Persistence in variance, structural change, and the GARCH model

Christopher G. Lamoureux; William D. Lastrapes

doi:10.1080/07350015.1990.10509794

Persistence in variance, structural change, and the GARCH model

Christopher G. Lamoureux, William D. Lastrapes

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

690 Scopus citations

Abstract

This article examines the persistence of the variance, as measured by the generalized autoregressive conditional heteroskedasticity (GARCH) model, in stock-return data. In particular, we investigate the extent to which persistence in variance may be overstated because of the existence of, and failure to take account of, deterministic structural shifts in the model. Both an analysis of daily stock-return data and a Monte Carlo simulation experiment confirm the hypothesis that GARCH measures of persistence in variance are sensitive to this type of model misspecification.

Original language	English (US)
Pages (from-to)	225-234
Number of pages	10
Journal	Journal of Business and Economic Statistics
Volume	8
Issue number	2
DOIs	https://doi.org/10.1080/07350015.1990.10509794
State	Published - Apr 1990
Externally published	Yes

Keywords

Bootstrap
Integration in variance
L-GARCH
Monte Carlo

ASJC Scopus subject areas

Statistics and Probability
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty

Access to Document

10.1080/07350015.1990.10509794

Cite this

@article{7ccbc3421bb94ce88920f237e6df89cc,

title = "Persistence in variance, structural change, and the GARCH model",

abstract = "This article examines the persistence of the variance, as measured by the generalized autoregressive conditional heteroskedasticity (GARCH) model, in stock-return data. In particular, we investigate the extent to which persistence in variance may be overstated because of the existence of, and failure to take account of, deterministic structural shifts in the model. Both an analysis of daily stock-return data and a Monte Carlo simulation experiment confirm the hypothesis that GARCH measures of persistence in variance are sensitive to this type of model misspecification.",

keywords = "Bootstrap, Integration in variance, L-GARCH, Monte Carlo",

author = "Lamoureux, {Christopher G.} and Lastrapes, {William D.}",

year = "1990",

month = apr,

doi = "10.1080/07350015.1990.10509794",

language = "English (US)",

volume = "8",

pages = "225--234",

journal = "Journal of Business and Economic Statistics",

issn = "0735-0015",

publisher = "Taylor and Francis Ltd.",

number = "2",

}

TY - JOUR

T1 - Persistence in variance, structural change, and the GARCH model

AU - Lamoureux, Christopher G.

AU - Lastrapes, William D.

PY - 1990/4

Y1 - 1990/4

N2 - This article examines the persistence of the variance, as measured by the generalized autoregressive conditional heteroskedasticity (GARCH) model, in stock-return data. In particular, we investigate the extent to which persistence in variance may be overstated because of the existence of, and failure to take account of, deterministic structural shifts in the model. Both an analysis of daily stock-return data and a Monte Carlo simulation experiment confirm the hypothesis that GARCH measures of persistence in variance are sensitive to this type of model misspecification.

AB - This article examines the persistence of the variance, as measured by the generalized autoregressive conditional heteroskedasticity (GARCH) model, in stock-return data. In particular, we investigate the extent to which persistence in variance may be overstated because of the existence of, and failure to take account of, deterministic structural shifts in the model. Both an analysis of daily stock-return data and a Monte Carlo simulation experiment confirm the hypothesis that GARCH measures of persistence in variance are sensitive to this type of model misspecification.

KW - Bootstrap

KW - Integration in variance

KW - L-GARCH

KW - Monte Carlo

UR - http://www.scopus.com/inward/record.url?scp=0000942739&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0000942739&partnerID=8YFLogxK

U2 - 10.1080/07350015.1990.10509794

DO - 10.1080/07350015.1990.10509794

M3 - Article

AN - SCOPUS:0000942739

SN - 0735-0015

VL - 8

SP - 225

EP - 234

JO - Journal of Business and Economic Statistics

JF - Journal of Business and Economic Statistics

IS - 2

ER -

Persistence in variance, structural change, and the GARCH model

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this