Inequality constraints in the univariate garch model

Daniel B. Nelson, Quanwei Cao

Research output: Contribution to journalArticle

239 Citations (Scopus)

Abstract

To keep the conditional variances generated by the GARCH ip, q) model nonnegative, Bollerslev imposed nonnegativity constraints on the parameters of the process. We show that these constraints can be substantially weakened and so should not be imposed in estimation. We also provide empirical examples illustrating the importance of relaxing these constraints.

Original languageEnglish (US)
Pages (from-to)229-235
Number of pages7
JournalJournal of Business and Economic Statistics
Volume10
Issue number2
DOIs
StatePublished - Jan 1 1992

Fingerprint

GARCH Model
Inequality Constraints
Univariate
Conditional Variance
Generalized Autoregressive Conditional Heteroscedasticity
Nonnegativity
Non-negative
Generalized autoregressive conditional heteroscedasticity
Inequality constraints
GARCH model
Conditional variance
Model

All Science Journal Classification (ASJC) codes

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

Cite this

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abstract = "To keep the conditional variances generated by the GARCH ip, q) model nonnegative, Bollerslev imposed nonnegativity constraints on the parameters of the process. We show that these constraints can be substantially weakened and so should not be imposed in estimation. We also provide empirical examples illustrating the importance of relaxing these constraints.",
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Inequality constraints in the univariate garch model. / Nelson, Daniel B.; Cao, Quanwei.

In: Journal of Business and Economic Statistics, Vol. 10, No. 2, 01.01.1992, p. 229-235.

Research output: Contribution to journalArticle

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