalex.org/W2053905577

UR - https://www.scopus.com/pages/publications/23744442346

U2 - 10.1007/BF02506881

DO - 10.1007/BF02506881

M3 - Journal Article

SN - 0020-3157

VL - 57

SP - 83

EP - 103

JO - Annals of the Institute of Statistical Mathematics

JF - Annals of the Institute of Statistical Mathematics

IS - 1

ER -

Joint modeling of cointegration and conditional heteroscedasticity with applications

Abstract

Keywords

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